Might be interesting132
Women & AIjournal
OpenAlex·16 September 2026·Thomas Brüggemann, Ulrich Ludewig, Ramona Lorenz, Nele McElvany·Journal of Psychoeducational Assessment, tier 3
A within and between subjects experimental design finds girls report slightly more end-of-test anxiety on computer adaptive tests than boys, N=253 fourth graders. The effect is small and the finding only confirms the library's existing pattern that women and girls report higher technology and test anxiety, so it does not change what she would say.
Companies & AIbusiness
MIT Sloan Management Review·14 September 2026·Melissa Swift, Teryluz Andreu, and Dolores Hernandez·tier 1
Draws on interviews with AI experts from a joint Anthrome Insight-Axialent study describing a 'capability mirage', where polished GenAI output masks eroding individual skill and damages team trust. The claim is a plausible mechanism but rests on qualitative expert opinion rather than measured skill data, so it is credible opinion, not primary evidence.
Companies & AIbusiness
MIT Sloan Management Review·10 September 2026·Rory McDonald and Will Drover·tier 1
McDonald and Drover argue AI has made organizational disruption permanent and propose three practices, permanent infrastructure, split cadences, embedded learning, to manage employee change fatigue. This is a credible conceptual argument extending disruption theory, but it offers no measured outcome data, so it counts as sound opinion rather than primary evidence.
Companies & AIbusiness
MIT Sloan Management Review·8 September 2026·Elizabeth M·tier 1
Reports that 72% of an MIT Sloan and BCG expert panel agree treating AI agents as fully autonomous decision makers will undermine accountability. It is a real proprietary panel survey with a number attached, but the panel is a small expert sample debating terminology, not a population-level adoption finding, so it counts as credible expert opinion rather than decisive primary evidence.
Companies & AIbusiness
MIT Sloan Management Review·26 August 2026·Kevin J·tier 1
Argues generative AI is scaling fast but the surrounding technological and institutional architecture is not yet 'platformed', so companies should invest in complements and durable capabilities rather than raw model access. This is a credible strategic argument with market figures as illustration, not an empirical adoption study, so it stays at credible opinion.
Companies & AIbusiness
Deloitte Insights·12 August 2026·tier 2
A 500+ leader Deloitte survey adds specific numbers on agentic AI readiness (only 15% at scaled multi-agent adoption, 72% lacking unified data), but it restates the already well-documented pattern that deployment outpaces process and governance readiness.
Companies & AIjournal
OpenAlex·1 August 2026·Jonathan Westover·Future of Work The Journal of Labor Transformation Technology Integration and Human Adaptation, tier 3
A mixed-methods study of 187 survey respondents, 42 interviews and experimental vignettes finds perceived decision-making autonomy predicts moral engagement (beta 0.47) and that algorithmic mediation reduces ethical accountability by 32 percent versus baseline. The vignette component gestures at an experimental design but the journal is an obscure tier 3 outlet and the finding sits adjacent to, rather than advancing, the library's existing identity-threat and resistance mechanisms, so it stays a might-read.
Companies & AIjournal
OpenAlex·31 July 2026·Chao Ni, Xiaohan Wang, L Chen, Yuexiang Yang, Zhiqiang Zhang·Sustainability, tier 3
Uses Chinese A-share panel data with fixed effects, instrumental variables, difference-in-differences and an event study to show quality management drives enterprise AI adoption and performance, which clears the tier 3 causal-design exception. But the abstract frames its payoff around ownership type and eastern versus other Chinese regions, a local-population claim rather than a pure mechanism claim, so it drops one level.
Companies & AIjournal
OpenAlex·26 July 2026·Nolan Lovett·Human Resource Development Review, tier 2
A conceptual framework arguing AI adoption could deplete the shared expertise professions need to renew themselves, credible and relevant but explicitly theoretical with no primary data of its own, so it stays at credible opinion rather than must-read.
Companies & AIjournal
OpenAlex·16 July 2026·Qiuhan Zhu, Xiangnan Li, Yiang Dong, Pengcheng Chang, Mengmeng Fan·Frontiers in Psychology, tier 3
A three-wave survey of 589 students and early-career workers distinguishes dependent from autonomous cognitive offloading to generative AI, finding dependent offloading undermines intrinsic motivation while autonomous offloading supports it, a useful new distinction, but the tier 3 venue and a self-report time-lagged design short of the named causal designs keep it below must-read.
Women & AIjournal
OpenAlex·13 July 2026·Farhad Mirkhil·Future Business Journal, tier 2
A cross-sectional survey of 349 employees in India's BFSI sector finds AI anxiety negatively predicts performance and is higher among women, but it is framed around a specific Indian sector population and its gender finding mainly confirms what the library already holds about women reporting higher AI anxiety.
Women & AIjournal
OpenAlex·1 July 2026·Hüseyin Gökal, Aytekin İŞMAN, Deniz Ay Usta·Turkish Online Journal of Distance Education, tier 3
Cross-sectional survey of 325 Turkish IT students finds AI attitudes do not predict job-seeking anxiety, but male students report higher job-seeking anxiety than female students, which runs counter to the library's consistent finding of women reporting higher AI anxiety. Tier 3 venue with no causal design and a single-country student sample caps it below a must-read.
Women & AIjournal
OpenAlex·27 June 2026·Derya Girgin, Gökhan Ilgaz, EYLEM YALÇINKAYA ÖNDER·Journal of Education Culture and Society, tier 3
Secondary analysis of ICILS 2018 and 2023 across 13 countries finds a persistent but narrowing gender gap in specialised ICT self-efficacy, and that specialised self-efficacy negatively predicts literacy scores. This confirms the library's existing self-efficacy gap findings rather than adding a new mechanism, and the tier 3 venue with no causal design caps it at medium.
Companies & AIbusiness
Deloitte Insights·18 June 2026·tier 2
A 200-executive retail/CPG survey quantifies a say-do gap (75% priority, 16.5% can quantify ROI) and notes AI ownership sits with tech leaders rather than P&L owners, but this is another variant of the adoption-ahead-of-execution finding already in the library.
Women & AIjournal
OpenAlex·9 June 2026·Philipp Brauner, Felix Glawe, Gian Luca Liehner, Luisa Vervier, Martina Ziefle·Acta Psychologica, tier 2
An exploratory Germany-China survey on AI risk-benefit perceptions and values, but the retrieved abstract is truncated and reports no concrete number or mechanism beyond vague cognitive-map contrasts, so it cannot be weighed as a must-read even though the cross-cultural AI-attitudes topic fits her themes.
Companies & AIbusiness
IBM·8 June 2026·tier 2
A 2,000-CxO IBM survey reports two thirds are accountable for AI systems they do not control and 77% say governance lags deployment, but this is the same governance-lags-adoption story the library already documents extensively, just with new percentages.
Women & AIjournal
OpenAlex·8 June 2026·Weina Ni, J C Li·Frontiers in Psychology, tier 3
A scoping review of 87 studies proposes a conceptual 'Psychosocial-Equity Nexus' linking psychological states and equity stratifiers in generative AI use in higher education, including gender disparities. It is a secondary synthesis rather than primary data, and the tier 3 venue with no causal design cannot carry a must-read regardless of the framework's ambition.
Companies & AIbusiness
Deloitte Insights·2 June 2026·tier 2
Polling nearly 3,700 professionals, it finds 48% added AI without redesigning workflows versus 12% doing full redesign, confirming the library's existing finding that adoption metrics diverge from real transformation.
Companies & AIjournal
OpenAlex·2 June 2026·John Dickens, Hasan Uvet, Antonina Bauman, Hee Yoon Kwon·Journal of Knowledge Management, tier 2
Factor analysis on two phases of business-practitioner survey data proposes a unifying 'big six' AI trust model and a 20-item scale. It adds a consolidated instrument but mainly reorganizes dimensions the library already documents, such as separable cognitive and emotional trust components, so it confirms more than it changes.
Companies & AIjournal
OpenAlex·28 May 2026·Răzvan-George Cotescu·INTERNATIONAL JOURNAL OF MARKETING & HUMAN RESOURCE MANAGEMENT, tier 3
Using 2025 Eurostat enterprise data across 27 EU states, the study finds a firm-size gradient in AI adoption that persists after country fixed effects, adding an official-statistics number to the survey-versus-reality adoption debate already in the library. The size-adoption relationship itself is expected and the design is correlational, not causal, so it stays at might-read despite the tier 3 venue not blocking a medium rating.
Companies & AIjournal
OpenAlex·26 May 2026·Johanathan Woodworth, Emily Ballantyne·American Journal of STEM Education, tier 3
A mixed-methods case study at one Canadian university finds limited current GenAI use, strong anticipated use, and concerns about integrity, trust and workload among faculty, then proposes a relational-affective layer to policy frameworks. Tier 3 venue and the finding mostly restates concerns the library already documents in detail, so it is a might, not a must.
Companies & AIjournal
OpenAlex·22 May 2026·Brahim Bergougui, Hamid Ghazi H Sulimany, Abdulrahman Atllah Alharbi·Corporate Social Responsibility and Environmental Management, tier 2
Panel data on Chinese listed firms from 2012 to 2022 finds AI language models curb ESG greenwashing through workforce skill restructuring and performance channels, with threshold nonlinearities by regulation intensity. Primary panel evidence and a stated mechanism, but the topic, corporate greenwashing measurement, sits at the edge of her organisational-adoption and gender themes rather than squarely in them.
Companies & AIbusiness
IBM·18 May 2026·tier 2
A 2,000-CEO IBM survey finds only 25% of workers use AI regularly despite 86% of CEOs believing them ready, and that redesigning five core business areas made firms 4x more likely to hit objectives. The core claim, that redesign beats bolt-on adoption, is already established in the library.
Companies & AIjournal
OpenAlex·15 May 2026·Thomas Montefiore, Paul Formosa, Sarah Bankins, Siavosh Sahebi·Journal of Business Ethics, tier 2
A conceptual paper integrating Amabile's creativity model with meaningful-work theory to argue GenAI both democratises and deskills creative work, naming an AI-use penalty and rising precarity as structural effects. It is credible synthesis rather than new primary data, and its themes of identity threat, autonomy erosion and status loss are already well covered in the employee-layer and identity-threat records.
Companies & AIjournal
OpenAlex·8 May 2026·Siran Wang, Qiang Yan, J. Leng·Kybernetes, tier 2
A 409-person PLS-SEM study finds AI intransparency and hallucination raise 'AI control anxiety,' which hurts brainstorming performance and idea selection, moderated by coping flexibility. It adds a named mediator but sits within the technostress and AI-anxiety territory the library already documents extensively.
Companies & AIjournal
OpenAlex·4 May 2026·LiMing Zhu, Qinghua Lu, Ming Ding, Sung Une Lee, Chen Wang·AI and Ethics, tier 2
A conceptual framework proposing layered human and AI agency and 'external reasoning faithfulness' as sufficient for oversight, with a catalogue of design patterns. It is a credible theoretical contribution with no primary data behind it, so it stays at credible opinion rather than must read.
Companies & AIjournal
OpenAlex·1 May 2026·Zeynep Engin·Journal of Responsible Technology, tier 2
A theoretical governance framework (HAIG) proposing trust thresholds and human oversight for autonomous AI systems in organisations. It is credible academic argument but carries no primary data, so it earns a might-read rather than a must-read.
Companies & AIjournal
OpenAlex·29 April 2026·Philipp Brauner, Felix Glawe, Gian Luca Liehner, Luisa Vervier, Martina Ziefle·AI & Society, tier 2
A large German study (1,100 public, 119 experts) quantifies that the public weighs risk more heavily than experts in judging AI (beta -0.361 vs -0.195) across 71 scenarios. The finding is solid primary data but is about societal risk perception rather than company adoption, women, or individual AI use, so it fits her themes only loosely.
Companies & AIjournal
OpenAlex·17 April 2026·Michaela Doubková, Martin Magdin·Management & Marketing, tier 2
A 2020 to 2025 literature review concludes AI mostly augments rather than replaces jobs and that governance, not technology, determines outcomes. It is a synthesis rather than primary evidence, and it largely restates the augmentation versus automation framing the library already holds.
Companies & AIjournal
OpenAlex·17 April 2026·Cristiana Tudor·Algorithms, tier 3
Using harmonized Eurostat enterprise data, this predictive model finds cloud CRM and e-sales capability, not general digital readiness, are the strongest predictors of high AI adoption across European firms, a capability-complementarity mechanism not yet in the library. It is explicitly a predictive, not causal, analysis in a tier 3 venue, so the causal-design exception does not apply and it cannot clear a must-read.
Women & AIjournal
OpenAlex·13 April 2026·Shooroq Mohammed Maberah, Mohammed Abu Al-Rub·Frontiers in Education, tier 3
A quasi-experimental field study (intervention vs control, n=45) shows an adaptive AI tutor raised digital literacy and self-efficacy for women with disabilities in Jordan. It is a sound, relevant addition to the 'what closes the gap' theme but is tier 3 without a randomized or clearly causal design, and it largely confirms the library's existing pattern that targeted interventions close gaps.
Companies & AIjournal
OpenAlex·13 April 2026·Hanne Shapiro, Manuel Souto‐Otero, Richard Watermeyer·Learning Media and Technology, tier 3
A conceptual argument that AI literacy should be reframed as a collective, metacognitive practice rather than a skills checklist, illustrated with case studies. It is credible opinion rather than primary evidence, so it caps at might-be-interesting regardless of venue.
Companies & AIjournal
OpenAlex·7 April 2026·Sven Kottmann, Jürgen Seitz·Journal of theoretical and applied electronic commerce research, tier 3
An extended UTAUT test on 106 professionals using a chatbot decision-support tool, tier 3 venue, no randomised design named despite the word experimental. It largely reconfirms performance expectancy, effort expectancy and social influence as drivers, which the library's UTAUT holdings already establish, though it adds cognitive load and source trustworthiness as secondary paths.
Companies & AIjournal
OpenAlex·3 April 2026·Leandro Bitetti, Carmine Garzia, Emanuele Carpanzano·Administrative Sciences, tier 3
A three-round Delphi panel of GenAI consultants and managers proposing a function and readiness framework for SME value creation. This is structured expert opinion rather than primary data, so per the rubric it is credible opinion at best; it does add a distinction between efficiency- and growth-oriented GenAI functions with organisational readiness dominating, but tier 3 and its opinion basis keep it from a must-read.
Companies & AIjournal
OpenAlex·1 April 2026·Xuehan Zhu, Aiai Zhang, Jiacheng Zhang·Behavioral Sciences, tier 3
A cross-sectional SEM study of 576 AI users finds self-efficacy erosion mediates the link between instant gratification, perceived AI efficacy, and AI dependency. This names a feedback mechanism, heavy AI use eroding the self-belief that then deepens dependency, that the library's self-efficacy holdings do not cover, but it is survey based with no causal design and sits in a tier 3 venue, so it cannot clear must-read.
Companies & AIjournal
OpenAlex·1 April 2026·Chunqu Xiao, Tianshu Zhou, Qingyi Li, Yayu Zhou·Asia Pacific Journal of Marketing and Logistics, tier 2
Four experiments show brand inclusivity raises consumer approval of AI-designed products through perceived consistency, a genuine mechanism from a tier 2 venue. But it is a consumer marketing study about reactions to a brand's AI use, not about an organisation adopting AI or an individual or woman putting AI to work, so it only loosely fits her themes and sits at might rather than must.
Companies & AIbusiness
Deloitte Insights·31 March 2026·tier 2
A 1,587-firm survey reports 86% of family businesses use AI with high reported satisfaction, but the finding that adoption is broad while structured strategy lags is already well covered by the practitioner-shelf literature.
Women & AIjournal
OpenAlex·28 March 2026·Glenys Oberg, Yifei Liang, Margaret Bearman, Tim Fawns, Michael Henderson, Kelly Matthews·Higher Education, tier 3
A large national survey (n=8021) plus focus groups documents ambivalence, moral emotions and institutional affective climates around student AI use, but it is qualitative-descriptive not a causal design, so tier 3 blocks a must-read. It largely confirms what the library already holds about AI ambivalence and dual benefit/concern feelings, with richer texture but no new number.
Companies & AIjournal
OpenAlex·28 March 2026·Yu Gao, Qiming Zhang, Shiyuan Huang, Na Li·International Review of Economics & Finance, tier 2
Panel data (2009-2023) on Chinese listed media firms finds AI adoption boosts innovation mainly by suppressing corporate financialization and reallocating capital to R&D, a genuinely new channel. But the heterogeneity claim is framed around Chinese state-owned versus non-state firms specifically, a local population claim rather than a general mechanism claim, so it drops a level from what would otherwise be a must-read.
Companies & AIjournal
OpenAlex·26 March 2026·Jan Zacharias, Alina Popova, Moritz von Zahn, Johannes Chen, Oliver Hinz·Business & Information Systems Engineering, tier 2
Thirty expert interviews describe GenAI's effects on developer productivity, over-reliance, skill degradation and declining team communication. It is qualitative and largely restates the identity-threat and resistance mechanisms already well documented in the library, with social-capital erosion as the main new angle, not enough to override the confirmatory pattern.
Companies & AIjournal
OpenAlex·26 March 2026·Brent Winslow, Özlem Özmen Garibay, Tesh Goyal, Sean Koon, George Margetis, Gavriel Salvendy, Ben Shneiderman, Aida Tayebi·International Journal of Human-Computer Interaction, tier 2
A position paper revisiting six human-centered AI grand challenges for the generative era, with no primary data, essentially a credible expert opinion piece setting a research agenda. Per the rubric this caps at might-be-interesting.
Companies & AIjournal
OpenAlex·25 March 2026·Michael Hahn, Max Tretter, Peter Dabrock·AI and Ethics, tier 2
A conceptual ethics paper applying classical principles (transparency, justice, non-maleficence) to agentic AI, using reflective equilibrium rather than empirical data. Credible opinion piece, so it sits at might-be-interesting rather than must-read.
Companies & AIjournal
OpenAlex·24 March 2026·Yuanzhe Liu, Hongzhen Lei, Xiaoqian Qu·Frontiers in Psychology, tier 3
A multi-wave employee-leader dyad survey in China introduces a validated AI Job Crafting Scale and a dual approach/avoidance pathway to career sustainability, but it is correlational, tier 3, and largely extends rather than overturns the library's existing identity-threat and resistance mechanisms.
Women & AIjournal
OpenAlex·20 March 2026·Nuo Chen, Zhiyuan Lai, Yichu Liu, Jia Ming Li, Rui Wang, Pu Yan·Information Research, tier 3
A randomized field experiment (n=60) with eye-tracking finds simple AI disclosure raises trust in bots but lowers trust and sharing for news, with light versus heavy internet users responding oppositely; the causal design would carry a tier 3 venue, but the small, locally framed Henan sample and existing trust-disclosure literature pull it down a level.
Women & AIjournal
OpenAlex·19 March 2026·Héla Mzoughi, Arafet Farroukh, Martina Metzger·FinTech, tier 3
A cross-country PCA-based FinTech index finds financial inclusion via FinTech benefits male account ownership more in developing economies but is more gender-balanced in high-income ones, adding a new numeric wrinkle to the digital gender divide, but it is correlational and sits in a tier 3 venue with no causal design.
Companies & AIjournal
OpenAlex·19 March 2026·Ojelanki Ngwenyama, Stefan Klein, Frantz Rowe·European Journal of Information Systems, tier 1
A tier 1 case study using Marx's subsumption theory to show how Elsevier's GenAI-reinforced platforms progressively sideline academics from knowledge production, a genuine mechanism with real evidence. It sits adjacent to her power-and-resistance classics but is about academic publishing political economy rather than workplace AI adoption, so it is credible and rigorous without squarely fitting her themes.
Companies & AIjournal
OpenAlex·17 March 2026·Oluseye Olugboyega, Daniel Oluwatobu Olowoniyi, Victor Iyanuoluwa Abiri, Olabisi Olabayo Ogunniyi, Silas Bisola Olatunji·Engineering Construction & Architectural Management, tier 3
A cross-sectional survey of construction managers finds GenAI competencies, especially scheduling, documentation automation and design support, positively associated with work-life quality and balance, a different result from the library's finding that AI adoption reduced psychological safety and raised depression. Tier 3 venue and no causal design keep it below a must-read despite the contrasting angle.
Companies & AIjournal
OpenAlex·13 March 2026·Fatma Nur Cicin, Güney Çetin Gürkan·Frontiers in Digital Health, tier 3
Survey of 414 physicians finds trust fully mediates TAM and TPB constructs' effect on AI adoption intention, with ease of use the strongest driver of trust. This restates what the library's trust-in-AI and TAM sections already establish about ease of use and trust dominating adoption, so it is sound but confirmatory.
Women & AIjournal
OpenAlex·12 March 2026·Roza Sh. Akhmadieva, Regina G. Sakhieva, Maria A. Khvatova, Natalya S. Erokhova, Zhanna M. Sizova, Natalya N. Shindryaeva·Contemporary Educational Technology, tier 3
Correlational study finding male and upper-grade students have higher AI literacy and more positive AI attitudes, explaining 38.6% of literacy variance, and negative attitudes correlate with lower literacy. This restates the adoption-gap and literacy-confidence findings the library already holds extensively, so it is sound but not new.
Companies & AIjournal
OpenAlex·9 March 2026·J. WANG, Bing Bai, Qi An·Frontiers in Psychology, tier 3
A mixed-methods study (n=590 survey, 30 interviews) of Chinese college students finds perceived ease of use and technological expectations predict AI-literacy behavior through perceived impressions and group needs. The core drivers, ease of use and expectancy pathways, mirror what the acceptance-model library already holds, and the tier 3 venue with a correlational design caps it below must-read.
Women & AIjournal
OpenAlex·7 March 2026·Andrea Bueno Baquero, José Antonio González-Calero, Javier del Olmo-Muñoz, María del Carmen Sánchez Pérez·Education and Information Technologies, tier 3
A large survey (n=3828) of Spanish teachers finds a level-by-gender interaction: male primary teachers report higher digital competence than female primary teachers, but the pattern reverses in secondary education. That interaction is a genuine nuance the library's simpler gender-gap findings do not capture, but the study is locally framed, tier 3, and correlational, so it cannot clear the must-read bar.
Companies & AIjournal
OpenAlex·6 March 2026·Jihye Choi, Seunggyu Kang, J.E. Moon, Soobean Jeon, Sesil Lim·Journal of theoretical and applied electronic commerce research, tier 3
A discrete choice experiment segments robo advisor users into high expertise investors who want personalization and control versus general consumers who want explainability, and shows a segmented design beats a uniform transparency mandate for adoption. Tier 3 venue, and the finding refines rather than overturns the library's existing transparency threshold and explainability distinctions, so it stays a might.
Companies & AIjournal
OpenAlex·6 March 2026·Yufeng Zhang, Xiaojun Wang, Shlomo Y. Tarba, Andy Neely·Technovation, tier 2
Inductive case studies across four sectors build a conceptual ORTA framework for structuring human-AI handoffs in innovation processes, but it offers a typology rather than a measured mechanism or number. Tier 2 venue, sound but theoretical, so it confirms rather than moves the needle on what she already knows about automation-versus-augmentation design choices.
Companies & AIjournal
OpenAlex·5 March 2026·Ana Bracic, Kayte Spector-Bagdady, Sophie Towle, Rina Zhang, Cornelius A. James, W. Nicholson Price·JAMA Network Open, tier 3
A preregistered conjoint experiment with randomized attributes across 36,000 observations finds patients trust physician expertise and formal governance certification over AI performance claims, a genuine causal design that would clear the tier 3 bar. It stays a might because the population is patients choosing medical encounters, not companies adopting AI or an individual professional using it, so the theme fit is weak.
Companies & AIjournal
OpenAlex·4 March 2026·Claudia-Elena Țuclea, Luciana-Floriana Poenaru·Merits, tier 3
This is the Romanian Gen Z PLS-SEM study the library already flags as the closest published test of psychological safety enabling AI use, finding usefulness as the strongest driver and technostress weakening the safety-to-ease-of-use link. It restates rather than extends what the library already holds on that exact sample, so it stays a might.
Companies & AIjournal
OpenAlex·4 March 2026·Laura Wittich, Hendrikje Rödiger, Tanja Rombey, Anna-Lena Brecher, Lena Kraft, Sophia Sgraja, Viktoria Stein, Cornelia Henschke·Implementation Science Communications, tier 3
A large scoping review of 238 studies on digital health technology implementation, but it is a synthesis with no causal design, so the tier 3 venue rules out a must-read. Its top findings, resistance to change and organisational leadership gaps, are already held in the library's implementation classics.
Companies & AIjournal
OpenAlex·3 March 2026·Edlin Garcia Colato, Nianjun Liu, Angela Chow, Catherine M. Sherwood-Laughlin, Jonathan T. Macy·JMIRx Med, tier 3
A cross-sectional survey of 357 US IT professionals reports specific odds ratios linking ransomware exposure, decision-making under uncertainty, and mental health outcomes. It is sound and adds concrete numbers to the technostress literature, but the tier 3 venue and cross-sectional design rule out a must-read.
Companies & AIjournal
OpenAlex·1 March 2026·David Dowell, Robert Bowen, Wyn Morris·Journal of Rural Studies, tier 3
Using the UK Longitudinal Survey for Small Business, a probit analysis of rural SME AI adoption finds networking, prior innovation activity, and firm size predict adoption. The analysis appears cross-sectional rather than exploiting the panel structure causally, and the finding is framed around rural SMEs specifically, so it stays a tier 3 study that mostly reconfirms known diffusion drivers.
Companies & AIjournal
OpenAlex·1 March 2026·Oliver Schilke, Reinhard Bachmann, Kirsimarja Blomqvist, Rekha Krishnan, Jörg Sydow·Organization Studies, tier 1
This is a special-issue introduction summarizing five embedded studies rather than a primary study itself, so it does not meet the primary-evidence bar even in a tier-1 venue. It does surface a genuine mechanism, that digital affordances can catalyze institution-based trust and that shared vocabulary aligned with identity lets trust cross unit boundaries, but this refines rather than overturns what the library already holds on calibrated and earned trust.
Women & AIjournal
OpenAlex·28 February 2026·Şevki Işıklı, Esra Fatma FAZLIOĞLU·Feminist Encounters A Journal of Critical Studies in Culture and Politics, tier 2
A systematic literature review arguing that digital technologies simultaneously offer emancipatory potential and reproduce patriarchal patterns via cyberviolence, algorithmic bias, and STEM underrepresentation. It is a synthesis rather than new primary evidence, and its core claims about digital exclusion and STEM gaps are already established in the library's digital-divide and self-efficacy sections.
Companies & AIjournal
OpenAlex·28 February 2026·Norma Ghamrawi, Norma Ghamrawi, Tarek Shal, Najah A. R. Ghamrawi, Najah A. R. Ghamrawi·School Leadership and Management, tier 3
A qualitative interview study across Arab-state teacher leaders finding that AI integration redefines rather than diminishes leadership authority through recalibrated practices and distributed agency. Tier 3 with no causal design caps it below must-read, and the identity-renegotiation mechanism it describes echoes what the library's professional-identity-threat literature already shows.
Companies & AIjournal
OpenAlex·28 February 2026·Imo Enang, Patrick Mukala, Ubong Nkereuwem·Systems, tier 3
A three-stage mixed-methods study of 50 manager interviews cross-mapped against 685 EU JRC AI-implementation cases and 37 documented failures, proposing a socio-technical governance taxonomy with twelve failure modes. It is a substantial empirical effort but the design is configurational mapping, not a randomised, panel, or event-study design, so the tier 3 venue caps it at might rather than must.
Companies & AIjournal
OpenAlex·26 February 2026·Sylwia Przytuła, Martina Rašticová, Natalia Versal, Pawan Kumar Mishra·Humanities and Social Sciences Communications, tier 3
Fifteen interviews with senior academics in three countries describe technostress and coping strategies during digitalization, which is sound but confirms what the library already holds about anxiety and coping under technostress. Tier 3 venue and small local qualitative sample rule out a must-read regardless.
Women & AIjournal
OpenAlex·26 February 2026·Hui Zhang, Yiming Jing, Ruolei GU·Behavioral Sciences, tier 3
Cross-cultural survey finds a consistent trust hierarchy, AI trusted less than close others but more than distant others, with embodied AI read through interpersonal trust schemas in China versus tool-like treatment in the US. The mechanism is a genuine addition to the trust literature, but it is a mediation survey, not a causal design, and the venue is tier 3, so it cannot pass the venue rule for a must-read.
Companies & AIjournal
OpenAlex·25 February 2026·Cong Fang, Mingyuan Zhang, Paul Vinod Khiatani, Huan Lin, Wei Liu, Stephen Jia Wang·Humanities and Social Sciences Communications, tier 3
A 607-respondent UTAUT comparison finds trust matters for GenAI adoption among UK design professionals but not Chinese ones, while resource access moderates more strongly in China, a real contextual nuance. It stays medium because the venue is tier 3 with no causal design, which blocks a must-read regardless of the finding's interest.
Companies & AIjournal
OpenAlex·25 February 2026·Ahmed Tantawy, Samar Abdalla, Poh Yen Ng, Joseph Amankwah-Amoah·Journal of Small Business Management, tier 2
Survey of 300 UK SME owners finds entrepreneurial self-efficacy mediates the digitalization-resilience link, moderated by passion, a specific mechanism rather than a mere confirmation. It is demoted from what would otherwise be a must-read because the finding is framed around a UK SME sample rather than a general mechanism.
Women & AIjournal
OpenAlex·24 February 2026·Ntombikayise Nkosi, Mncedisi Christian Maphalala·Gender Issues, tier 2
A PRISMA systematic review of the gendered digital divide in higher education, synthesizing a decade of studies on literacy, barriers and institutional bias. It is a secondary review rather than primary evidence, and its findings largely restate what the library's digital divide section already holds.
Companies & AIjournal
OpenAlex·24 February 2026·Cassandra E. Hayes·Journalism and Media, tier 3
Qualitative interviews with journalists describe how they manage technostress and diffusion-of-innovation stages, but this mirrors what the library already holds on technostress and adoption theory. Tier 3 venue and no causal design keep it capped at might.
Companies & AIbusiness
IBM·23 February 2026·tier 2
A 400-leader IBM/Oxford Economics survey finds only 25% are confident their infrastructure can scale AI, reinforcing the library's existing point that AI problems are systems and governance problems, not new evidence.
Companies & AIjournal
OpenAlex·23 February 2026·Afef Saihi, Vian Ahmed·International Journal of Educational Technology in Higher Education, tier 3
A clustering study finds four generative-AI adoption personas among 192 higher-education users, echoing the persona-typology approach the library already treats with caution. Tier 3 and a cross-sectional design keep it from clearing must-read, but the method is more disclosed than the marketing-quiz personas already catalogued.
Companies & AIjournal
OpenAlex·23 February 2026·Qijia Zhang, Qin Wang, Yutao Liang, Ke Zhang, Hao Hu·Frontiers in Sustainable Food Systems, tier 3
Panel data on Chinese A-share agricultural firms (2007-2023) with fixed-effects models show AI raises total factor productivity mainly through labour reallocation and inter-firm resource sharing, not R&D collaboration, a mechanism finding that clears the tier-3 bar via linked panel data. The finding is framed around a specific population, Chinese listed agricultural firms, which drops it one level since the library already holds a similar general finding that AI investment lifts firm growth.
Companies & AIjournal
OpenAlex·21 February 2026·Zhu, Yang·Behavioral Sciences, tier 3
A survey of graduate students finds generative-AI use predicts research competence through critical thinking, moderated by self-efficacy, a correlational finding that echoes the library's existing self-efficacy and mediation literature rather than adding a new mechanism. Tier 3 and a cross-sectional design cap it below must-read.
Companies & AIjournal
OpenAlex·20 February 2026·Llewellyn E. van Zyl·The Journal of Positive Psychology, tier 2
A conceptual framework paper proposing six human capacities threatened by AI optimisation of wellbeing, built on cognitive offloading and automation bias mechanisms already known to the library. It is theory and argument, not primary data, so it stays at credible opinion rather than must-read.
Women & AIjournal
OpenAlex·19 February 2026·Alaa Zuhir AL-Rawashda, Laid Bouakaz, Asma Rebhi Al-Arab·Contemporary Educational Technology, tier 3
A survey of 608 UAE university students found no significant gender difference in ChatGPT awareness, a data point that runs against the adoption-gap pattern the library otherwise holds. It is tier 3 and locally framed so it cannot rise higher, but the null gender result is worth noting against the existing evidence base.
Companies & AIjournal
OpenAlex·19 February 2026·Lingfei Wu, Bogdan Vasilescu·Science, tier 1
Published in Science, a tier 1 venue, but the supplied text is a one-line placeholder with no stated finding, mechanism or number to weigh against the rubric. Without visible evidence of what was actually found, it cannot be elevated past credible-but-unverified.
Companies & AIjournal
OpenAlex·19 February 2026·Cleotilde Gonzalez, Kate Donahue, Daniel G. Goldstein, Hoda Heidari, Mohammad S. Jalali, Beau G. Schelble, Aarti Singh, Anita Williams Woolley·PNAS Nexus, tier 2
A multi-author conceptual framework for human-AI complementarity in decision making, covering trust calibration and role partitioning that overlap with the library's existing automation-versus-augmentation and trust-calibration findings. It is a synthesis and design proposal, not primary data, so it stays at might-be-interesting.
Companies & AIjournal
OpenAlex·18 February 2026·Diane Vassallo·Journal of Academic Ethics, tier 3
A mixed-methods survey of 109 academics introduces an 'AI Guilt Complex' with four adoption profiles and a finding that anticipatory credibility guilt exceeds post-use remorse, which extends the library's 'AI feels like cheating' finding with a new emotional mechanism. It sits in a tier 3 venue with a 3.5% response rate and no causal design, and the authors themselves call it exploratory, so it cannot clear the must-read bar.
Women & AIjournal
OpenAlex·17 February 2026·Yıldız Yıldırım, Tuba GÜNDÜZ, Melek Gülşah Şahin·Current Psychology, tier 2
A tier 2 reliability-generalization meta-analysis pools 25 studies of the AI Anxiety Scale and finds high pooled alphas, with the ratio of women in a sample significantly predicting the alpha for the job-replacement subscale. It is a useful psychometric confirmation rather than a new mechanism, so it stays at might.
Companies & AIjournal
OpenAlex·17 February 2026·Anurag Shekhar, Musawenkosi D. Saurombe·Frontiers in Psychology, tier 3
A tier 3 mixed-methods study of 1,454 Reddit posts finds algorithmic anxiety splits into three discourse clusters and seven themes including eroded identity and devalued expertise, adding texture to psychological-contract theory. It largely restates identity threat and technostress findings the library already holds, so it stays at might.
Women & AIjournal
OpenAlex·16 February 2026·Laure Lu Chen, Zemin Guo, Qianru Liang·Frontiers in Psychology, tier 3
A meta-analysis of 43 studies across 31 regions finds a small but consistent female advantage in measured digital literacy performance, g = +0.14, larger in more developed regions, which nuances the library's self-efficacy-gap findings but the venue is tier 3 and the design is correlational rather than causal, so it cannot clear the bar for a must-read.
Women & AIjournal
OpenAlex·14 February 2026·Sinem Burcu UĞUR, Nehir Yasan Ak, Aylin Çiçekli·Healthcare, tier 3
A qualitative case study of 13 older women in a digital competence training program finds gains in autonomy, confidence and connectedness beyond technical skill. This confirms what the library already holds about training and safe spaces closing the gap, and the small qualitative sample in a tier 3 venue keeps it from being more than that.
Companies & AIjournal
OpenAlex·13 February 2026·Huiwen Zou, Ka Ian Chan, Patrick Cheong‐Iao Pang, Blandina Manditereza, Yi-Huang Shih·Education Sciences, tier 3
A quasi-experimental study of 148 CS students over a 16-week AI-and-ethics curriculum finds performance and effort expectancy became non-significant while hedonic motivation dominated intention and habit, with ethical awareness acting as a cognitive brake on dependence. This extends but mostly echoes the library's existing finding that emotion and technology anxiety often outweigh utilitarian beliefs in generative-AI studies, and without a control group or randomization the tier 3 venue rule keeps it from a must-read.
Companies & AIjournal
OpenAlex·12 February 2026·João M. Lopes, Sofia Gomes, Elisabete Nogueira, João J. Ferreira, Marina Dabić·Behaviour and Information Technology, tier 2
A PLS survey of 422 Portuguese respondents extends TAM by adding promotion focus, positive reinterpretation, and technostress as antecedents of perceived usefulness and AI-use intention, with adaptable organisational culture as a moderator. The usefulness-driven pathway mostly restates what the library already holds, though the culture moderator is a new wrinkle worth flagging as a might.
Companies & AIjournal
OpenAlex·12 February 2026·Haiden Michael, Uhl Matthias·AI & Society, tier 2
A vignette experiment finds people judge AI-based resource allocation as morally less desirable than a friend, waiting list, lottery, or market, especially for nonessential goods, and links this to perceived opacity. It extends algorithm aversion into moral judgments about allocation but the direction and mechanism largely reconfirm what the trust library already catalogues.
Companies & AIjournal
OpenAlex·12 February 2026·Hans Westerbeek·AI & Society, tier 2
An Open Forum philosophical essay argues AI is shifting cognition from effortful to machine-guided across generations, drawing on Rousseau, Heidegger, and Postman, with no primary data collected. It is credible academic opinion rather than an empirical finding, so it lands at might rather than a must-read.
Companies & AIjournal
OpenAlex·10 February 2026·Dominic Chalmers, Richard ‘Rick’ Hunt, Stella Pachidi, Kristina Potočnik, David M. Townsend·Journal of Management Studies, tier 1
A peer reviewed conceptual framework proposing that predictive, generative, agentic and embodied AI need separate theorising, with a research agenda attached. No primary data or effect size is offered, so despite the tier 1 venue and 2026 date it counts as credible opinion rather than evidence that changes a number or mechanism.
Women & AIjournal
OpenAlex·10 February 2026·Franziska Baier-Mosch, Lukas Schulze-Vorberg, Jürgen Schneider·Technology Knowledge and Learning, tier 3
Cross sectional survey of 177 teachers finds older and female teachers report less positive affect and lower AI content knowledge, which matches what the library already holds about women's lower AI self efficacy and cooler attitudes. Tier 3 venue and no causal design keep it capped even if the confirmation were new.
Companies & AIjournal
OpenAlex·9 February 2026·Mohammadreza Farrokhnia, Saeed Latifi, Pantelis M. Papadopoulos, Loes Hogenkamp, Hannie Gijlers, Hassan Khosravi, Omid Noroozi·International Journal of Educational Technology in Higher Education, tier 3
A randomized three group experiment, the causal design that lets a tier 3 venue count, finds chain of thought GenAI feedback rated higher quality than teacher feedback yet produced no greater revision gains, while GenAI feedback quality tracked students' initial essay quality and teacher feedback did not. The design is strong, but the population is graduate students revising essays rather than a professional or organisational AI adoption setting, so the thematic fit is thin enough to keep it at might.
Companies & AIjournal
OpenAlex·8 February 2026·Ali Derakhshan, Yujong Park·Journal of Education for Students Placed at Risk (JESPAR), tier 3
A quasi experimental design with control and experimental groups over a year finds an AI powered course raised psychological needs satisfaction among Iranian under resourced EFL students, with the strongest effect in the adoption phase. The causal design would normally lift a tier 3 venue, but the claim is framed specifically about this under resourced population's needs rather than a general mechanism, and the fit to organisational AI adoption themes is loose, so it lands at might.
Companies & AIjournal
OpenAlex·6 February 2026·Simeon Allmendinger, Lukas Bonenberger, Kathrin Endres, Dominik Fetzer, Henner Gimpel, Niklas Kühl·Electronic Markets, tier 2
A structured five-component conceptual framework for multi-agent AI in knowledge work, from a solid tier 2 venue, directly relevant to organizational AI adoption and useful for orienting future work, but it is a synthesis with no primary data or number, so it is credible opinion rather than a must-read.
Companies & AIjournal
OpenAlex·6 February 2026·Andrés Rodríguez-Pose, Zhuoying You·Spatial Economic Analysis, tier 2
Panel study of 270 Chinese cities with IV-2SLS finds AI and robotics raise technological innovation and the returns to science and technology spending, especially in cities at or below the technology frontier, a real mechanism and number. But the claim is framed around Chinese cities specifically rather than a portable organizational-adoption mechanism, so the geography rule keeps it at might-read.
Companies & AIjournal
OpenAlex·5 February 2026·Gerit Wagner, Julian Prester, Reza Mousavi, Roman Lukyanenko, Guy Pare·Journal of Information Technology, tier 1
A tier 1 perspective paper offering prompts and strategies for using GenAI in literature reviews. It is credible-author opinion with no primary data, so per the rubric it caps at might, and its fit to her core themes of organizational adoption is only tangential.
Companies & AIjournal
OpenAlex·5 February 2026·Frida Milella, Federico Cabitza·Machine Learning and Knowledge Extraction, tier 3
A tier 3 survey (n=610) finding trust in automation and perceived performance drive deference to AI authority, with moral attitudes moderating high-stakes deference. This confirms what the library already holds on trust as the dominant driver of algorithmic deference, and there is no causal design to trigger the tier 3 exception.
Women & AIjournal
OpenAlex·4 February 2026·Sedef Çelik, Metin Besalti, Ümit Kul·Frontiers in Psychology, tier 3
A tier 3 psychometric validation of a Turkish AI self-efficacy scale on pre-service teachers, finding gender invariance and that self-efficacy mediates the anxiety-to-acceptance link. This confirms an already well-established mechanism in the library's self-efficacy and anxiety sections; it is locally framed and carries no causal design, so it stays at might.
Companies & AIjournal
OpenAlex·4 February 2026·Amani Marcelin Kalimira, Kian Jazayeri·Sustainability, tier 3
A tier 3 PLS-SEM study of 965 university students finding social drivers (FOMO, word-of-mouth, norms) act on AI usage through trust, while dependency tracks perceived competence and intelligence rather than usage itself. This adds a usage-versus-dependency distinction but mainly reconfirms trust as the central driver already documented in the library, and no causal design lifts it past the tier 3 cap.
Companies & AIjournal
OpenAlex·3 February 2026·Michael Chan, Jörg Matthes, Ljubiša Bojić·Online Media and Global Communication, tier 2
A four country survey of 2,144 young adults finds perceived usefulness and attitude mediate the effect of social media valence on generative AI use intention everywhere, but the direct valence effect only holds in Indonesia and Hong Kong, not Austria or Serbia. This is a cultural boundary condition on a TAM pathway the library already holds extensively, so it confirms more than it changes.
Companies & AIjournal
OpenAlex·2 February 2026·Thomas A. Hanson, Caleb Ott·Journal of risk and financial management, tier 3
In a survey of 117 college students, trust in AI was the only significant predictor of fintech trust, uncorrelated with any literacy measure. This reinforces the library's existing finding that trust dominates performance and literacy factors in AI reliance, so it is credible but confirmatory, and the small student sample and tier 3 venue limit it further.
Companies & AIjournal
OpenAlex·1 February 2026·Heejeong Yoon, Jungwan Lee, Namhwa Kim, Siwoo Ban, Hyeri Shin, Yong Wook Kim·Digital Health, tier 3
Latent profile analysis of 336 Korean care workers over 50 finds four technostress profiles, with the high-complexity, low-inclusion group showing the worst self-efficacy, usefulness and intention scores. This confirms the library's existing technostress-acceptance link rather than adding a new mechanism, and the venue is tier 3 with no causal design, so it cannot be a must-read despite the specific profile finding.
Companies & AIjournal
OpenAlex·1 February 2026·Elena Botezat, Alexandru Constăngioară, Olimpia Ban, Diana Claudia Sabău-Popa, Diana Claudia Perțicaș, Veronika Fenyves·Amfiteatru Economic, tier 2
A PLS-SEM survey of Romanian firms finds AI and sustainable digitalisation strengthen supply chain resilience mainly through competitive advantage. The finding is framed around Romanian companies specifically, a local population rather than a general mechanism, which drops it a level, and the TOE-diffusion mechanism it tests is already well covered by the classics in the library.
Women & AIjournal
OpenAlex·31 January 2026·Kathryn Wheeler·Qualitative Research in Psychology, tier 2 by default, this venue is not on the tier list yet
A reflexive account by a female qualitative researcher of how MAXQDA, NVivo and ChatGPT shaped her analysis of a large youth climate survey. It is a genuine single-researcher account of putting AI to work, but it is a reflexive methodological essay rather than a test of a mechanism, so it stays at credible-account level rather than must-read.
Companies & AIbusiness
Deloitte Insights·21 January 2026·tier 2
Deloitte's flagship 3,235-leader survey adds granular numbers, worker access up 50%, only 34% truly reimagining the business, agentic governance maturity at one in five, but the headline claim that adoption outpaces transformation is already thoroughly documented in the library.
Companies & AIbusiness
Harvard Business Review·tier 1
Argues AI adoption stalls because industry-shaped anxiety about identity, relevance and job security drives surface use without real commitment, which closely restates the library's existing findings on professional identity threat predicting resistance to AI.
Companies & AIbusiness
Harvard Business Review·tier 1
A credible-author argument that AI-era competitive advantage depends on recombination capability across modular firms, but the opening offers no data or study design, only a framework and four managerial prescriptions.
Companies & AIbusiness
Harvard Business Review·tier 1
HBS case study on Microsoft's Copilot rollout gives usage numbers, 60% daily and 98% monthly active use after two years, but the mechanism, top down mandate fails, training and peer champions work, largely echoes the library's existing automation versus augmentation and six stage adoption findings rather than adding a new one.
Companies & AIbusiness
Harvard Business Review·tier 1
A five profile typology for how middle managers respond to AI is presented with no disclosed method or sample in the opening, making it credible opinion rather than a tested finding, similar to the persona typologies the library already flags as unvalidated marketing frameworks.
Companies & AIbusiness
Harvard Business Review·tier 1
A proprietary executive benchmark survey, but the opening reports only vague quantifiers, virtually every leader, vast majority, with no hard percentage, and it restates the already-held optimism-versus-readiness gap the library documents with sharper numbers, 88% adoption versus 6% high performers.
Companies & AIbusiness
Harvard Business Review·tier 1
Describes a study of three MBA-recruiting sectors identifying three future-relevant capabilities, but the opening gives no sample size, method or quantified result, leaving it as a plausible framework rather than a number or mechanism she could cite.
Companies & AIbusiness
Harvard Business Review·tier 1
A reflective essay by a long-time hiring researcher on how AI has degraded parts of recruiting, credible opinion but no study, sample or number given in the opening.
Companies & AIbusiness
Harvard Business Review·tier 1
Third edition of an ongoing usage study, but the opening only cites generic market facts, ChatGPT's 900 million users, Gemini's 750 million, rather than the study's own quantified findings, and the described trend, widening but marginal AI use, mostly confirms what the library already holds.
Companies & AIbusiness
Harvard Business Review·tier 1
Based on 18 interviews at two consulting firms, this identifies middle managers as overloaded by validation and coaching duties under unchanged delivery pressure, a real but small and narrowly sourced qualitative finding that extends rather than overturns the library's existing identity-threat and resistance mechanisms.
Companies & AIbusiness
Harvard Business Review·tier 1
Interviews and focus groups with 35 executives surface contested definitions of AI value and emotionally divided leadership responses, a reasonable qualitative finding but without a number or a clearly new mechanism beyond what the library's identity-threat and resistance literature already covers.
Companies & AIbusiness
Harvard Business Review·tier 1
Describes AI intensifying work through faster pace, broader task scope and longer hours, but gives no sample size, method or effect size, only descriptive claims. The mechanism largely restates what the library already holds on technostress and burnout, so it confirms rather than changes her view.
Companies & AIbusiness
Harvard Business Review·tier 1
A multi-year field study across banking, recruitment and biotech finds employees mask, amplify or complement AI outputs rather than relaying them verbatim, shaping trust and risk. This extends but largely echoes the library's existing findings on covert workarounds and quiet resistance to AI-driven decisions.
Companies & AIbusiness
BCG·tier 2
BCG's AI Radar survey of 2,400 executives reports CEO AI ownership nearly doubling and spending rising from 0.8% to 1.7% of revenue, with persistent concerns about control and privacy. This is credible large-scale data but mostly confirms the already well-documented trend of rising executive AI investment rather than adding a new adoption mechanism.
Women & AIbusiness
BCG·tier 2
A 2019 opinion piece citing the IMF's projection that 11% of women's jobs are at risk from automation, illustrated with finance-sector concentration data; it is secondary-sourced analysis rather than primary research and long predates the current adoption-gap evidence the library already holds.
Women & AIbusiness
BCG·tier 2
BCG's own global survey of 6,500 tech employees finds senior women outadopt men on GenAI by 14 points while junior women lag, a seniority-interaction not captured in the library's overall adoption-gap picture. The report is from May 2024, though, outside the twelve-month window for business pieces, so it stays a might rather than a must.
Companies & AIbusiness
BCG·tier 2
Draws on the same fourth annual AI at Work survey as its sibling BCG piece and adds a 'joy paradox' (satisfaction up 67%, cognitive load up 41% simultaneously) plus a Global-South-leads-adoption pattern. Since it is the same underlying dataset already credited elsewhere, it mostly restates rather than supplies an independent primary source.
Companies & AIbusiness
BCG·tier 2
BCG's 2025 AI at Work survey of 10,600 people documents a 'silicon ceiling', frontline regular use stalled at 51% against leaders' much higher rate, and shows firms that 'Reshape' workflows outperform those that just 'Deploy'. Solid primary data, but published mid-2025, right at or past the twelve-month recency cutoff, so it stays a might.
Companies & AIbusiness
BCG·tier 2
BCG's microeconomic model projects 50 to 55% of US jobs reshaped within two to three years and 10 to 15% eliminated within five, a specific number, but it rests on internal task-automation modeling rather than measured survey or behavioural data, so it falls short of the primary-evidence bar.
Companies & AIbusiness
BCG·tier 2
BCG's 2024 survey of 13,102 employees documents rising confidence and rising job-loss fear moving together, and shows AI training concentrated on leaders (50%) versus frontline workers (28%). Solid primary data, but the report is from 2024, outside the recency window for a business piece.
Companies & AIbusiness
BCG·tier 2
BCG's 2023 survey of nearly 13,000 employees across 18 countries documents a leader-frontline gap in both training (44% vs 14%) and confidence in the company's AI program (68% vs 29%), alongside rising optimism overall. Solid primary data, but from 2023 and superseded by the newer waves already noted in the practitioner shelf, so it is outside the recency window.
Companies & AIbusiness
Deloitte Insights·tier 2
The summary describes a genuinely new mechanism, AI automating entry-level tasks and firms hiring fewer juniors, but the fetched opening only delivers author bios and stops before any number or dataset is shown, so it cannot be verified as primary evidence.
Companies & AIbusiness
Deloitte Insights·tier 2
This is Deloitte's own large State of AI in the Enterprise survey, a proprietary dataset in the same class the rubric allows, but the fetched opening only lists seven headline themes with no numbers or mechanism to weigh.
Women & AIbusiness
Deloitte Insights·tier 2
A 25,000-respondent UK workforce survey finds men are more likely than women to use GenAI multiple times a day (15% vs 9%), which is real primary data, but it confirms the adoption-gap pattern the library already holds in several forms rather than adding a new mechanism.
Companies & AIbusiness
IBM·tier 2
IBM's own Think Circle and CEO study figures (29% measure ROI confidently, 25% deliver expected ROI, 16% scaled enterprise-wide) are primary survey data, but they land in the same range and tell the same story the library already holds: most AI initiatives stall on organizational rather than technical grounds.
Companies & AIbusiness
IBM·tier 2
An IBM-sponsored survey reports 80% of office workers use AI but only 22% rely solely on employer tools, with Gen Z far more likely to go outside sanctioned tools. This closely tracks the library's existing finding that 57% of employees hide their AI use, so it refines rather than changes the picture.
Companies & AIbusiness
Accenture·tier 2
Proprietary survey of 2,000 companies across 15 countries finds only 7% have reached the data readiness required to scale advanced AI. This is a large proprietary dataset and a specific number, but it restates the library's well established pattern that few firms convert AI investment into real capability or value, just through a data readiness lens rather than a new mechanism.
Companies & AIbusiness
Accenture·tier 2
Accenture survey reports specific multiples, reinvention ready firms show 2.5x revenue growth and 16% versus 9% year over year reaching full AI led processes. The piece is over a year old, which rules out a must read on recency, and its core claim that maturity separates winners from laggards duplicates what the library already holds many times over.
Companies & AIbusiness
Accenture·tier 2
Accenture's AI Progress Barometer tracks roughly 3,000 companies and finds Europe's largest firms narrowing the AI readiness gap with North America while smaller European firms lag by 7.6 points, a new number not yet in the library. But the finding is framed explicitly around Europe versus North America and large versus small firms, a population claim rather than a mechanism, so the geography rule drops it a level from what would otherwise be a must read.
Companies & AIbusiness
Accenture·tier 2
The fetched opening gives real numbers, 95% of workers see value in gen AI, two-thirds of C-suite feel ill-equipped, three-quarters of Reinventors involve workers in redesign, and top-quartile Reinventors are twice as likely to expect 20%+ productivity gains. But it is Accenture's own branded survey and it mainly restates the leader-worker trust gap and readiness themes the library already holds, so it confirms rather than changes the picture.
Companies & AIbusiness
Accenture·tier 2
This press release version of the same Accenture report adds a specific perception-gap number: almost 60% of workers worry about AI eliminating their jobs versus fewer than a third of C-suite leaders sharing that worry. It is vendor-funded and duplicates the leadership-blind-spot pattern already in the library, so it is a might, not a must-read.
Companies & AIbusiness
Accenture·tier 2
The opening reports Accenture's Pulse of Change Index: business change up 183% in four years, 9% of firms now 'Reinventors,' that share quadrupling among the largest companies, with software and life sciences posting double-digit gains. It is a large proprietary dataset, but the branded Reinventor/Transformer/Optimizer typology and the finding that a few large firms pull ahead while most lag mirrors patterns the library already documents (88% use AI but 6% are high performers; gains concentrate in the biggest firms), so it is a might rather than a must-read.
Would not read402
Companies & AIbusiness
McKinsey·18 September 2026·tier 2
The page could not be fetched, so only the title and a one-line teaser about redesigning workflow handoffs for agentic AI are available. No number or mechanism is present to weigh, and a title alone cannot carry a must-read.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIbusiness
McKinsey·17 September 2026·tier 2
Opening unavailable, leaving only a title claiming Europe is positioned for an AI application layer. No data or mechanism is shown, so there is nothing here beyond a headline claim.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIbusiness
McKinsey·16 September 2026·tier 2
Fetch failed, so only the title about a leaner transformation office survives. No evidence of a number, sample, or mechanism, just a promotional headline.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIbusiness
McKinsey·15 September 2026·tier 2
This is a podcast teaser with McAfee, a credible commentator, but the opening could not be fetched so there is no argument or data to assess, only a rhetorical title question.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIjournal
OpenAlex·15 September 2026·Guangji Bai, Zheng Chai, Ling Chen, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu·ACM Computing Surveys, tier 3
A technical literature survey on resource-efficient large language model architectures, with no primary data and no bearing on organisational adoption, women, or AI in the workplace.
Companies & AIbusiness
McKinsey·14 September 2026·tier 2
Title-only McKinsey piece on scaling agentic AI; the actual content, including any figures on rollout success, is inaccessible, leaving a headline with no mechanism to evaluate.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIjournal
OpenAlex·14 September 2026·Junchao Chen, Tinghong Huang·Discover Computing, tier 3
A conceptual paper proposing a theoretical model of AI-assisted sustainable behaviour with testable propositions but no empirical data at all, only a proposed three-stage research programme.
Companies & AIbusiness
McKinsey·11 September 2026·tier 2
Fetch failed; only a title and one-line claim about attacker speed outpacing committee-speed decisions remain, with no data on the actual security gap or its size.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIbusiness
McKinsey·10 September 2026·tier 2
Title-only piece describing AI's economy-wide feedback loops. No opening content survived retrieval, so there is no number or mechanism, just a broad framing claim.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIbusiness
McKinsey·9 September 2026·tier 2
Opening could not be fetched; only a title claiming operating-model design, not a single best model, drives AI transformation success. No figures or design details are available to evaluate the claim.
Open the article →Judged on the title alone: the page did not answer: The operation timed out.
Companies & AIbusiness
MIT Sloan Management Review·9 September 2026·Khaled Soufani and Samsurin Welch·tier 1
A qualitative case analysis of Ørsted and Microsoft arguing reinvention should build on existing 'kernels' rather than starting over. It is opinion built on illustrative cases, not an AI-adoption study, so it sits outside her core themes and offers no adoption mechanism or number.
Companies & AIjournal
OpenAlex·9 September 2026·Noam Angrist, Micheal Ainomugisha, Sai Pramod Bathena, Peter Bergman, Colin Crossley, Claire Cullen, Thato Letsomo, Moitshepi Matsheng·Nature, tier 1
Five randomised trials show phone-call tutoring is highly cost-effective for education resilience during emergencies, but this is about mobile tutoring delivery, not AI, companies, or women and AI, so it does not fit either theme despite the tier 1 venue and rigorous design.
Companies & AIjournal
OpenAlex·9 September 2026·Wes Brewer, Ana Gainaru, Frédéric Suter, Feiyi Wang, Murali Emani, Shantenu Jha·ACM Computing Surveys, tier 3
A technical survey of AI-coupled high-performance-computing workflows and execution motifs, with no data on organisational adoption, women, or workplace use, and no primary evidence.
Companies & AIjournal
OpenAlex·5 September 2026·Steffen Eger, Cao Yong, Jennifer D’Souza, Andreas Geiger, Christian Greisinger, Stephanie Groß, Yufang Hou, Brigitte Krenn·ACM Computing Surveys, tier 3
A literature survey cataloguing AI tools across the scientific research lifecycle, with no primary data and no findings about adoption mechanisms, companies, or gender.
Women & AIjournal
OpenAlex·28 August 2026·Mateusz Paliga, Agnieszka Skorupa, Ari Nowacki, Dariusz Niedbała, Agnieszka Szczotka, Leszek Orzechowski, Agata Mintus·Scientific Reports, tier 3
A correlational multilevel study of personal values, technostress and affective well-being among nine analog astronauts during a simulated space mission. The sample is tiny, the population is a highly specific extreme-environment crew, and the design is correlational rather than one of the named causal designs, so the tier 3 venue cannot carry it.
Companies & AIjournal
OpenAlex·22 August 2026·Vanshika Vats, Marzia Binta Nizam, Minghao Liu, Ziyuan Wang, Richard C. Ho, Mohnish Sai Prasad, Vincent Titterton, Sai Venkat Malreddy·ACM Transactions on Intelligent Systems and Technology, tier 3
A literature survey on human-AI collaboration with foundation models, offering no primary data and only a general call for human-centred design.
Companies & AIbusiness
MIT Sloan Management Review·18 August 2026·Lauren Aydinliyim and Deepak Somaya·tier 1
This is a retention-strategy framework illustrated by the OpenAI pay war, not a study of AI adoption in organisations. The AI angle is a hook, not the finding, so it does not fit her themes.
Companies & AIjournal
OpenAlex·18 August 2026·Ogan Yigitbasioglu·Journal of the Association for Information Systems, tier 1
An Australian survey tests a transaction-cost model of cloud computing adoption, finding vendor opportunism and legislative uncertainty predict perceived security risk which reduces adoption intention. This is about cloud computing, not AI, so it falls outside her themes despite the tier 1 venue.
Companies & AIjournal
OpenAlex·11 August 2026·Fuseini Mumuni, Alhassan Mumuni·Array, tier 3
A comprehensive survey of explainable AI methods from inherently interpretable models to LLM-based explanation, with no primary data and no findings about organisational adoption or gender.
Companies & AIjournal
OpenAlex·10 August 2026·Kabirat Motunrayo Ogundairo, Steve Senyo Ayivi-Donkor·INTERNATIONAL JOURNAL OF MARKETING AND COMMUNICATION STUDIES, tier 3
A conceptual paper proposing that supply chain AI adoption failures stem from missing product-marketing framing, with no empirical data, only a four-move argument and an agenda for future empirical work.
Companies & AIjournal
OpenAlex·1 August 2026·Karen Manley·Journal of the Association for Information Systems, tier 1
A general overview of systems approaches to innovation for policymakers, with no AI content and no primary data, essentially a conceptual synthesis that duplicates ground the library's adoption classics already cover.
Companies & AIjournal
OpenAlex·28 July 2026·Sixbert Sangwa, Dennis NGOBI, Emmanuel Ekosse, Placide Mutabazi
A desk-based meta-synthesis of policy documents with no primary data collection, offering a proposed governance framework rather than evidence of a mechanism or number.
Companies & AIjournal
OpenAlex·22 July 2026·Jeanette Van Akkeren, Angèle Cavaye·Journal of the Association for Information Systems, tier 1
A literature review proposing a composite SME technology-adoption model, not AI-specific, with no primary data collected, largely reprising ground the library's adoption-classics section already holds.
Companies & AIjournal
OpenAlex·17 July 2026·Jasper Roe, Mike Perkins·Academia AI and Applications, tier 3
A thematic literature review on generative AI and learner agency in education with no primary data, and its tier 3 venue cannot carry a must-read without a causal design, which this lacks.
Women & AIjournal
OpenAlex·16 July 2026·Wenwen Xu, Xiangdong Li, Yuanhao Sun, Yangyang Pan, Lin Zhang, Hao Wen, Ting Yuan, Hairong Liu·Scientific Reports, tier 3
A cross-sectional hospital survey of Chinese older adults links technophobia to depressive symptoms, but the design is correlational, the venue is tier 3 without a qualifying causal design, and the population is a specific Anhui hospital sample rather than a general mechanism claim.
Companies & AIjournal
OpenAlex·13 July 2026·Ming Li, Qin Xie, Ariunaa Enkhtur, Shuoyang Meng, Lilan Chen, Beverley Anne Yamamoto, Fei Cheng, Masayuki Murakami·Studies in Higher Education, tier 3
A qualitative cross-national comparison of university AI governance documents with no primary behavioral data, proposing a policy framework rather than testing a mechanism, and its tier 3 venue has no qualifying causal design.
Companies & AIjournal
OpenAlex·8 July 2026·Chahat Harish Rajusth, Jugindar Singh Kartar Singh, Nor Nazeranah Omar Din, Noraini Binti Ahmad·International Journal of Human Resource Studies, tier 3
A cross-sectional PLS survey of 184 Mumbai remote workers finds only two of five technostress dimensions affect exhaustion and technophobia fails to moderate anything, a local-population, non-causal finding in a tier 3 venue.
Companies & AIjournal
OpenAlex·4 July 2026·Bhuvan Chandra Kasarapu·International Journal of Computer Information Systems and Industrial Management Applications, tier 3
A vendor-style description of a generative AI micro-frontend architecture for retail with vague claims of experimental superiority and no reportable data or method, a tool round-up rather than evidence.
Companies & AIjournal
OpenAlex·3 July 2026·Yiheng Zhu, Zitai Kong, Jialu Wu, Mingze Yin, Weize Liu, Yuqiang Han, Hongxia Xu, Chang‐Yu Hsieh·npj Drug Discovery., tier 3
A technical survey of generative AI methods for protein sequence design, entirely outside her themes of organizational adoption or women and AI.
Companies & AIjournal
OpenAlex·1 July 2026·Joseph P. Gaspar, Maurice E. Schweitzer, Redona Methasani·Journal of Business Ethics, tier 2
A purely theoretical model of moral advice seeking and taking with no empirical data and no connection to AI adoption or gender and AI, it does not fit her themes despite the credible venue.
Companies & AIjournal
OpenAlex·30 June 2026·Xinyue Li, Zhenpeng Chen, Jie M. Zhang, Ying Xiao, Tianlin Li, Weisong Sun, Yang Liu, Yiling Lou·Proceedings of the ACM on software engineering., tier 3
Large-scale bias audit of ten LLMs in role-playing finds over 100,000 biased responses across demographic attributes, but it is a software-engineering fairness benchmark with no link to organisational adoption or gender-and-AI mechanisms, and the venue is tier 3 with no causal design.
Companies & AIjournal
OpenAlex·30 June 2026·Jorge García Hombrados, Marcel Jansen, Ángel Martínez, Berkay Özcan, Pedro Rey‐Biel, Antonio Roldán-Monés·American Economic Review, tier 1
A well-designed country-wide RCT in a top journal showing ideological alignment of the messenger drives a 65% jump in policymaker adoption of evidence-based policy, but the population is policymakers adopting public policy, not companies adopting AI or women and AI, so it sits outside her themes regardless of its rigour.
Companies & AIjournal
OpenAlex·28 June 2026·Isaac Koomson, Simplice A. Asongu, Esther Laryea·Journal of Global Information Technology Management, tier 2
Multilevel regression on 33,194 individuals across 34 African countries finds mobile phones, governance quality, and digital interoperability platforms jointly promote financial inclusion, but this is about financial inclusion infrastructure, not AI, and carries no gender-specific finding despite the tier 2 venue.
Companies & AIjournal
OpenAlex·28 June 2026·Ahmad Nabriz, Ahmad Faizal Syahrul Azmi, Abubaker Kashada, Rahmat Ullah, Ajoy Chandra·Al Husna Jurnal Ilmiah Pendidikan Agama Islam, tier 3
A qualitative literature synthesis proposing an Islamic Digital Citizenship Framework, with no primary data and no AI-adoption or gender-and-AI content, and a tier 3 venue.
Women & AIjournal
OpenAlex·26 June 2026·Claudia Fornari, Daria Ricci, Yoni Couderc, Carmen Guerrero-Márquez, Praneeth Namburi, Camille Penet, Céline Nicolas, Anna Beyeler·Molecular Psychiatry, tier 3
A mouse neuroscience study on sex differences in insular-cortex circuits driving persistent alcohol drinking, with no connection to AI, companies, or technology adoption; included only because sex difference is the nearest thematic anchor.
Companies & AIjournal
OpenAlex·25 June 2026·Alfio Ventura, Christopher Starke, Francesca Righetti, Nils Köbis·Computers in Human Behavior Reports, tier 2
A narrative review proposing a research agenda on AI companions and loneliness, with no primary data of its own and only theoretical claims about risks and benefits, so it is opinion-grade evidence that does not meet the primary-evidence bar.
Women & AIjournal
OpenAlex·18 June 2026·Kilda Gusha, Marsida Tafilica·UniVlora Scientific Journal, tier 3
A 100-person Albanian survey linking egalitarian gender-role attitudes to relationship satisfaction, with no AI or technology content at all and a tier 3, locally framed sample.
Companies & AIbusiness
IBM·12 June 2026·tier 2
No primary survey data is presented, only a Gartner prediction and a podcast quote strung into a generic thought-leadership narrative about 2026 adoption challenges.
Women & AIjournal
OpenAlex·12 June 2026·Şeyma Yıldırım-Samuk, İsmail Fırat Altay·Contemporary Educational Technology, tier 3
A 145-student UTAUT2 survey finds habit and performance expectancy drive generative-AI acceptance among graduate students, with gender showing no moderating effect. This only restates predictors already well documented in the acceptance-model literature the library holds, from a tier 3, single-country student sample with no causal design.
Women & AIjournal
OpenAlex·12 June 2026·Mesbah Fathy Sharaf, Abdelhalem Mahmoud Shahen·Journal of risk and financial management, tier 3
Logit and decomposition models on Brazilian Global Findex microdata find the digital-finance gender gap concentrates among the unemployed and unconnected and vanishes among employed, connected individuals. The finding is framed around a specific national population and the venue is tier 3 with no causal design, and the topic is digital finance rather than AI.
Companies & AIjournal
OpenAlex·11 June 2026·Sasichakorn Wongsaichia, Teerapong Pienwisetkaew, Chavis Ketkaew·PLoS ONE, tier 3
A 602-respondent Thai consumer survey on collaborative innovation and sustainable-fashion adoption has no AI content and no gender focus, and sits in a tier 3 venue with a locally framed sample.
Companies & AIjournal
OpenAlex·8 June 2026·Tarek Ali, Panos Kostakos, Saeid Sheikhi·Telecom, tier 3
HuntGPT is a technical demonstration of an LLM-augmented intrusion-detection dashboard evaluated on exam accuracy and readability metrics. It has nothing to do with organizational AI adoption, trust, or women and AI, and sits in a tier 3 venue with no relevant primary evidence for her themes.
Women & AIjournal
OpenAlex·5 June 2026·Ayesha Wazir·UCP Journal of Humanities & Social Sciences, tier 3
A feminist ethnography of tribal patriarchal practices in South Waziristan mentions in passing that young women use technology to resist tradition, but this is not a study of AI adoption or technology use in any substantive sense. Tier 3 venue, no relevant primary evidence.
Companies & AIjournal
OpenAlex·3 June 2026·Kristel Marmor, Janika Leoste, Mati Heidmets·Frontiers in Robotics and AI, tier 3
A small Estonian pilot on guide-robot acceptance finds age and gender differences in self-efficacy were not statistically significant and flags its own group comparisons as non-random and exploratory. The authors call the results hypothesis-generating, and the tier 3 venue has no causal design to invoke the exception.
Companies & AIjournal
OpenAlex·3 June 2026·Frederik Simon, Sebastian Weibels, Tom Zimmermann·Management Science, tier 1
This is a finance-methodology paper on neural-network portfolio optimization and certainty-equivalent returns, not a study of organizational AI adoption, employee experience, or women and AI. It does not fit her themes despite the tier 1 venue.
Women & AIjournal
OpenAlex·1 June 2026·Jiajun Yin, Fang Fang, Zhaoguo Liu, Yingying Ji, Li Guo, Xiaoyan He, Xia Sun·Current Psychology, tier 2
A network analysis of sleep, depression and anxiety among Chinese vocational students, with a gendered comparison, contains no mention of AI or technology adoption at all and does not fit either of her themes.
Companies & AIjournal
OpenAlex·1 June 2026·Hui-Yuan Liao, Chih-Hung Ko, Cheng-Fang Yen·Biomedical Journal, tier 3
A narrative review of problematic ChatGPT use across several countries synthesizes prevalence and proposed mechanisms like compensatory internet use, but it is a review rather than primary data, sits in a tier 3 venue, and has no causal design to justify an exception.
Companies & AIjournal
OpenAlex·31 May 2026·Kayode Sunday John Dada, Romoke Opeyemi Quadir, Diana Mallam·Informatio Journal of Library and Information Science, tier 3
A descriptive survey of 245 Nigerian library professionals finds AI catalogue and chatbot tools are the most-adopted practices, limited by infrastructure and digital literacy. The finding is framed around a specific national population, the venue is tier 3, and the design is not causal, so the geography rule and venue rule both work against it.
Women & AIjournal
OpenAlex·28 May 2026·Farhod Ahrorov, Azamat Saydullaev, Abduvakil Alimov, Beknazar Sultonov, Akida Abdurakhmanova·Frontiers in Human Dynamics, tier 3
A mixed-methods survey of 883 rural Uzbek women finds financial literacy is the strongest predictor of moving from smartphone access to income-relevant platform participation. The claim is framed around this specific local population, the venue is tier 3, and the design is not causal, so it drops rather than earning a must-read.
Companies & AIjournal
OpenAlex·28 May 2026·Christian J. Wiedermann, Giuliano Piccoliori, Doris Hager von Strobele Prainsack, Dietmar Ausserhofer·Medical Sciences, tier 3
A scoping review of 35 studies on AI attitudes among Italian healthcare professionals and patients reports a recurrent 'optimism-knowledge gap.' It is a secondary synthesis in a tier 3 venue with no causal design, and the finding is framed around the Italian healthcare population rather than a general mechanism.
Companies & AIjournal
OpenAlex·27 May 2026·Nathan Gabriel Wood, Scott Robbins, Eduardo Zegarra Berodt, Anton Graf von Westerholt, Michelle Behrndt, Hauke Budig, Daniel Schreiber·Philosophy & Technology, tier 2
A conceptual, philosophical argument that debates should stop using the umbrella term 'AI' and instead specify discrete systems, illustrated through a taxonomy of military AI. It presents no primary data and is not about organizational adoption or women and AI.
Women & AIjournal
OpenAlex·25 May 2026·Diah Pranitasari, Iman Sofian Suriawinata, Warcito Warcito·Frontiers in Human Dynamics, tier 3
A survey of 250 women-owned MSMEs in West Java finds an awareness-to-adoption gap in digital and financial inclusion and proposes a four-stage empowerment model. The claim is framed around this Indonesian population rather than a general mechanism, which drops a tier-3 piece further, and it mainly restates the access-versus-use gap the digital divide section already holds.
Women & AIjournal
OpenAlex·25 May 2026·Yangyang Fu, Deyong Lv, Rui Chen, Kaiyuan Feng, B Q Li, Qinling Li, Ziwei Qin, Shuyi Yan·Frontiers in Public Health, tier 3
A Chinese undergraduate sample of 1,151 finds social capital and eHealth literacy predict digital health literacy with slightly stronger paths for men, but the gender difference is explicitly not statistically significant. Tier 3, local population framing, and a null result on the one thing that would matter to her.
Companies & AIjournal
OpenAlex·23 May 2026·Anton Sokolov·Zenodo (CERN European Organization for Nuclear Research), tier 3
A Zenodo preprint mapping EU AI Act compliance onto eIDAS trust-service standards for procurement documentation. No primary data, not peer-reviewed, and it addresses regulatory engineering rather than how organisations or people adopt AI.
Companies & AIjournal
OpenAlex·22 May 2026·Chenchen Hao, Zeguo Wang, Ping Wang·Behavioral Sciences, tier 3
A UTAUT-based survey of 434 preschool teachers finds performance expectancy, social influence and tech-savviness predict GenAI intention while effort expectancy does not, explicitly flagged by the authors as exploratory due to methodological limitations. Tier 3, and it reproduces predictor patterns the UTAUT sections already hold in far more depth.
Companies & AIjournal
OpenAlex·21 May 2026·Fei Chen·International Journal of Asian Studies, tier 3
An interview study of Shanghai residents' self-organisation during the 2022 lockdown. It contains no AI content and does not engage her adoption or gender themes at all.
Companies & AIjournal
OpenAlex·19 May 2026·Arnab Majumdar, Dhritidipa Bagchi, Ioly Kotta-Loizou, Martin Buck·Journal of Hazardous Materials, tier 3
A review of antimicrobial-resistance surveillance technology that mentions machine learning and blockchain in passing. It is not about organisational AI adoption or gender and AI, and it is a synthesis review with no primary adoption data.
Companies & AIjournal
OpenAlex·15 May 2026·Jingyao Wang, Haoming Wang, Junwu Yang, Chengliang Wang·Humanities and Social Sciences Communications, tier 3
A UTAUT survey of 238 university teachers finds performance expectancy and attitude drive GenAI intention, with attitude fully mediating literacy's effect. Tier 3, and the mediation pattern is already established in the library's UTAUT and attitude-reinstatement records.
Companies & AIjournal
OpenAlex·15 May 2026·Md Shafiqur Rahman Jabin·Frontiers in Digital Health, tier 3
A conceptual, theory-building paper proposing four mechanisms of health-IT risk emergence and concealment, built from literature synthesis rather than a dataset. No primary evidence, and it addresses patient-safety theory rather than organisational AI adoption or gender.
Companies & AIjournal
OpenAlex·15 May 2026·Abeer F. Alkhwaldi, Cherie Noteboom, Amir A. Abdulmuhsin·Sustainability, tier 3
A survey of 489 Midwestern US farmers finds performance expectancy, effort expectancy and trust drive AI adoption intention while data-security concerns deter it. Tier 3, the finding is framed around this regional farming population rather than a general mechanism, and the predictors match the UTAUT and trust findings already in the library.
Companies & AIjournal
OpenAlex·15 May 2026·Müzeyyen Ataseven, Zeynep Ersoz, Beyza Kahvecı·International Emergency Nursing, tier 3
A cross-sectional survey of 250 Istanbul emergency-department staff finds AI anxiety correlates with occupational anxiety, strongest on a sociotechnical-blindness subscale. Tier 3, local sample, and it confirms the AI-anxiety-as-real-and-consequential finding the library already holds in more depth.
Women & AIjournal
OpenAlex·12 May 2026·Helena J Teede, Mahnaz Bahri Khomami, Rachel Morman, Joop S E Laven, Anju E. Joham, Michael Costello, Madhuri Patil, D Aled Rees·The Lancet, tier 3
A consensus process for renaming PCOS has no connection to AI adoption, companies, or the tech gender divide. Wrong subject entirely, forced into the closer domain only nominally.
Women & AIjournal
OpenAlex·11 May 2026·Abdelhalem Mahmoud Shahen, Mesbah Fathy Sharaf·Journal of risk and financial management, tier 3
Using 2025 Global Findex data, the gender gap in Nigerian digital financial inclusion mostly disappears once education, income and internet access are controlled for, with 79 to 94 percent explained by endowments. The finding is framed around Nigeria specifically and the venue is tier 3, so it drops below a confirmatory medium.
Companies & AIjournal
OpenAlex·11 May 2026·Kerem Öge, Manuel Quintin·JCMS Journal of Common Market Studies, tier 3
A discourse-network analysis of facial recognition framing in the EU and US traces a shift from security to ethics framing that shaped regulation. It is about policy discourse, not about companies adopting AI, women, or one person using AI, and the venue is tier 3.
Companies & AIjournal
OpenAlex·9 May 2026·Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Zican Dong, Yupeng Hou, Beichen Zhang, Yingqian Min·Frontiers of Computer Science, tier 3
A technical survey of LLM pre-training, fine-tuning, prompting and evaluation methods. No adoption data, no organizational or gender angle, and no primary empirical finding to weigh.
Companies & AIjournal
OpenAlex·9 May 2026·Igor Milojević, Dragana Rejman Petrović, Marina Milanovic, Bojan Leković, Marko Slavković·Information, tier 3
An ERP study of 123 Serbian managers finds top-management support moderates the effect of technological complexity on implementation success, largely reconfirming TOE-framework findings already in the library. Tier 3 venue and a Serbia-specific sample both work against it.
Companies & AIjournal
OpenAlex·7 May 2026·Alejandro Granados, Raghav Khanna, Nikola Fischer, Nicholas Raison, Margarita Ciabattini, Harry Robertshaw, Maxence Boels, Mohsan Malik·Frontiers in Science, tier 3
A forward-looking vision piece on future surgical AI and robotics teams, with no primary data behind its predictions about role shifts and ethical challenges. Tier 3 venue, no evidence to weigh.
Companies & AIjournal
OpenAlex·6 May 2026·Doaa Mohamed Salman, Mostafa Mohamed Awad, Cherine Soliman·Future Business Journal, tier 2
An SEM study of 406 Egyptians finds effort expectancy and generational membership are the strongest predictors of digital payment use, mostly reconfirming UTAUT2 constructs already in the library. The framing is explicitly about Egypt's fintech ecosystem, which drops it a level.
Companies & AIjournal
OpenAlex·2 May 2026·Fangfang Wu, Huanyu Huang, Zirui Zhan·Scientific Reports, tier 3
An SEM study linking external learning contexts to college students' resilience through self-efficacy and campus belonging. It contains no technology or AI content at all, so it does not engage her themes.
Companies & AIjournal
OpenAlex·2 May 2026·Ari Deller·Philosophy & Technology, tier 2
A philosophical argument that super-persuasive but not super-truthful AI will undermine warrant for beliefs formed through argument. It is opinion with no primary data and addresses epistemology rather than organizational adoption or gender, so it does not fit her themes closely enough.
Companies & AIjournal
OpenAlex·2 May 2026·Chenghao Wang, Bin Zou, Weilei Zhang, Yiran Du, Wei Hu·Humanities and Social Sciences Communications, tier 3
A 187-respondent TAM study of EFL teachers finds usefulness and ease of use drive ChatGPT adoption attitudes, with self-efficacy and facilitating conditions feeding ease of use. This reconfirms constructs already thoroughly documented in the library's TAM and UTAUT sections, and sits in a tier 3 venue.
Companies & AIjournal
OpenAlex·2 May 2026·Francis Khek Gee Lim·Religions, tier 3
A theoretical framework paper on AI and religious authority in Asian religious practice. It has no primary data, no causal design, and sits outside her themes of companies, women, or individual AI use in work contexts.
Women & AIjournal
OpenAlex·1 May 2026·WANG Dian, SHANG Li, Li Sun, LIU Haihui, WANG Kexin·DOAJ (DOAJ: Directory of Open Access Journals), tier 3
A Chinese-language translation and psychometric validation of an existing AI Anxiety Scale on 305 medical students. It only replicates an instrument the library already tracks in other languages and adds no new mechanism or number, and the population is locally framed.
Companies & AIjournal
OpenAlex·1 May 2026·SHING FUNG CHOI·British Research Review, tier 3
A 25-person qualitative interview study on employee reactions to the automation-augmentation paradox. Tier 3, no causal design, and its themes of identity friction and psychological safety as buffers duplicate what the library already holds in depth on AI identity threat and resistance.
Women & AIjournal
OpenAlex·30 April 2026·Özkan Özbay·Hacettepe University Journal of Education, tier 3
A correlational survey of 400 Turkish undergraduates linking AI literacy, attitudes, and technostress. Tier 3, locally framed population, and it only restates the already-established literacy-attitude-technostress links the library holds.
Women & AIjournal
OpenAlex·29 April 2026·Ali Altındağ, Sultan Uzun, Ömer Altındağ, Kaan Orhan·BMC Medical Education, tier 3
A cross-sectional survey of 501 Turkish dental students and dentists on AI knowledge and attitudes. Tier 3, locally framed population, descriptive only, adding nothing beyond existing attitude-survey findings in the library.
Companies & AIjournal
OpenAlex·29 April 2026·İlhan Celil Özbek, Erkan Özduran, Volkan Hancı·Medical Journal of Western Black Sea, tier 3
A narrative review of chatbot answer quality for pain-related medical questions. No primary data of her own, no adoption or organisational angle, outside her themes entirely.
Companies & AIjournal
OpenAlex·28 April 2026·Yueen Ma, Zixing Song, Yuzheng Zhuang, Jianye Hao, Irwin King·IEEE Transactions on Neural Networks and Learning Systems, tier 3
A technical survey of vision-language-action models for robotics. It is an engineering taxonomy with no bearing on organisational adoption, women and AI, or individual AI use.
Women & AIjournal
OpenAlex·27 April 2026·Eman Alnazly, Nadine Absy, Nader Absy·Frontiers in Psychiatry, tier 3
A cross-sectional survey of 312 nurses showing anxiety predicts negative AI attitudes (49.4% variance explained). Tier 3, no causal design, and it only reconfirms the anxiety-attitude link the library already documents extensively.
Companies & AIjournal
OpenAlex·24 April 2026·Yufei Guo, Muzhe Guo, Juntao Su, Zhou Yang, Mengqiu Zhu, Hongfei Li, Mengyang Qiu, Shuo Shuo Liu·Electronics, tier 3
A review of bias origins, evaluation, and mitigation in large language models. It is a technical survey with no primary data and no connection to organisational adoption or the women-and-AI theme.
Companies & AIjournal
OpenAlex·24 April 2026·August Keshav, Ashish Ranjan Sinha·Asian Journal of Interdisciplinary Research, tier 3
A UTAUT-extended survey of 415 Indian respondents on CBDC adoption intention. Tier 3, locally framed population, and it is an empirical adoption study of the generic UTAUT-survey type the rubric marks as not worth reading.
Companies & AIjournal
OpenAlex·24 April 2026·Mohhidin Othman, Tachaini KANDASAMY, Ainul Zakiah Abu Bakar, Bee‐Lia Chua·International Journal of Engineering & Technology, tier 3
A qualitative study of success factors at Mamak restaurants in Malaysia. It has no connection to AI, companies adopting AI, or women and AI whatsoever.
Women & AIjournal
OpenAlex·23 April 2026·Aneesh Rai, Erika Kirgios, Brian J. Lucas, Katherine L. Milkman·Journal of Applied Psychology, tier 1
A well-powered preregistered field and lab study finds doubling referral targets raises women referred by 17 to 88 percent through a goals mechanism, but it is about hiring referrals, not AI or technology adoption, so it fails her theme fit criterion entirely.
Companies & AIjournal
OpenAlex·23 April 2026·Lingxi Cui, Huan Li, Ke Chen, Lidan Shou, Gang Chen·ACM Computing Surveys, tier 3
A technical computing survey on generative AI for tabular data augmentation in machine learning pipelines, with no organizational, gender or individual-adoption content and no primary empirical finding about people or firms.
Women & AIjournal
OpenAlex·22 April 2026·Beáta Bőthe, Aurélie Michaud, Vanessa Beaulieu, Simon A. Houle, Léna Nagy, Mónika Koós, Shane W. Kraus, Marc N. Potenza·Journal of Behavioral Addictions, tier 3
A large multi-country structural model of pornography use and moral incongruence across genders and religions, methodologically strong but has nothing to do with technology adoption, AI or organizations.
Companies & AIjournal
OpenAlex·21 April 2026·Jameson Goto, Umesh Ramnarain·International Journal of Educational Technology in Higher Education, tier 3
A small (n=102) cross-sectional UTAUT study of Sub-Saharan African university students finds personal innovativeness and social influence predict AI use while most cultural dimensions do not. Tier 3 venue with no causal design, and the finding is framed around a specific student population rather than a general mechanism, so it drops further.
Companies & AIjournal
OpenAlex·20 April 2026·Mehmet Ertaş, Burçin Kırlar-Can, Demet Ceylan, Metin Kozak·Information Technology & Tourism, tier 3
A survey of 245 Antalya hotel employees finds all three technostress types raise emotional exhaustion, which then hurts performance via role ambiguity. This confirms what the library already holds on technostress's five faces and productivity effects, is framed around a specific local hospitality sample, and sits in a tier 3 venue with no causal design.
Companies & AIjournal
OpenAlex·20 April 2026·Chrysanthi Melanou, Maik Beege·Education Sciences, tier 3
A 175-student quasi-experiment on scaffolded GenAI tutoring found knowledge gains across all conditions but no significant difference between scaffolding levels, a null result for the manipulation of interest. Tier 3 venue, education context rather than her organizational or individual-use themes, and no clearly stated randomized or causal design to invoke the exception.
Companies & AIjournal
OpenAlex·16 April 2026·Ali Yari, Mohammad Taghi Taghavifard, Iman Raeesi Vanani·PLoS ONE, tier 3
A topic-modeling analysis of LinkedIn posts re-contextualizes UTAUT constructs for AI experts, but it is exploratory qualitative discourse analysis in a tier 3 venue with no causal design, and its findings mostly restate known UTAUT limitations rather than adding a mechanism or number.
Companies & AIjournal
OpenAlex·16 April 2026·Marwin E. Obmerga, Dennis G. Caballes·GiLE Journal of Skills Development, tier 3
A qualitative content analysis of 210 Reddit posts from science educators identifies three themes of AI-induced pedagogical technostress. It is scraped social-media commentary, not a validated primary dataset, in a tier 3 venue with no causal design, and adds no number or mechanism beyond existing technostress findings.
Companies & AIjournal
OpenAlex·16 April 2026·Hisham Noori Hussain Al-Hashimy, Jinfang Yao, Anwar Allah Pitchay, Zubir Azhar·Future Business Journal, tier 2
A 348-respondent PLS-SEM survey of Iraqi public-sector employees finds AI readiness and digital governance capability predict implementation effectiveness, which in turn drives public value. The finding is framed around a specific Iraqi public-sector population rather than a general mechanism, and the survey evidence is not large enough or causal enough to outweigh that demotion.
Companies & AIjournal
OpenAlex·16 April 2026·Hannes Schilling, Marie Ritter, Clara Kühner, Stephanie Hirschberger, Hannes Zacher, Simone Kauffeld·Industrial and Organizational Psychology, tier 2
A conceptual piece linking industrial-organizational psychology to circular economy implementation. It does not concern AI, technology adoption or gender at all, so it does not fit her themes.
Companies & AIjournal
OpenAlex·15 April 2026·Lingxi Fan, Lingsong Xiong, Weiqing Xiao, Andrew K. F. Cheung·The Interpreter and Translator Trainer, tier 3
An 89-student cross-regional study finds instructor feedback is rated clearer and more actionable than GenAI feedback in interpreter training, and general technology readiness does not predict acceptance of the AI feedback specifically. Tier 3 venue, narrow student population, and no clearly randomized causal design, so it cannot clear a must-read despite the interesting readiness-does-not-transfer nuance.
Companies & AIjournal
OpenAlex·14 April 2026·Xiting Wang, Liming Jiang, José Hernández‐Orallo, David Stillwell, Shiqiang Chen, Luning Sun, Fang Luo, Xing Xie·Communications of the ACM, tier 2
A methodological argument for applying psychometric theory to evaluate general-purpose AI systems' capabilities. It concerns measuring AI models themselves, not organizational adoption, women's AI use, or an individual putting AI to work, so it misses her theme criterion.
Companies & AIjournal
OpenAlex·14 April 2026·Halime Dinç, Bülent Gürbüz, Mehmet Tahir Dursun, Metin ARGAN, Mehpare Tokay Argan, Funda Koçak·Tourism, tier 3
A survey-based structural model of ChatGPT adoption for travel, folding TAM, theory of planned behaviour and word of mouth together. It is a confirmatory acceptance-model study in a tier 3 venue with no causal design, adding no new mechanism beyond what the library's technology-acceptance section already holds.
Companies & AIjournal
OpenAlex·14 April 2026·P. Naresh, Tanvir Habib Sardar, Bharti Ramityal, Ahlam Almusharraf, Mahesh T R, Vipul Jain·Enterprise Information Systems, tier 2
This is a technical architecture paper for edge-AI digital twins with a barrage of implausible-sounding component names and numbers, not a study of organizational adoption, people, or power. It offers no human or organizational mechanism and does not fit her themes.
Companies & AIjournal
OpenAlex·13 April 2026·Habib Alrashedi, Nader Alnomasy, Romeo Mostoles·JMIR Nursing, tier 3
A cross-sectional TAM survey of 132 Saudi nursing students finding usefulness and ease of use predict intention, which the library already holds in dozens of variants. It is tier 3, correlational, and framed around a specific local population, so it drops rather than earns a read.
Women & AIjournal
OpenAlex·13 April 2026·Moeketsi Mosia, Fadip Audu Nannim·Frontiers in Education, tier 3
A Bayesian mediation analysis on 79 South African pre-service teachers finds self-efficacy mediates AI-training-to-intention only for women and only among untrained teachers. The sample is tiny, the venue is tier 3 with no causal design, and the finding is local to one teacher-training population, so it drops a level.
Companies & AIjournal
OpenAlex·13 April 2026·Clara Punzi, Roberto Pellungrini, Mattia Setzu, Fosca Giannotti, Dino Pedreschi·ACM Computing Surveys, tier 3
This is a computing-survey taxonomy of machine-learning abstention methods for human-AI collaboration, not primary behavioral evidence. It offers no number or mechanism about how people trust or resist AI, just an ML methods classification.
Companies & AIjournal
OpenAlex·12 April 2026·Sebastian Then, Lars Burghardt, Matthias Borgstede, Yvonne Anders·International journal of child care and education policy/International journal of child care and education, tier 3
A survey of 886 German early-childhood staff finds self-efficacy and attitude (Will-Skill-Tool) predict ICT use in teamwork, echoing the acceptance literature the library already holds in depth. It is tier 3, correlational, and framed around German ECEC centres specifically, and it is not really about AI.
Companies & AIjournal
OpenAlex·11 April 2026·Qiao Jingjing, Zhao Yan, Xu Xiaobing, Li Li, Aasia Nusrat·Scientific Reports, tier 3
A PLS-SEM study of 392 Chinese EFL students finds technostress lowers and generative-AI use raises metacognitive reading strategies via motivation. It is tier 3, cross-sectional, locally framed, and only tangentially about workplace AI adoption rather than companies or women.
Companies & AIjournal
OpenAlex·11 April 2026·Nasareldeen Hamed Ahmed Alnor, Ebrahim Mohammed Al-Matari, Omer Alsir Alhassan Mohammed, Ibrahim Ahmed Elamin Eltahir, Mohamed Ishag Abdelrahman Eisa·Cogent Business & Management, tier 3
An OLS/correlation study of 180 bank and insurance firm-year observations claims AI use correlates with better financial analysis, with smaller firms less likely to adopt. This mirrors what the library already holds about AI gains concentrating in bigger firms, the design is not causal, and the venue is tier 3.
Companies & AIjournal
OpenAlex·10 April 2026·Angel M. Joseph, Angel M. Joseph, Rahaf E. Almutairi, Wejdan A. Alrashidi, Reem M. Almutairi, Yahya Theeban, Sami Aldhuwayhi, Ahmed Altuwalah·Scientific Reports, tier 3
A UTAUT survey of 700 Saudi dental students finds effort expectancy, not performance expectancy, drives LLM adoption intention. It is tier 3, cross-sectional, and framed around one national student population, echoing library findings that predictor rankings across UTAUT studies are unstable and often over-read.
Companies & AIjournal
OpenAlex·10 April 2026·Peter Rentzepis, Donna L. Snyder, Trevor Baker, Barbara E. Bierer·The American Journal of Bioethics, tier 3
An ethics and policy discussion of AI in clinical-trial recruitment with no primary data, essentially a framework and recommendations paper. It does not meet the bar for primary evidence regardless of venue.
Companies & AIjournal
OpenAlex·9 April 2026·Guikun Chen, Wenguan Wang·ACM Computing Surveys, tier 3
A computing survey of 3D Gaussian Splatting rendering techniques, entirely about graphics representation with no connection to organizational AI adoption, gender, or individual use of AI.
Companies & AIjournal
OpenAlex·8 April 2026·Michele Alves, Domingos Santos Martinho, Ricardo Marcão, Pedro Sobreiro·Systems, tier 3
Cross-sectional PLS-SEM survey of 104 Portuguese B2B managers, tier 3 venue with no causal design, and framed around this local sample rather than a general mechanism. It adds a mediation claim, exploratory innovation working through GenAI adoption, but that refines rather than changes what the library holds on adoption and performance.
Women & AIjournal
OpenAlex·7 April 2026·Ümmügülsüm Güler, Özge Mengi Çelik, Emine Nefise Başpınar, Elif Değirmencioğlu, Binnaz Eser, Dila Serenli̇oğlu, Gülnur Kiliç, İrem Gençoğlu·BMC Public Health, tier 3
A cross-sectional correlational study of 1240 Turkish adults linking diet literacy, AI attitudes and quality of life. It is tangential to her themes of organisational adoption or the gender AI gap, and gender appears only as one demographic predictor among many, not as a claimed mechanism.
Companies & AIjournal
OpenAlex·7 April 2026·Enas Jamal Alsaffarini, Bahaa Subhi Awwad·Sustainability, tier 3
A mixed-methods PLS-SEM study of Palestinian industrial firms finding AI has a small supporting role behind green marketing for sustainability outcomes. Tier 3 venue, locally framed sample, and the topic (green marketing and sustainability) sits outside her core adoption themes.
Companies & AIjournal
OpenAlex·7 April 2026·Derya Kayıran, Mehtap Sönmez, Alperen AVCI, Rahma Yusuf Haji Mohamud·Frontiers in Artificial Intelligence, tier 3
A qualitative interview study of 30 Turkish teachers on AI in curriculum, tier 3 venue. It concerns education practice rather than companies adopting AI or an individual professional's tool use, and offers no number or generalisable mechanism.
Companies & AIjournal
OpenAlex·5 April 2026·Megan Rand Wheeler, Brandi Everett, Victor R. Prybutok·Clean Technologies, tier 3
A systematic literature review proposing an environmental cost-benefit framework for AI infrastructure. It addresses AI's environmental footprint, not organisational adoption or the gender AI gap, so it falls outside her themes regardless of its tier 3 status.
Companies & AIjournal
OpenAlex·4 April 2026·Mingxin Li, Yuka Kikuchi, Jonas W. Ringsberg, Konstantinos C. Gryllias, Piero Baraldi, Enrico Zio, James Carroll·Renewable and Sustainable Energy Reviews, tier 3
A prospective review of digital twin technology for wind turbine maintenance. It has no connection to companies adopting AI in the organisational sense, women and AI, or individual AI use, and is a non-empirical framework paper in a tier 3 venue.
Women & AIjournal
OpenAlex·3 April 2026·Linda Ariany Mahastanti, Maria Rio Rita, Destri Destri Sitorus, Atahau Dorkas R Apriani·JWEE, tier 2
A PLS-SEM survey of 185 women-led MSMEs in Central Java on P2P lending usage. It is about fintech capability and context, not AI specifically, and the finding is framed around this local Indonesian sample rather than a general mechanism.
Women & AIjournal
OpenAlex·2 April 2026·Farah Zahan Shuchy, Md. Azaher Uddin·Media and Communication, tier 2
An interview-based feminist discourse analysis of gendered disinformation against Bangladeshi activists. The abstract contains no AI adoption content at all, and the finding is framed around this specific local uprising and platform context, not a transferable mechanism relevant to her themes.
Women & AIjournal
OpenAlex·2 April 2026·Aizhan Nazyrova, Muslim Sergaziyev, Assel Omarbekova, Latifa Sautbayeva, Zhandos Akimjan, Zhanar Lamasheva·Frontiers in Computer Science, tier 3
A conceptual paper proposing a human-centered AI framework for detecting mental health signals from women's social media use. It is a proposed framework, not primary empirical evidence of an adoption mechanism, and sits at the edge of her themes.
Companies & AIjournal
OpenAlex·2 April 2026·Vera Goer, Julian Schwarz·Die Psychotherapie, tier 3
Eleven German psychotherapists interviewed about ambient AI documentation tools report time savings and reduced cognitive load alongside quality concerns. This is a small qualitative sample framed around this local professional group, and it echoes rather than extends the library's existing findings that AI assistance reduces task burden.
Companies & AIjournal
OpenAlex·2 April 2026·Te Li, Hadrian Nichols·Economics of Innovation and New Technology, tier 2
A theoretical general equilibrium model of AI-driven automation and inequality, with no primary data collected. The rubric excludes non-empirical pieces regardless of how well they fit her themes.
Companies & AIjournal
OpenAlex·1 April 2026·Budi Setiawan, Sasiska Rani, Emilda Emilda, Firmansyah Arifin, Dinarossi Utami·Risks, tier 3
An extended UTAUT survey of 632 rural and urban MSMEs in South Sumatra finding facilitating conditions and effort expectancy dominate FinTech adoption in each group respectively. It is framed around this local Indonesian population and mainly reconfirms UTAUT drivers the library already holds in depth.
Women & AIjournal
OpenAlex·1 April 2026·Wang Honggang, Abdul Khalique Khoso, Adel R. Althubyani·Scientific Reports, tier 3
Cross-sectional SEM on 545 Chinese and international EFL students, framed around a specific population and a specific classroom context. It confirms the library's existing technostress and self-efficacy-buffer findings rather than adding a new mechanism, and Scientific Reports here carries no causal design to trigger the tier 3 exception.
Companies & AIjournal
OpenAlex·1 April 2026·Peter RITTGEN·IBIMA Business Review, tier 3
A literature review of AI trust antecedents concluding trust is 'complex and poorly understood.' No primary data, a tier 3 venue, and no causal design, so the exception cannot apply.
Companies & AIjournal
OpenAlex·1 April 2026·Rasha M. Abd El-Aziz, Wael Z. El-sayad, David Neels Ponkumar Devadhas, Alanazi Rayan, Loay F. Hussein·Frontiers in Sustainable Food Systems, tier 3
A generative AI framework for food-waste reclamation with simulated accuracy gains. It has nothing to do with organisational AI adoption, women and AI, or an individual's AI use, so it fails her theme fit outright.
Companies & AIjournal
OpenAlex·1 April 2026·Mohamad Firdaus Che Abdul Rani, Nor Hafizah Adnan, Ahmad Zamri Mansor, Melor Md. Yunus·Bulletin of Electrical Engineering and Informatics, tier 3
A PRISMA review of TAM in educational games confirming that perceived usefulness and ease of use are the strongest predictors, which the library already holds in depth. Tier 3 review with no causal design.
Companies & AIjournal
OpenAlex·1 April 2026·Levi Dean, Filippo Gilardi, Sadia Jamil, Helen Kennedy, Zhaoyu Zhu·Convergence The International Journal of Research into New Media Technologies, tier 2
An editorial introduction to a special issue on virtual production adoption challenges. It states no finding of its own, only describes the issue's contents, and virtual production is not an AI technology, so it misses both the evidence bar and the theme.
Companies & AIjournal
OpenAlex·31 March 2026·Sulaiman Alnujaidi·Journal of language and Education, tier 3
A UTAUT2 survey of 345 Saudi students and instructors finding performance expectancy is again the strongest predictor of ChatGPT adoption intention. Population-specific, tier 3, and it only reconfirms predictor rankings already well established in the library.
Companies & AIjournal
OpenAlex·31 March 2026·Ahed Al-Haraizah, Fida’a Al-Quran, Malik Jawarneh·Marketing and Management of Innovations, tier 3
A UTAUT survey of 343 Jordanians on drone delivery adoption. Not an AI technology, population-framed around Jordanian citizens, tier 3, and it adds no mechanism beyond standard UTAUT predictor patterns.
Women & AIjournal
OpenAlex·31 March 2026·Jayantika Yadav, Aamir Aijaz Syed·Scriptora International Journal of Research and Innovation (SIJRI), tier 3
A survey of rural Indian women's digital payment adoption across three named districts, finding trust, awareness and ease of use as barriers. This is a local population study, tier 3, non-causal, and it confirms rather than extends the library's existing digital-divide and adoption-driver findings for this same population.
Women & AIjournal
OpenAlex·31 March 2026·Hai Anh Thi Vu, Dieu Thi Nguyen, Lan Anh Thi Nguyen, Binh Thi Dinh, Nhung Thi Tran·International Journal of Science and Research Archive, tier 3
A PLS-SEM survey of 408 Hanoi seniors finding technophobia suppresses online shopping intention despite awareness of benefits. Locally framed, tier 3, cross-sectional, and it reconfirms the library's existing technophobia and TAM findings rather than adding a new mechanism.
Companies & AIjournal
OpenAlex·30 March 2026·Uğur Başarmak, Hüseyin Ateş·Education and Information Technologies, tier 3
A UTAUT2 plus Protection Motivation Theory survey of 864 Turkish pre-service teachers on AI-supported game-based learning adoption. Population-specific, tier 3, cross-sectional, and its predictor list (habit, hedonic motivation, self-efficacy) restates patterns already catalogued in the library's UTAUT holdings.
Companies & AIjournal
OpenAlex·30 March 2026·Kai Cao, Ping Wang, Chunzhen Zhang, Jie Zhao·PLoS ONE, tier 3
A TAM-UTAUT survey of library self-service system continuance among students and faculty at three Qinghai universities. Not an AI system, locally framed, tier 3, and it only reconfirms that ease of use and usefulness predict continued use.
Companies & AIjournal
OpenAlex·30 March 2026·Agus Widayoko, Syunu Trihantoyo, Nunuk Hariyati·AL-ISHLAH Jurnal Pendidikan, tier 3
A PRISMA review of 56 UTAUT education studies from 2015 to 2025 finding performance expectancy remains the top predictor. A review with no primary data, tier 3, and it duplicates conclusions the library already holds in far greater depth.
Women & AIjournal
OpenAlex·30 March 2026·Barış Alperen Özden, Pınar Duru·Journal of Evaluation in Clinical Practice, tier 3
A cross-sectional study of 265 Turkish nurses finding AI anxiety does not significantly mediate the link between health-tech attitudes and readiness for medical AI. Population-specific, tier 3, no causal design, and a single null mediation result in one hospital sample does not clear the bar even though it is a real number.
Companies & AIjournal
OpenAlex·30 March 2026·Peter Slattery, Alexander K. Saeri, Emily A. C. Grundy, Jess Graham, Michael Noetel, Risto Uuk, James Dao, Soroush Pour·Patterns, tier 3
A taxonomy of 1,725 AI risks pooled from 74 existing frameworks, built to standardise risk terminology. It is a governance and safety classification exercise with no finding about organisational adoption, women and AI, or individual AI use, so it does not fit her themes regardless of its scale.
Women & AIjournal
OpenAlex·28 March 2026·Luma Ghazi Alzamel, Layla Hassouneh, Samar Thabet Jallad·BMC Medical Education, tier 3
Cross-sectional survey of Jordanian healthcare students with descriptive statistics and ANOVA, no causal design, tier 3 venue with no exception available. It confirms the already well-held finding that AI attitudes are mixed and knowledge is patchy, adding no new mechanism or number.
Companies & AIjournal
OpenAlex·28 March 2026·Yunkun Zhang, Jin Gao, Zheling Tan, Lingfeng Zhou, Kexin Ding, Mu Zhou, Shaoting Zhang, Dequan Wang·ACM Computing Surveys, tier 3
A technical literature survey of data-centric foundation model methods for healthcare AI, with no primary empirical data on adoption, organizations or people. It does not speak to her themes of adoption mechanisms or workforce experience.
Women & AIjournal
OpenAlex·27 March 2026·Elif Dönmez, Gamze Temiz, Burak Mete, Elif Marangoz, Tülay Ortabağ·Healthcare, tier 3
Cross-sectional mediation study of 207 Istanbul oncology nurses linking AI readiness, attitudes and anxiety. No causal design, tier 3 venue, local sample, and it simply reconfirms the already-held finding that attitudes and anxiety move together.
Women & AIjournal
OpenAlex·27 March 2026·Zühal Kınış, Fatih Denizli, Ozgur DEMIRTAS·BMC Health Services Research, tier 3
Correlational field study of 418 healthcare workers in Kayseri testing transformational leadership as a mediator between AI anxiety and job performance. Tier 3, no causal design, local sample, and it adds only an incremental mediator to an already crowded anxiety-outcome literature.
Companies & AIjournal
OpenAlex·27 March 2026·Kağan Kırcaburun, Pınar Güzel Özdemir·Behavioral Sciences, tier 3
Path analysis of 491 adults linking antagonistic personality traits to problematic generative AI use via moral disengagement. Correlational, tier 3, and tangential to her adoption and gender themes rather than adding a mechanism she would cite.
Companies & AIjournal
OpenAlex·27 March 2026·Nipuna Chamara, Yu Pan, Saleh Taghvaeian, Cory Walters, Chris Proctor, Daran R. Rudnick, Daren D. Redfearn, Joe Luck·Artificial Intelligence in Agriculture, tier 3
A single-season case study of ChatGPT-4o generating farm management decisions on one research plot, with no comparison data on adoption behaviour or outcomes beyond speed and plausibility. It is a tool demonstration, not primary evidence about how people or organizations take up AI.
Companies & AIjournal
OpenAlex·26 March 2026·Sadia Samar Ali, José Antonio Marmolejo-Saucedo, Rosario Landa Piedra, Gerhard-Wilhelm Weber·Logistics, tier 3
A Best-Worst Method ranking of critical success factors for digital twin adoption in warehousing, based on six expert judgments. No causal design, tier 3 venue, and it deals with digital twins rather than AI adoption mechanisms she tracks.
Women & AIjournal
OpenAlex·25 March 2026·Guifeng Zheng, Yanting Wang, Juan Du·PLoS ONE, tier 3
A TAM-extension survey on mobile learning apps in physical education finds usefulness and attitude drive intention and self-efficacy, which is exactly what the library's acceptance meta-analyses already establish. No new predictor, no AI content, tier 3 venue.
Companies & AIjournal
OpenAlex·24 March 2026·Shaofeng Wang, Hao Zhang·International Journal of Educational Technology in Higher Education, tier 3
A tier 3 venue with a cross-sectional, non-causal mixed-methods design (SEM, IPMA, fsQCA) on student cognitive offloading in higher education, it neither names a qualifying causal design nor sits close to her organizational or gender themes.
Companies & AIjournal
OpenAlex·24 March 2026·Hanan Shaher Almarashdi, Othman Abu Khurma, Khaleel AlArabi, Enas Abulebdeh, Jihan Yousef·European Journal of STEM Education, tier 3
A bibliometric mapping of AI-in-STEM-education literature with no primary data and no mechanism or number to weigh.
Women & AIjournal
OpenAlex·23 March 2026·Erhan Dağ, Mustafa Nal, İbrahim Topuz, Hatice Kılınç, Yaşar Demir, Gülfer Bektaş·Scientific Reports, tier 3
A cross-sectional correlational survey of Turkish health-sciences students linking AI anxiety to job-search anxiety (r=0.233); tier 3, locally framed, and it only restates the already well-documented AI anxiety literature.
Companies & AIjournal
OpenAlex·23 March 2026·Claudiu Coman, Vasile Gherheș, Anna Bucs, Ecaterina Coman, Cioca Victoria-Rodica, Diana-Cristina Bódi, Raluca-Maria Șerbănescu·Frontiers in Artificial Intelligence, tier 3
A thematic review of 27 articles on GenAI in higher education with no primary data, offering only a synthesis of known themes like literacy and acceptance.
Companies & AIjournal
OpenAlex·23 March 2026·Joshua W. Ohde, Arjun Thompson, Zhenghong Liu, Lauren M. Rost, Joshua Overgaard, Jonathan Yue En Tan, Shauna M. Overgaard, Raymond Francis Sarmiento·npj Digital Medicine, tier 3
An opinion perspective piece on scaling ambient AI scribes with no primary data, evidence, or mechanism.
Companies & AIjournal
OpenAlex·23 March 2026·Tanzina Akter, Shiful Islam, Abrar Maswood Haider, Kaniz Fatema, Fiona Stapleton, Mark Willcox·European Journal of Clinical Microbiology & Infectious Diseases, tier 3
A narrative review of antibiotic resistance in Pseudomonas aeruginosa keratitis, entirely unrelated to AI adoption or organizational or gender themes.
Women & AIjournal
OpenAlex·20 March 2026·Chang Liu (35901), Zuhao Sun·Acta Psychologica, tier 2
A correlational survey of Chinese physical-education faculty shows technostress lowering creative self-efficacy and innovation, buffered by perceived innovation importance; it is locally framed and mostly restates the library's existing five-dimension technostress model rather than adding a new mechanism about AI specifically.
Companies & AIjournal
OpenAlex·20 March 2026·Thirumalaisamy Suryaprabha, Chunghyeon Choi, Yanfang Wu, Liyang Liu, Byungil Hwang·npj Flexible Electronics, tier 3
A materials-science review of wearable biosensors that mentions AI only as a peripheral signal-processing tool, with no primary adoption or organizational data.
Companies & AIjournal
OpenAlex·20 March 2026·Irene Dini·Antibiotics, tier 3
A review of antimicrobial resistance mechanisms and food-chain contamination, unrelated to AI or organizational themes.
Companies & AIjournal
OpenAlex·19 March 2026·Misnawati Misnawati, Saidna Zulfiqar Bin-Tahir, Masriadi Masriadi, Fatimah Hidayahni Amin, Alwi Sibali·Frontiers in Education, tier 3
A small quasi-experimental study (n=30) of a mobile corpus-linguistics tool for Indonesian ESP students; it is not about AI, is locally framed, and its design does not qualify for the tier 3 causal exception.
Women & AIjournal
OpenAlex·19 March 2026·Reem Alsadoon·Frontiers in Psychology, tier 3
Cross-sectional, mixed-methods study of 60 Saudi female EFL students using ChatGPT, tier 3 venue with no causal design, so the venue rule blocks a must-read regardless of the behavioural-tracking method. The finding that heavier copying tracks weaker integrity beliefs largely echoes the library's existing 'feels like cheating' finding, and the population framing (Saudi female EFL students) pulls it down further.
Companies & AIjournal
OpenAlex·19 March 2026·Mingcheng Wang, Panyue Du, Liyang Xi, Haifeng Lin, Shufen Zhang·Biomolecules, tier 3
A plant molecular biology review of ERF transcription factors in crop stress response, with no connection to organisational AI adoption or gender and AI whatsoever.
Companies & AIjournal
OpenAlex·19 March 2026·Waleed Mugahed Al-Rahmi·Journal of University Teaching and Learning Practice, tier 3
A TOE/DOI survey of 300 Saudi higher-education staff finding that culture, compatibility and relative advantage drive AI adoption intention, which just restates textbook technology-acceptance predictors already deeply covered in the library. Tier 3 venue, no causal design, and a specific national population caps it at low.
Companies & AIjournal
OpenAlex·18 March 2026·Le Fang, Yujie Zhu, Jiajuan Li, Cong Fang, Yingqing Xu, Stephen Jia Wang·International Journal of Human-Computer Interaction, tier 2
A cross-sectional survey of 458 Chinese respondents finds users want AI as an objective 'clinical assistant' rather than an empathetic therapist and reject it in high-stakes emotional crises. It is a specific-population, correlational study on personal emotional-regulation AI rather than organisational adoption or the gender gap, so it only weakly fits her themes and the local framing pulls it further down.
Companies & AIjournal
OpenAlex·18 March 2026·Kutoya Kusse, Asmera Adicha·Critical Insights in Agriculture, tier 3
A double-hurdle econometric study of Ethiopian smallholder maize adoption with no AI content at all, and a specific local population, so it neither fits her AI themes nor clears the bar on its own agricultural-technology terms.
Companies & AIjournal
OpenAlex·17 March 2026·Shane McLoughlin, Verónica Fernández-Espinosa, Marta Velázquez-Gil·Journal of Moral Education, tier 3
Two correlational studies link practical wisdom to techno-optimism and more ethically reflective AI engagement, credible but a moral-psychology construct-validation exercise, not a finding about company AI adoption or the gender gap. Tier 3, no causal design, and one sample is a specific national student population.
Companies & AIjournal
OpenAlex·17 March 2026·Aymane Chemmaa, Mohammed Amine, Mohammed Ibrahimi·Corporate and Business Strategy Review, tier 3
A systematic review of 21 papers mapping which AI models different regions use for earnings-management detection. It is method-cataloguing scholarship about accounting research practice, not a finding about how organisations adopt AI or about women and AI.
Companies & AIjournal
OpenAlex·17 March 2026·Kewen Huang, C Chen, Hongyu Wu, Yi Su, Xiaoting Wu, Bo Huang, Jiangjun Wan·Agriculture, tier 3
A random-forest/SHAP analysis of 482 Chinese farmers' agricultural technology adoption, finding male, middle-aged, higher-income farmers adopt more. It is a local-population study using machine learning as an analytic tool rather than a study of AI adoption itself, and it echoes known adoption predictors.
Women & AIjournal
OpenAlex·16 March 2026·Rouba Jamal Eddine, Ergun Gide, Abdallah Al-Sabbagh·Discover Computing, tier 3
A PRISMA-ScR evidence map of just twelve studies on GenAI and digital-divide equity in higher education, identifying access, literacy, cost and policy barriers that the library's digital-divide section already documents in more concrete numbers. It is a synthesis with no primary data of its own.
Women & AIjournal
OpenAlex·16 March 2026·Alfred Mvunyelwa Msomi, Kavita Behara·Education Sciences, tier 3
A correlational survey of 121 South African students finds institutional support correlates with AI-learning perceptions more than material access (r=0.212), a weak effect in a specific disadvantaged local population, with no causal design to offset the tier 3 venue and geography penalty.
Companies & AIjournal
OpenAlex·16 March 2026·Faisal Saeed Malik, Orestis Terzidis·Review of Managerial Science, tier 2
A hybrid systematic literature review of 76 studies on SME resilience treats digital transformation as just one enabler among many rather than examining AI adoption mechanisms directly, and it is a secondary synthesis with no primary data of its own.
Companies & AIjournal
OpenAlex·15 March 2026·Hakan Kaya·Sakarya University Journal of Computer and Information Sciences, tier 3
Another TAM/UTAUT extension, this time for meta-banking with technostress and AR/VR, confirming that ease of use, usefulness and trust drive adoption and technostress lowers perceived value. These are relationships the library's instrument and acceptance sections already establish at scale, and the tier 3 venue with no causal design blocks anything higher.
Women & AIjournal
OpenAlex·15 March 2026·Marijana Ćuk, Ivana Batarelo Kokić·Nova prisutnost, tier 3
Validates a human-enhancement-technology questionnaire on Croatian secondary students and finds no gender or grade differences, only an achievement effect on scepticism. It is about enhancement tech generally rather than AI adoption or a company or person putting AI to work, a Croatian tier 3 survey with no causal design, and it does not change anything the library holds on gender and technology attitudes.
Companies & AIjournal
OpenAlex·15 March 2026·Isaac Davor, Francis Ohene Boateng, Prince Osei-Tutu, Aaron Osei Bosompem, Asie Sumalia Patience, Lord Ampofo Adusei·Journal of mathematics science and technology education., tier 3
A cross-sectional SEM study of 375 Ghanaian undergraduates finds ChatGPT use predicts math problem-solving efficacy via digital literacy and critical thinking, essentially another TAM mediation confirmation. Tier 3 venue, no causal design, and the finding is framed about a specific Ghanaian student population rather than a general mechanism, so it drops further.
Companies & AIjournal
OpenAlex·14 March 2026·Bernardo G. Collaco, Syed Ali Haider, Srinivasagam Prabha, Cesar A. Gomez-Cabello, Ariana Genovese, Nadia Wood, Sanjay P. Bagaria, Narayanan Gopala·npj Digital Medicine, tier 3
A scoping review of only seven exploratory studies on agentic AI in healthcare, explicitly lacking rigorous clinical validation. It is secondary literature, not primary evidence, so it cannot pass the evidence bar regardless of venue.
Companies & AIjournal
OpenAlex·13 March 2026·Muhammad Salman Shabbir, Amir Keshtiban·Business Strategy and the Environment, tier 3
A bibliometric-systematic literature review proposing a conceptual ecosystem framework for GenAI and social entrepreneurship, with no primary data and only 'analytically derived' mechanisms for future study. Opinion-adjacent synthesis, not evidence.
Companies & AIjournal
OpenAlex·13 March 2026·Sabah Abdullah Al-Somali·Systems, tier 3
PLS-SEM survey of 191 Saudi food-logistics managers on Industry 4.0 adoption and supply chain resilience; the framing is about a specific Saudi industry population and the technology in question is Industry 4.0 broadly, not AI, so it barely touches her themes and confirms known adoption-success drivers.
Companies & AIjournal
OpenAlex·12 March 2026·Kamel Mouloudj, Tiziana Amoriello, Eeman Almokdad, Rafid Abduljalil Majeed Al-Hassan, Ahmed Chemseddine Bouarar, Smail Mouloudj·Sustainability, tier 3
TAM extension survey of 214 Algerian grocery retailers finds perceived usefulness, ease of use and economic utility drive AI adoption intention for waste reduction, another confirmatory TAM finding. The Algerian retailer sample is a named local population, which drops it a further level.
Companies & AIjournal
OpenAlex·12 March 2026·Michelle A. Fortier, Lessley B. Torres, Belinda Campos, Haydee G. Cortes, Sonia Morales, Carol Lin, Lilibeth Torno, Zeev N. Kain·Children, tier 3
A single-arm pre-post trial of a psychosocial intervention for Latino caregivers of children with cancer, with no AI or technology content whatsoever. It does not engage any of her three themes.
Companies & AIjournal
OpenAlex·12 March 2026·Ramil Akhundov, Elshan Hashimov·Management Information System and Devises, tier 3
A conceptual paper on information-flow modeling for physical protection system design, entirely about security engineering rather than AI adoption, companies, or women and AI. No fit to her themes.
Companies & AIjournal
OpenAlex·12 March 2026·Tong Zhu, Mohd Zaidi Abd Rozan·PLoS ONE, tier 3
Qualitative interview study of Anhui, China e-commerce firms describing stratified AI adoption patterns ('platform-bound' to 'self-developed') and a human-AI collaboration model. It is a named local population with no causal design, and its adoption-maturity observations largely echo what the practitioner-shelf records already show.
Women & AIjournal
OpenAlex·11 March 2026·Emma C. Stephens, Marie L. Spiker, Ramya Ambikapathi, Jennifer Rebecca Wiegel, E. F. Phillips, James Leo Garrett, Daniel Mason-D'Croz, Laura Cramer·Frontiers in Sustainable Food Systems, tier 3
A methodological paper advocating participatory systems modeling for gender-responsive agri-food policy under climate change, with no AI or technology adoption content at all. It does not engage her themes despite the gender framing.
Companies & AIjournal
OpenAlex·11 March 2026·Osman Titrek, Nermin Dingin, Cemile Yaşa·Pedagogika, tier 3
A short correlational study of 260 pre-service teachers finding digital competence positively relates to AI attitudes, with no gender breakdown reported. This is a thin, confirmatory restatement of the self-efficacy and ease-of-use literature already well covered in the library.
Companies & AIjournal
OpenAlex·11 March 2026·Antonio Pérez-Portabella, Jorge de Andrés-Sánchez, Mario Arias-Oliva, Graciela Padilla-Castillo·Innovative Higher Education, tier 3
Cross-sectional PLS-SEM survey of 151 Spanish social-science students, tier 3 venue with no causal design, so it cannot carry a must-read. The finding that routine legitimate GenAI use predicts misuse intentions is plausible but rests on a small local sample and correlational modeling.
Companies & AIjournal
OpenAlex·11 March 2026·Sheela Sundarasen, Kamilah Kamaludin, Deepa Nakiran·Journal of risk and financial management, tier 3
A bibliometric mapping of AI-auditing literature using Biblioshiny and VOSviewer. It has no primary data on adoption or outcomes, only citation clustering, so there is nothing here that changes what she would say.
Companies & AIjournal
OpenAlex·10 March 2026·Mohammad Mousa Mousa, Abdullah Saad Rashed, Mustafa Akaileh, Ahmad M. Zamil, Hebatallah A. M. AHMED, Abdelrahman A. A. ABDELGHANI·Sustainability, tier 3
A PLS-SEM survey of 487 Saudi telecom customers testing TAM constructs on AI marketing tools. Tier 3 venue, no causal design, locally framed sample, and the finding that usefulness-type variables predict purchase intention just restates what the acceptance literature already holds.
Companies & AIjournal
OpenAlex·10 March 2026·Purshottam J. Assudani, Balakrishnan . P., Anny Leema A, Gina George, Ankita Avthankar, Aditya Tiwari, Manish Bhaiyya, Madhusudan B. Kulkarni·Microchimica Acta, tier 3
A biosensor engineering review for foodborne pathogen detection. It has no bearing on companies adopting AI or on women and AI, and offers no organizational or attitudinal data at all.
Companies & AIjournal
OpenAlex·10 March 2026·Hung Dong Truong, Zhixing Ge, Elgene Chng, Y-Van Tran, Yusheng Zhang, Chwee Teck Lim·Microsystems & Nanoengineering, tier 3
A tissue-engineering review on spatial organization in microphysiological systems. It is unrelated to AI adoption or gender and AI in any way.
Companies & AIjournal
OpenAlex·10 March 2026·Şerife Hikmet, Nazife Ozay·Buildings, tier 3
A qualitative interview study proposing a conceptual framework for human-AI collaboration in architecture education. Tier 3, no causal design, and no primary quantitative finding to weigh.
Women & AIjournal
OpenAlex·9 March 2026·Samantha Teague, Klaire Somoray, Adrian Shatte, Daniel J. Miller, Kristian Moss, Andrew Crawford, Harrison Wildman, Diana Kayal·Archives of Pediatrics and Adolescent Medicine, tier 3
A large preregistered meta-analysis (153 studies, 18,933 participants) on digital media and child health outcomes, but it is about screen time and developmental effects in children, not about AI adoption, companies, or the gender gap in AI use. It does not speak to her themes despite the size of the dataset.
Women & AIjournal
OpenAlex·9 March 2026·Deborah Salvo, Inácio Crochemore-Silva, Andrea Wendt, Jakob Tarp, Eric J. Shiroma, Ruth Simpson, I-Min Lee, Ulf Ekelund·Nature Medicine, tier 3
A global analysis of physical-activity inequality by gender and income, published in Nature Medicine but tagged tier 3 here. It documents a 40-point gap in active leisure between privileged and disadvantaged groups, but this is about physical activity, not AI or technology adoption, so it does not fit her themes.
Companies & AIjournal
OpenAlex·9 March 2026·Olivia G. Stewart·AI in Education, tier 3
A qualitative thematic analysis of Reddit discussions among higher-education faculty about AI. Tier 3, no causal design, interpretive rather than measurement-based, and it offers no number or mechanism beyond describing recurring discourse themes.
Women & AIjournal
OpenAlex·8 March 2026·Özkan Özbay, Selma Durmuş Sarıkahya, Sevil Çınar Özbay·Participatory Educational Research, tier 3
A correlational survey of 451 Turkish university students links digital detox to lower digital phobia and higher self-efficacy and academic performance. It is locally framed, tier 3, non-causal, and it restates the already well-documented self-efficacy and anxiety associations rather than adding a new mechanism.
Companies & AIjournal
OpenAlex·6 March 2026·Fiona Buckmaster, Diane van Staden, Lauren Coetzee·Ophthalmic and Physiological Optics, tier 3
A cross-sectional survey of UK optometry students and educators finds most students have had no AI training and rate their knowledge low, while trained respondents hold more positive attitudes. This restates the well-established training-attitude link already in the library, on a small tier 3, professionally narrow sample.
Companies & AIjournal
OpenAlex·6 March 2026·Shanhui Wu, Tian Wang·Energies, tier 3
Panel data on Chinese listed firms links generative AI development to lower energy intensity through human capital and dynamic capabilities, but the outcome, corporate energy efficiency, sits outside her themes of adoption, workforce and individual use. Tier 3 venue and a firm-population frame push it further down.
Women & AIjournal
OpenAlex·5 March 2026·Majid Mapkhot Goaill, Adel Abdulmohsen Alfalah, Yaser Hasan Al‐Mamary, Aliyu Alhaji Abubakar, Nezar Mohammed Al‐Samhi, Isyaku Salisu, Mohammad Alshallaqi, Homoud Alhaidan·Humanities and Social Sciences Communications, tier 3
A PLS survey of 314 Saudi job seekers finds internet self-efficacy mediates economic satisfaction from internet use, which restates the library's existing self-efficacy mechanism. Local population framing, no causal design, tier 3 venue.
Companies & AIjournal
OpenAlex·5 March 2026·Hanhui Li, Fan Yang, Jinpeng Liu·BMC Psychology, tier 3
An SEM survey of 442 Chinese college students finds task complexity raises AI dependency through cognitive load and future anxiety while motivation dampens it, explicitly reporting no gender differences. Cross-sectional, tier 3, and the population is students rather than her companies or individual-professional themes.
Companies & AIjournal
OpenAlex·5 March 2026·Michael Constantin Kirchberger·JMIR Formative Research, tier 3
A cross-sectional US survey finds most people trust a physician's own judgment over AI diagnosis and want mandatory AI training in medical school. Descriptive-only, tier 3, and about patient perceptions rather than organizational adoption or individual professional AI use.
Companies & AIjournal
OpenAlex·5 March 2026·Lina Zhao, Shengrui Liu, Tangsiwei Xin, Jiawen Tan, Xiaoran Wang, Yafang Li, Zihao Bian, Yiyang Chen·npj Artificial Intelligence, tier 3
A narrative review of AI agents in healthcare with no primary data, proposing future research directions. Tier 3, review only.
Companies & AIjournal
OpenAlex·5 March 2026·Humairah Zainal, Voo Teck Chuan, Xiaohui Xin, Julian Thumboo, Fong Kok Yong·Medical Education, tier 3
Thematic analysis of 30 interviews with Singaporean early-career doctors builds an ethics competence framework for clinical AI. Qualitative, local population, tier 3, no mechanism or number that changes her framing of company or individual AI adoption.
Companies & AIjournal
OpenAlex·5 March 2026·Bramwell Kundishora Gavaza, Obrain Murire·Journal of Entrepreneurship and Sustainability Issues, tier 3
A qualitative synthesis of thirty existing publications on township small business technology adoption in South Africa, calling for more research. No primary data of its own, local population, tier 3.
Companies & AIjournal
OpenAlex·5 March 2026·Brad S. Currier, Alysha C. D’Souza, Maria Fiatarone Singh, Caroline V Lowisz, Eric S. Rawson, BRAD J. SCHOENFELD, ABBIE E. SMITH-RYAN, Jeremy Steen·Medicine & Science in Sports & Exercise, tier 3
An overview of reviews on resistance training prescription for muscle hypertrophy. Entirely unrelated to AI adoption or her themes.
Women & AIjournal
OpenAlex·4 March 2026·Mathea Brückner, Christoph Thyssen, Johannes Huwer·Frontiers in Education, tier 3
A pre-post pilot with German science teachers finds a short intervention raises AI self-efficacy and perceived usefulness. No control group, small pilot, tier 3, and it confirms the library's existing pattern that brief interventions close self-efficacy gaps rather than adding a new mechanism.
Companies & AIjournal
OpenAlex·4 March 2026·Yi Zhang, Yanqi Han, Ying Sun, Longhui Hao, Yue Gao, Jun Ye, Hongliang Wang, Tiantai Zhang·Signal Transduction and Targeted Therapy, tier 3
A molecular biology review of osteoarthritis pathogenesis and therapeutics, with no connection to AI or organizational adoption.
Companies & AIjournal
OpenAlex·4 March 2026·Nesrine Gafsi, Amina Hamdouni, Aida Smaoui·Sustainability, tier 3
Cross-country panel regression across G20 economies finds AI, FinTech and blockchain each raise sustainable development scores, with AI the strongest. Macro sustainability outcomes are outside her themes of organizational adoption dynamics, workforce effects or individual AI use, tier 3 venue.
Companies & AIjournal
OpenAlex·4 March 2026·Jehad Alqurni·Frontiers in Artificial Intelligence, tier 3
A 280-student SEM-PLS survey validating an ESG framework for AI-Metaverse adoption in one university context. It only restates that usefulness and social acceptance beat governance concerns, which the library's acceptance-model holdings already cover, and the tier 3 venue with no causal design cannot carry a must-read.
Companies & AIjournal
OpenAlex·4 March 2026·Aron Witkowski, Andrzej Wodecki·Journal of Manufacturing Technology Management, tier 2
This is a maturity-model and diagnostic tool built through design science research and expert validation, not a hypothesis-tested empirical study. Case studies only report vague 'moderate maturity, limited adoption' findings with no number or mechanism, so it reads as a practitioner framework rather than primary evidence.
Companies & AIjournal
OpenAlex·3 March 2026·Md. Jabir Al Mursalin·BRAC University Journal, tier 3
A 255-firm UTAUT validation among Bangladeshi SMEs. It is a locally framed population study in a tier 3 venue with no causal design, and it only reconfirms performance and effort expectancy as adoption drivers, which the library already holds in depth.
Companies & AIjournal
OpenAlex·3 March 2026·Asma Almusharraf·Humanities and Social Sciences Communications, tier 3
A mixed-methods study of 387 Saudi students using AI chatbots for writing finds usefulness predicts outcomes and gender shows no significant effect. It is a locally framed sample in a tier 3 venue with no causal design, adding nothing beyond what usefulness-driven acceptance models already say.
Companies & AIjournal
OpenAlex·3 March 2026·Mohammad S. Abu-Mahfouz, Sarah AlFehaid, Hala M. Burqan, Rabie Adel El Arab·Frontiers in Psychiatry, tier 3
A scoping review of reviews on AI in mental health care, reporting internal validation accuracies around 0.80 to 0.88 that drop sharply externally. This is clinical AI performance evidence, not organisational adoption or women and AI, and a review of reviews in a tier 3 venue cannot carry a must-read.
Companies & AIjournal
OpenAlex·2 March 2026·Guanli Xie, Jianglong Liao, Xiaoxia Tang, Yuting Yang, Fu Han, Duo Liu, Deng Li, Yaju Jin·BMC Medical Education, tier 3
A scoping review of 123 articles on digital health literacy in medical education finds fragmented frameworks and motivation gaps, with no gender analysis and no causal design. It is a tier 3 synthesis that restates known implementation barriers without a new mechanism.
Companies & AIjournal
OpenAlex·2 March 2026·Raghu Raman, Krishnashree Achuthan, Prema Nedungadi·Information, tier 3
A theoretical systematic review mapping GenAI education adoption onto the Antecedents-Decisions-Outcomes framework, built on TAM and institutional theory with no primary data collected. It offers no number or mechanism beyond restating that usefulness, literacy and readiness matter.
Companies & AIjournal
OpenAlex·2 March 2026·Shuang Wang, Zhiyuan Li, Mengjiao Pei, Qinqi Ren, Ming Deng, K. Kian Ang, Alon Ascoli, Sarbajit Banerjee·ACS Nano, tier 3
A materials-science roadmap on bioinspired computing hardware for AI chips. It does not address organisational adoption, women and AI, or any individual's use of AI, and sits outside her themes entirely.
Companies & AIjournal
OpenAlex·1 March 2026·Yunhao Chen, Jiajun Yuan, Chengjin Li, Hansong Wang, Lili Shi, Shan Zhao, Abílio Oliveira, Liebin Zhao·BMJ Open, tier 3
A 1222-patient UTAUT and Knowledge-Attitude-Practice survey of elderly chronic-disease patients in Shanghai finds technology anxiety lowers and effort and performance expectancy raise intention to use digital health tools. This is a locally framed population study in a tier 3 venue that only reconfirms the standard TAM predictors already in the library.
Companies & AIjournal
OpenAlex·1 March 2026·Viktoria Mazur, David Ramiro Troitino·Białostockie Studia Prawnicze, tier 3
A legal policy analysis arguing EU digital inclusion should become an enforceable right, drawing on Eurostat data and case studies rather than original empirical testing. It has no primary data and no mechanism, so it does not clear the evidence bar regardless of venue.
Companies & AIjournal
OpenAlex·1 March 2026·Carolyne Nabwoba Simiyu, Kennedy Ndenga Malanga, Franklin Wabwoba·Sustainable and Pedagogical Technologies, tier 3
A conceptual systematic review and framework proposal on GenAI resistance in developing-country higher education, with no primary data collected. It argues resistance stems from ethical and infrastructural concerns rather than technophobia, but this is opinion synthesis, not evidence.
Companies & AIjournal
OpenAlex·1 March 2026·Georgia Channing, Avijit Ghosh·Patterns, tier 3
A tier 3 opinion piece arguing that social and institutional factors, not technical ones, limit AI's impact on science. No primary data and no causal design, so the venue rule blocks any must-read regardless of the argument's plausibility.
Companies & AIjournal
OpenAlex·1 March 2026·Njeri Chege·Social Sciences, tier 3
An opinion essay on African privacy awareness and AI readiness, tier 3, with no primary data collection or causal design. It is a policy argument, not evidence that would change a claim about company AI adoption.
Companies & AIjournal
OpenAlex·28 February 2026·Hamza Alqudah, Adel M. Qatawneh, Abdalwali Lutfi, Sajead Mowafaq Alshdaifat, Ahmad Farhan Alshira’h, Hosam Alden Riyadh, Malek Hamed Alshirah, Mohamed Saad·The International Journal of Digital Accounting Research, tier 2
Another UTAUT-PLS-SEM survey, this time on Jordanian accountants adopting digital accounting systems, not AI. It reproduces familiar UTAUT predictors already exhaustively covered in the library and is framed around a specific local population, so it adds nothing new and drops a level besides.
Companies & AIjournal
OpenAlex·28 February 2026·Jinhui Wu, Changqing Xiang, Jie Zhao, Huajiang Zhang, Yuliang Ji, Shengli Li·Scientific Reports, tier 3
A TAM plus Technology Readiness Index survey of Chinese college students adopting sports wearables. Tier 3, local population, non-AI technology, and it only reconfirms the standard usefulness or ease-of-use finding the library already holds many times over.
Companies & AIjournal
OpenAlex·28 February 2026·Jeong, Choi, Mun·Behavioral Sciences, tier 3
A UTAUT and Media Richness Theory survey of Korean Gen Z sports learners split by digital literacy level. Tier 3, not about AI or companies, and it only restates that higher digital literacy correlates with higher acceptance scores, which the library's acceptance section already covers extensively.
Companies & AIjournal
OpenAlex·28 February 2026·Irfan Saleem, Manuela Weller, Abdul Rauf, Muhammad Ashfaq·The International Journal of Entrepreneurship and Innovation, tier 2
A time-lagged SEM survey of German family-owned SMEs proposing AI adoption as a moderator between knowledge acquisition, frugal innovation and resilience. The contribution is explicitly framed around the German Mittelstand context rather than a general mechanism, which drops it a level, and the moderating role claimed is vague rather than a stated effect size.
Companies & AIjournal
OpenAlex·28 February 2026·Danarsiwi Tri Lastiwi, Ekawati Marlina, Jihan Fie Jannath·International Journal of Innovation and Learning, tier 2
The abstract supplied is publisher boilerplate with no actual findings reported, and the underlying topic, a case study of one Indonesian LMS platform, is local and non-AI. Nothing here could inform a claim about company AI adoption.
Companies & AIjournal
OpenAlex·27 February 2026·Dana Olsen, Cecilia Nguyen, Marshall Hall, Michael Carletti, Stephen E Weis·HCA Healthcare Journal of Medicine, tier 3
A clinical dermatology paper about the Fitzpatrick skin-tone scale that mentions AI only as one possible alternative measurement tool. It does not address company adoption, women and AI, or an individual putting AI to work, so it does not fit either theme.
Companies & AIjournal
OpenAlex·27 February 2026·Maria Rhoda Damos Sosas, Arcelli Faith Getalla Fat, Jody May Minao Dangculos, Harvey Rex Pitogo Anoba, Charlene Go Remiscal, Judith M. Aleguen·Contemporary Mathematics and Science Education, tier 3
A small mixed-methods survey of 91 Filipino pre-service teachers on ChatGPT as a math-learning aid, tier 3, confirming the standard finding that perceived ease of use and compatibility drive positive intention, which the library's acceptance section already holds many times over.
Companies & AIjournal
OpenAlex·27 February 2026·Maikel Leon·Big Data and Cognitive Computing, tier 3
A narrative review positioning generative AI as a general-purpose technology and proposing a conceptual 'disruption index.' It presents no primary data collection, is tier 3, and functions as synthesis and recommendation rather than new evidence.
Companies & AIjournal
OpenAlex·27 February 2026·Rohit Agrawal, Vishal Ashok Wankhede·International Journal of Lean Six Sigma, tier 2
A factor-analysis and DEMATEL study ranking critical success factors for combining Industry 4.0 with Lean Six Sigma. It is not about AI specifically and does not engage either of her themes directly, so it falls outside scope regardless of method quality.
Companies & AIbusiness
Deloitte Insights·26 February 2026·tier 2
The piece promotes Deloitte's own 'people-focused approach' with a claimed 90% adoption and 15% productivity result, marketing language for a proprietary methodology rather than independent primary evidence.
Companies & AIjournal
OpenAlex·26 February 2026·Irina Canco, Drita Kruja, Forcim Kola·Tourism and Hospitality, tier 3
Tier 3 venue with no causal design, workforce segmentation by cluster analysis in Albanian tourism only, a specific local population rather than a general mechanism. Confirms already-documented digital skills gaps without adding a transferable finding.
Companies & AIjournal
OpenAlex·25 February 2026·Elif Güzelyurt, Aynur Kolburan Geçer, Arzu Deveci Topal, Canan Dilek Eren·International Journal of Information and Learning Technology, tier 3
A TAM survey on LMS acceptance during emergency remote teaching, not about AI, and its findings, gender and situational differences in acceptance, are already thoroughly covered by the library's TAM holdings. Tier 3 venue with no causal design.
Companies & AIjournal
OpenAlex·25 February 2026·Julius Samuel Opolot, Gabriel Simiyu, Sulait Tumwine, Rogers Mwesigwa, Sentrine Nasiima·Cogent Psychology, tier 3
A Ugandan university study of organizational culture, commitment and turnover intention with no mention of AI or digital technology at all. Off-theme for her library and tier 3.
Companies & AIjournal
OpenAlex·25 February 2026·N. D. Broshevitskaya, Anastasia A Rebik, Lidia M. Birioukova, Maria Zaichenko, I. S. Midzyanovskaya·OBM Neurobiology, tier 3
An animal behavior study of aggression and autonomic responses in a rat strain, entirely unrelated to AI, organizations or women. No thematic fit.
Companies & AIjournal
OpenAlex·25 February 2026·Andrea De-Santis, Ángel Torres-Toukoumidis, Ramiro Morejón-Vallejo·Social Sciences & Humanities Open, tier 3
Survey of Ecuadorian citizens' perceptions of AI in political campaigns, framed around a specific national population and concerned with democratic legitimacy rather than company adoption or women and AI. Tier 3 with no causal design.
Companies & AIjournal
OpenAlex·25 February 2026·Esther O. Esho, Andronicus A. Akinyelu, Maria Alzira Pimenta Dinis·Frontiers in Sustainability, tier 3
A review of environmental impacts of generative AI and quantum computing, secondary synthesis with no primary data and no connection to organizational adoption or gender themes.
Companies & AIjournal
OpenAlex·25 February 2026·Stephen Goldsmith, J. Yang·Urban Governance, tier 3
Case-study piece on AI in urban governance stated in hedged language, 'AI may reshape,' 'may reposition,' with no clear empirical design behind the five proposed principles. Tier 3 and essentially an opinion piece dressed as case analysis.
Women & AIjournal
OpenAlex·24 February 2026·Patricia Bachiller, Emilio Martín Vallespín·Sustainability Accounting Management and Policy Journal, tier 2
Large Bank of Spain survey data show women underestimate their own financial knowledge relative to men, a confidence-gap pattern, but the subject is financial literacy, not technology or AI adoption, so it sits outside her two themes despite the structural similarity to the tech confidence gap.
Companies & AIjournal
OpenAlex·24 February 2026·Xi Luo, Jennifer Yee‐Shan Chang, Jun-Hwa Cheah, Weng Marc Lim, Xin‐Jean Lim·Internet Research, tier 2
Two-wave study of cyberchondria and health information seeking, unrelated to company AI adoption or women and AI.
Women & AIjournal
OpenAlex·24 February 2026·Retnoningrum Hidayah, Dhini Suryandari, Trisni Suryarini, Rita Rahayu, Ima Nur Kayati, Yuni Nur Fadhila, Indah Fajarini Sri Wahyuningrum, Arfi Fernando·Corporate Governance and Sustainability Review, tier 3
Indonesian corporate governance study linking board gender diversity and audit committees to enterprise risk management, with no connection to AI or technology adoption. Tier 3 and off-theme.
Companies & AIjournal
OpenAlex·23 February 2026·Stamer Tjorven, Machinek Nora, Steinhäuser Jost, Goujard Mathilde, Flägel Kristina·BMC Medical Education, tier 3
A scoping review of digital teaching methods for practical health-profession skills, with no data on organisational AI adoption or gender and AI. It does not fit her themes and is a review, not primary evidence.
Companies & AIjournal
OpenAlex·23 February 2026·Cătălin Beguni, Alin-Mihai Căilean, Eduard Zadobrischi, Sebastian-Andrei Avătămăniței, Alexandru Lavric, Florinel-Mădălin Stoian·Smart Cities, tier 3
A literature review of ride-hailing research topics with no primary data and no findings about companies adopting AI, individuals using it, or gender. Off-theme and evidence-free.
Companies & AIjournal
OpenAlex·23 February 2026·Thomas Schmitt, Nils Gegenmantel, Matías Urenda Moris, Pär Mårtensson, Kaveh Amouzgar·Journal of Manufacturing Systems, tier 3
A technical feasibility demonstration of LLM-driven simulation across 21 runs at one manufacturer, showing the framework works with human oversight. It is a tool capability study, not an adoption or organisational-behaviour finding.
Companies & AIjournal
OpenAlex·23 February 2026·Imad Antoine Ibrahim, Esmat Zaidan, Jon Truby, Thomas Hoppe·Technology in Society, tier 2
A doctrinal legal analysis of environmental provisions in the EU AI Act, with no primary data on companies adopting AI or on people using it. Off-theme policy analysis.
Companies & AIjournal
OpenAlex·23 February 2026·Kasyapp Ivaaturi·Universal Library of Innovative Research and Studies, tier 3
A conceptual synthesis of existing literature on leadership coaching and digital transformation success, not a primary study. Tier 3, no data of its own, reads as an argued position rather than evidence.
Companies & AIjournal
OpenAlex·23 February 2026·Francesco Veri, Nenad Stojanović·European Political Science, tier 3
A QCA study of institutional conditions for adopting deliberative minipublics like citizens' assemblies. It concerns democratic institutions, not AI adoption in companies or by individuals, and is off-theme.
Women & AIjournal
OpenAlex·22 February 2026·Monjurul Islam, Happy Kumar Das, Sumaiya Akter, Md. Delowar Hossain·Asia Pacific Journal of Education and Society, tier 3
A study of reading comprehension struggles among Bangladeshi secondary students has no connection to AI, gender and technology, or organisational adoption. Off-theme entirely.
Women & AIjournal
OpenAlex·21 February 2026·André Hajek, Andrew Stickley, Karl Peltzer, Supa Pengpid, Hans-Helmut König·Addictive Behaviors Reports, tier 3
A prevalence study of gaming disorder in the German adult population addresses technology-related psychosocial harm but not AI, adoption, or gender-and-AI dynamics specifically. Off-theme.
Companies & AIjournal
OpenAlex·20 February 2026·Bandar Alotaibi·Applied Sciences, tier 3
A review of IoT resilience strategies across hardware, network and governance layers has no connection to AI adoption in organisations or to gender and AI. Off-theme survey with no primary data of its own.
Women & AIjournal
OpenAlex·20 February 2026·Ronnel Victor Kilat·Frontiers in Education, tier 3
A PLS-SEM survey of 488 English-language teachers in Cebu extends UTAUT with perceived knowledge and privacy concerns, but it is a locally framed sample of a specific population, cross-sectional, tier 3, and largely reproduces predictor structures the library's UTAUT holdings already cover in depth.
Companies & AIjournal
OpenAlex·20 February 2026·Emmanuel Kwarteng-Amaniampong, Madele Tait·South African Journal of Economic and Management Sciences, tier 2
A cross-sectional SEM survey of 244 South African MSMEs finding that digital marketing integration improves customer experience and marketing performance is about e-commerce and marketing diffusion, not AI, and every hypothesis was confirmed with no surprising mechanism. It is also framed around a specific local population, which drops it further.
Women & AIjournal
OpenAlex·19 February 2026·Salman Khan, Sarah Webster, John Puxty, Madison Robertson·JMIR Aging, tier 3
A tier 3 scoping review of 22 mostly qualitative studies on digital literacy barriers in older Canadians, with no gender analysis and no causal design to trigger the tier 3 exception. It restates known barrier categories rather than adding a mechanism or number.
Women & AIjournal
OpenAlex·19 February 2026·Zeshan Ahmad, Ahmad Raza Bilal, Pierfelice Rosato, Raffaele Campo·Management Decision, tier 2
A survey of 329 Malaysian female descendant entrepreneurs on self-compassion and business succession contains no AI content at all, so it fails her core theme criterion regardless of its methodological quality.
Women & AIjournal
OpenAlex·19 February 2026·Yiping Chen, Yiping Chen, Xiang Li, Xiang Li, Yingyu Chen, Yingyu Chen, Wei Li·BMC Nursing, tier 3
A cross-sectional mediation study of 415 Chinese nursing students links AI literacy to academic resilience through self-efficacy and AI anxiety, echoing relationships the library already documents. Tier 3 venue, no causal design, and a narrow single-university population cap it.
Companies & AIjournal
OpenAlex·19 February 2026·Meet Hemant Parikh, Xiantao Fan, Jian-Xun Wang·Journal of Fluid Mechanics, tier 3
A computational fluid dynamics paper on generative modelling of turbulence has no connection to organisational AI adoption or women and AI.
Companies & AIjournal
OpenAlex·19 February 2026·David B. Olawade, Shamiul Bashir Plabon, Adeyinka Ojo, Muyiwa Ademola Ogunbona, Babajide David Makanjuola, Rosemary Olasilola·International Journal of Medical Informatics, tier 3
A narrative review of human-in-the-loop AI in healthcare synthesises existing literature with no new primary data and restates a human-oversight-improves-outcomes claim the library's radiologist studies already complicate. Tier 3 with no causal design.
Women & AIjournal
OpenAlex·18 February 2026·Fanni Kövesdi, Sabina Alkire·Social Indicators Research, tier 2
A review of household survey coverage for a global multidimensional poverty index is about poverty measurement infrastructure, not the digital gender divide or AI adoption, so it does not fit her themes despite being aimed at the divide section.
Women & AIjournal
OpenAlex·18 February 2026·Dave Brown, Usman Butt, Bilal Naqvi, Saber Farag·Information and Computer Security, tier 3
A systematic review of 62 studies on older adults' barriers to government digital services has no gender or AI focus, is tier 3, and offers no causal design or new mechanism beyond known barriers like anxiety and trust.
Companies & AIjournal
OpenAlex·18 February 2026·David B. Olawade, Saria Almarzook, Muyiwa Ademola Ogunbona, Babajide David Makanjuola, Olabanke Florence Olawuyi, Ojima Z. Wada·International Journal of Medical Informatics, tier 3
A narrative review of digital twin applications in disability healthcare has no bearing on company AI adoption or women and AI, and provides no primary data of its own.
Companies & AIjournal
OpenAlex·18 February 2026·Norazila Mat, Rosmah Mat Isa, Nur Atiqah Abdullah, Jamsari Alias·Architecture Image Studies, tier 3
A survey of 150 Malaysian public sector employees reproduces the library's existing five-dimension technostress finding and its negative link to performance almost exactly, adding nothing new, and is tier 3 with a locally framed sample.
Women & AIjournal
OpenAlex·18 February 2026·Manzoor H. Dar, Showkat A. Waza, Asma Majid, Pooja Trivedi, Najam W. Zaidi, Swati Srabani Nayak, Mosharraf Hossain, Sampath Kumar·Frontiers in Sustainable Food Systems, tier 3
A randomised trial on women's self-help groups scaling seed adoption in India, with real numbers on adoption and seed output, but it contains no AI content at all, so it fails her theme criterion regardless of its causal design.
Companies & AIjournal
OpenAlex·18 February 2026·Mahmoud Khaled Al-Kofahi, Badi Salem Rawashdeh, Faraj Salman Alfawareh, Hamza Alqudah·EDPACS, tier 3
A tier 3 survey of 107 Jordanian accounting-system users finds usefulness, ease of use, value, compatibility and threat drive resistance and usage intention, which only restates TAM constructs the library already holds, is framed around a local population, and carries no causal design to invoke the tier 3 exception.
Companies & AIjournal
OpenAlex·17 February 2026·Xue Jiang, Tong Weifeng, Mingquan Xue, Zitong Yuan, Jing Tong, Dawei Xu, Haiyang Li·Frontiers in Psychology, tier 3
A tier 3 UTAUT survey of 1,781 Chinese medical students on generative AI intention reproduces the standard performance expectancy and social influence effects the library already documents, is framed around a specific local population, and has no causal design.
Companies & AIjournal
OpenAlex·17 February 2026·Juan S. Izquierdo‐Condoy, Marlon Arias-Intriago, Laura Montero Corrales, Esteban Ortiz-Prado·JMIR Medical Education, tier 3
A tier 3 viewpoint article proposing a six-dimension FACETS framework for AI in medical education, with no primary data behind it.
Companies & AIjournal
OpenAlex·17 February 2026·Jansen N. Seheult, Jay R. Malone, Brian R. Jackson, Momin M. Malik, Mark Yazer·Vox Sanguinis, tier 3
A tier 3 narrative review proposing an ethics and oversight framework for AI in transfusion medicine, opinion and synthesis rather than primary evidence.
Companies & AIjournal
OpenAlex·17 February 2026·Shristi Kharola, Mangey Ram, Shivani Singh·Journal of Graphic Era University, tier 3
A reliability analysis of elevator repair policies has nothing to do with companies adopting AI, women and AI, or individual AI use, so it does not fit her themes at all.
Companies & AIjournal
OpenAlex·17 February 2026·Anders Giovanni Møller, Daniel M. Romero, David Jurgens, Luca Maria Aiello·Scientific Reports, tier 3
A randomised experiment with 680 US participants finds generative-AI writing aids raise social-media engagement but lower perceived authenticity and spill over negatively onto conversations. The causal design would normally rescue a tier 3 piece, but the topic is social-media discourse quality, not organisational AI adoption or an individual's professional use of AI, so it does not fit her themes.
Companies & AIjournal
OpenAlex·17 February 2026·Mariangeles Salas, Anand Singh, Carlos Pignataro, Lokendra Pal·Communications Materials, tier 3
A tier 3 review proposing an open-source AI infrastructure framework for materials science and manufacturing, with no primary adoption data and no connection to organisational AI adoption, women, or individual professional use.
Women & AIjournal
OpenAlex·16 February 2026·Amr Mahmoud Mohamed, Abdul Qader Emran, Abbas Hussein Abdelrady, Abdul Aziz Mohamed Mohamed Ali El Deen·Frontiers in Education, tier 3
A tier 3 survey of 304 gifted Saudi EFL students finds GenAI anxiety mediates the gifted-behavior to motivation link and the effect is stronger for women, but it is framed around a narrow local population, uses no causal design, and mostly confirms the library's existing finding that women report higher AI anxiety.
Companies & AIjournal
OpenAlex·16 February 2026·Husein Osman Abdullahi, Murni Mahmud, Elin Eliana Abdul Rahim·Cogent Food & Agriculture, tier 3
A tier 3 UTAUT survey of 349 Somali farmers finds performance expectancy, ease of use, trust and perceived risk predict mobile-technology adoption while social influence does not. It concerns general mobile technology rather than AI, is framed around a specific local population, and adds no new mechanism.
Companies & AIjournal
OpenAlex·16 February 2026·Giovanna Bagnato, Cristina Caterina Amitrano, Chiara Giachino, Augusto Bargoni·Management Decision, tier 2
A tier 2 non-systematic critical review proposing a twelve-dimension framework for disability-inclusive technology acceptance using VR as an example, but it is conceptual with no primary data and is not centred on AI, companies, or women.
Women & AIjournal
OpenAlex·16 February 2026·Vivian Hui, Lidan Tian, Malavika Eby, Bohan Zhang, Rose E. Constantino·Frontiers in Psychology, tier 3
A qualitative content analysis of website links shared in an IPV subreddit. It contains no AI content and no adoption or gender-and-technology mechanism, so it does not fit her themes despite the female population.
Companies & AIjournal
OpenAlex·16 February 2026·Rachana Jaiswal, Shashank Gupta, Po-Ju Chen·International Journal of Contemporary Hospitality Management, tier 3
A PRISMA-guided conceptual review building a framework of antecedents and outcomes for GenAI personalization in hospitality. It is a synthesis with no primary data and a tier 3 venue, so it cannot carry a read beyond noting the field exists.
Companies & AIjournal
OpenAlex·16 February 2026·Peter A. Cotton, Debby R. E. Cotton·Journal of Biological Education, tier 3
A narrative review of AI tools in biology education listing potential benefits and challenges. No primary data, no number or mechanism, tier 3 venue.
Companies & AIjournal
OpenAlex·16 February 2026·Toni Lorente, Kathrin Gardhouse·Internet Policy Review, tier 2
A legal argument that ChatGPT should be classified as a hybrid search-engine-and-platform under the DSA. It is doctrinal analysis, not empirical evidence about adoption, and adds no mechanism or number relevant to her themes.
Companies & AIjournal
OpenAlex·15 February 2026·Jia Li Duan, Goh Chin Fei, Tan Owee Kowang, Azmirul Ashaari, Halimah Mohd Yusof·International Journal of Academic Research in Business and Social Sciences, tier 3
A narrative review of TAM, TRA and TPB across 2021 to 2025 studies. It only restates that extended models trade predictive power for theoretical coherence, which the library already documents extensively, and it is a review with no primary data in a tier 3 venue.
Companies & AIjournal
OpenAlex·15 February 2026·Carlos Alberto Rosas-Jiménez, Cynthia Lokker, Bonny Ibhawoh, Lisa Schwartz·Discover Public Health, tier 3
A narrative review proposing six requirements for optimal reliance on ChatGPT in health policy. No primary data, no number, tier 3 venue, and TAM-based overreliance claims already sit in the library.
Companies & AIjournal
OpenAlex·15 February 2026·Kien A. Vu·Water Science & Technology, tier 3
A review of plastics as vectors for pathogens in water systems. It has no connection to AI adoption, companies, or women and AI.
Companies & AIjournal
OpenAlex·14 February 2026·Claudia Ciceri, Federico Caniato, Antonella Moretto·International Journal of Physical Distribution & Logistics Management, tier 3
Three embedded case studies of cybersecurity vendors mapping AI capabilities onto supply chain cyber risk phases. It is qualitative and framework-building with no adoption mechanism or number, tier 3 venue.
Companies & AIjournal
OpenAlex·14 February 2026·Homa Molavi, Fariborz Rahimnia, Lihong Zhang·Financial Innovation, tier 2
An SEM survey on Iranian traders finding strategic planning drives FinTech acceptance and advisory quality, mediated by acceptance and moderated by servant leadership. The finding is framed around a specific Iranian trading population and a specific market crisis rather than a general mechanism, which drops it a level, and its fit to her AI themes is thin.
Companies & AIjournal
OpenAlex·13 February 2026·Raghad Baker Sadiq, Nur Fazidah Elias, Hazura Mohamed·Journal of information and organizational sciences, tier 3
A review of 36 studies applying Meta-UTAUT, concluding attitude is a strong determinant of intention and behavior. This restates findings the library already holds about attitude's centrality and UTAUT's construct proliferation, with no primary data of its own, tier 3 venue.
Companies & AIjournal
OpenAlex·13 February 2026·Abeer F. Alkhwaldi, Sultan Hammad Alshammarı·International Journal of Information and Communication Technology Education, tier 3
A survey of Jordanian academics on VR adoption using UTAUT plus protection motivation theory. It is a locally framed sample and the findings largely restate standard UTAUT predictors already in the library, tier 3 venue.
Companies & AIjournal
OpenAlex·13 February 2026·Heeyoon Ko·Journal of Intelligence, tier 3
A PLS-SEM survey of 432 undergraduates linking digital learning competence to academic achievement through informal digital learning, moderated by self-regulation. It is about general digital learning skill rather than AI adoption or gender, and is a cross-sectional survey in a tier 3 venue.
Companies & AIjournal
OpenAlex·13 February 2026·Eleni G. Mantouka, Katerina Vakrinou, Konstantinos N. Christidis, Babis Magoutas, Akrivi Kiousi, Eleni I. Vlahogianni·Sensors, tier 3
A review of operational and infrastructure challenges for automated vehicle traffic systems. It has no connection to AI adoption in organizations or to women and AI, and is a review with no primary data.
Companies & AIjournal
OpenAlex·13 February 2026·Petar Radanliev, Omar Santos, Carsten Maple·Frontiers in Artificial Intelligence, tier 3
A systematic-review and framework paper on adversarial robustness in agentic AI security, not on organisational adoption, gender, or an individual's use of AI. Tier 3 venue, no primary experiment and no fit to her themes, so it fails on relevance alone.
Companies & AIjournal
OpenAlex·13 February 2026·Mohamed Mohiya·Kybernetes, tier 2
Qualitative interviews and document analysis identify organisational support factors, responsiveness, feedback, recognition, that make enterprise social networking succeed, but the technology studied is not AI. It overlaps with what the employee-layer library already holds on recognition and purpose, and its non-AI focus fails her theme fit.
Companies & AIjournal
OpenAlex·12 February 2026·Jingke Li, Yongkang Wang, Joongoo Han·Frontiers in Psychology, tier 3
A two-wave survey of 352 Chinese employees finds digital leadership raises engagement via digital self-efficacy, and technostress weakens that path. Tier 3 venue with a time-lagged survey design, not a qualifying causal design, and the finding is framed around a Chinese employee sample rather than a general mechanism, so it stays low.
Companies & AIjournal
OpenAlex·12 February 2026·Wenxiang Yang, Li Tang, Guanyu Zhang·Discover Computing, tier 3
A technical engineering paper on generative AI for power-grid data-quality rule generation, with no organisational, gender, or individual-adoption content, fails her theme fit entirely.
Companies & AIjournal
OpenAlex·12 February 2026·Donia Arafa, Julia van de Korput, Philipp N. Braaker, Kieran Higgins, Niels R. C. Meijns, Katy L. H. Marshall-Phelps, Julia Meng, Daniel Soong·Science, tier 1
A neuroscience paper on myelin remodelling after demyelination, unrelated to AI adoption or gender themes, appears to be a misfiled search result.
Companies & AIjournal
OpenAlex·11 February 2026·Ninggui Duan, Lina Li, Guangbo Lin, Hao Chen·Scientific Reports, tier 3
A cross-sectional SEM on 315 Chinese college students finds AI anxiety lowers career decisions mostly by reducing career adaptability, accounting for 63% of the effect, with self-efficacy failing to buffer it. Tier 3 venue, no causal design, and the finding is framed around a Chinese student sample rather than a workplace population.
Companies & AIjournal
OpenAlex·11 February 2026·Lucy Osler·Philosophy & Technology, tier 2
A philosophical argument piece on distributed cognition and AI-induced psychosis, with no primary data and no organisational or gendered-adoption angle, falls outside her themes despite being conceptually interesting.
Companies & AIjournal
OpenAlex·11 February 2026·Cong Shu, Kaisheng Lai, Lingnan He·Frontiers in Psychology, tier 3
A conceptual paper proposing a three-stage model of human-AI emotional attachment, with no empirical data collected, tier 3 venue, and no connection to organisational adoption or gendered AI use.
Companies & AIjournal
OpenAlex·11 February 2026·Hector Zenil, Jesper Tegner, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa Soldatova·Frontiers in Artificial Intelligence, tier 3
A perspective piece arguing for graded autonomy in AI-conducted science, opinion writing with no primary data, concerned with scientific discovery rather than organisational AI adoption or individual work practices.
Companies & AIjournal
OpenAlex·10 February 2026·Duong Huu Tong, Hoang Thi Nguyen, Tien-Trung Nguyen, Trinh Le, Xuan Mai Vo, Le Viet Minh Triet, Tăng Minh Dũng·Contemporary Educational Technology, tier 3
A survey of 422 Vietnamese secondary teachers finds self-efficacy and peer or student norms shape ICT beliefs more than institutional support. The technology is general ICT rather than AI, the finding is framed around a Vietnamese teacher population, and it mostly reconfirms self-efficacy and subjective-norm mechanisms already deep in the library.
Companies & AIjournal
OpenAlex·9 February 2026·Hong Zhang, Shuang Liang, Lin Wu, Yixin Wang, Lan Luo, Bin Peng, Xue Xiong, Liyu Chen·Frontiers in Public Health, tier 3
Ethnographic study of digital health usage among rural Chinese elders, tier 3 venue, qualitative with no causal design, and framed explicitly around a local population rather than a general mechanism. It also sits outside her companies or women and AI focus.
Companies & AIjournal
OpenAlex·9 February 2026·Steven Lee Mwaseba, Emmanuel Simon Mwang’onda, Winnie Robi Donald·Cogent Economics & Finance, tier 3
A Tanzania mobile money study explaining a rural urban ownership gap through financial literacy. It is about financial inclusion, not AI, and the finding is framed around a specific national population, tier 3 venue with no causal design.
Women & AIjournal
OpenAlex·9 February 2026·Ning Zhu, Aleksandra Gaweł, Timo Toikko·Journal of Family and Economic Issues, tier 2
Panel data across 27 EU countries links motherhood timing to the gender pay gap. Solid data and tier 2 venue, but there is no AI or technology content anywhere in the finding, so it does not fit either of her themes.
Companies & AIjournal
OpenAlex·9 February 2026·K. Ann Renninger, Lux K. Barton, G Hontoria Bautista, Mary Garcia-Barrios, Iyinoluwa Ogunyinka, Kathryn Riley·Educational Psychology Review, tier 3
A literature review plus a small pilot with Black middle schoolers on interest, self efficacy and belonging in classroom learning. No technology or AI is involved, and the venue is tier 3, so it sits outside her research focus.
Women & AIjournal
OpenAlex·9 February 2026·Mariana Pinho, Enrickson Varsori·Sexuality & Culture, tier 3
A Portuguese national sample of 3,300 finds women report higher trait and state anxiety and negative affect than men, mediated interactions with life satisfaction. This is general mental health research with no AI or technology framing, and the venue is tier 3.
Companies & AIjournal
OpenAlex·9 February 2026·Sheng Wang, Noor Fatima, Muhammad Shahbaz, Muhammad Asif·Scientific Reports, tier 3
Qualitative interviews with 28 chatbot users in Pakistan and China identify the same cognitive versus affective trust split the library already holds. Tier 3 venue, no causal design, and the study frames its contribution explicitly as insight into a developing market population rather than a general mechanism.
Companies & AIjournal
OpenAlex·9 February 2026·Weicheng Gu·PLoS ONE, tier 3
A correlational PLS SEM survey of 453 sports undergraduates finds GenAI dependence raises creativity via self efficacy, with a gender moderated effect stronger for men. No causal design, tier 3 venue, and a population specific sample of one academic major keep it out of the must read tier.
Companies & AIjournal
OpenAlex·8 February 2026·Lubna Farhan Ali, S. K. Asim Ali·IARS International Research Journal, tier 3
A small mixed methods case study of 135 surveyed and 15 interviewed underprivileged youth in Karachi links digital literacy to lifelong learning tendencies. Tier 3 venue, correlational, no AI content, and framed around one local learning center.
Companies & AIjournal
OpenAlex·7 February 2026·Christopher David Burr, Shuang Qian, Peter Winter, Tim Chico, Camila Rangel Smith, David Wagg, S A Niederer·AI & Society, tier 2
A thematic literature review of ethical, legal and social issues for healthcare digital twins, mapped onto the NASSS framework. It is a synthesis with no primary data, and its subject, healthcare digital twins, sits outside her companies or women and AI themes.
Companies & AIjournal
OpenAlex·7 February 2026·Gianvincenzo Zuccotti, Valeria Calcaterra, Gabriele Infante, Martina Pisarra, Gianluca Damonte, Alberto Passi, Marcello Maggiolini, Fabio Ferretti·BMC Medical Education, tier 3
A cross sectional survey of 438 Italian medical students and residents finds technology enthusiasm and smartphone confidence predict telemedicine readiness. Tier 3 venue, framed around a specific national training population, and not about companies adopting AI or women and AI.
Companies & AIjournal
OpenAlex·7 February 2026·Martin Obschonka, Moren Lévesque·Small Business Economics, tier 2
Survey of 172 entrepreneurship scholars finds AI-based studies suffer a measurable trust discount versus conventional-method studies, framed through a market-for-lemons lens, but this is about researchers judging academic AI methods, not about organizations adopting AI, women's AI use, or an individual deploying AI at work.pdf
Companies & AIjournal
OpenAlex·7 February 2026·Liangfei Qiu·Artificial Intelligence Machine Learning & Robotics in Business, tier 3
Tier 3 venue, a conceptual research-agenda essay synthesizing prior work on social technologies and AI with no primary data collected. It is also tangential to her themes, being about social media and market design broadly rather than organizational AI adoption.
Companies & AIjournal
OpenAlex·7 February 2026·Nina Rizun, Ovidiu Niculae Bordean, Anastasija Nikiforova, Ioana Natalia Beleiu, Aleksandra Revina·Computers and Education Open, tier 3
Survey of 344 students across four named European countries testing a TAM/UTAUT/TPB/FATE model finds explainability and privacy predict trust in ChatGPT, and trust flows through perceived performance rather than intention. This elaborates paths the library already holds, the venue is tier 3 with no causal design, and the framing names a specific four-country population.
Companies & AIjournal
OpenAlex·6 February 2026·Guangxiang Liu, Md Kamal Hossain·Journal of Computer Assisted Learning, tier 3
Cross-sectional survey of 508 rural Bangladeshi students finds self-efficacy and L2-self variables predict AI-mediated informal English learning. Tier 3 venue, correlational design, and the finding is framed about a specific local population, so no exception applies.
Companies & AIjournal
OpenAlex·6 February 2026·Jiachang Li, Hanqi Song, Yufei Ma·Scientific Reports, tier 3
A panel study of Chinese manufacturing firms 2011 to 2024 with instrumental-variable checks finds digital transformation improves supply chain resilience via financing and competition channels, but this is about corporate digitization broadly, not AI adoption specifically, and the claim is framed around Chinese manufacturing listed firms rather than a portable mechanism.
Companies & AIjournal
OpenAlex·6 February 2026·Boumediene Hamzi·Philosophies, tier 3
A philosophical essay reading AI's data-centric worldview through Islamic metaphysics and Heidegger. Pure opinion with no empirical claim and no real fit to organizational adoption or women and AI.
Companies & AIjournal
OpenAlex·6 February 2026·Argyro Kavadella, Sergio E. Uribe, Marco Antônio Dias da Silva, Prof Dr Falk Schwendicke, Antonín Tichý, Reinhilde Jacobs, Daniel Karni, Akhilanand Chaurasia·BMC Medical Education, tier 3
Descriptive multinational survey of dental students' AI knowledge and attitudes, tier 3, no mechanism relevant to organizational adoption or gendered AI use, just percentages of self-reported familiarity and support for AI education.
Companies & AIjournal
OpenAlex·6 February 2026·Ramteja Sajja, Yusuf Sermet, Brian Fodale, İbrahim Demir·Scientific Reports, tier 3
Small mixed-methods evaluation of one university's AI tutoring tool across two courses (71 students), tier 3, descriptive findings about usability and ethical uncertainty with no generalizable mechanism.
Companies & AIjournal
OpenAlex·6 February 2026·Beverley Cherie Millar, Mary J. Cates, Marco Torrisi, Amanda J. Round, Aisling Warde, Colm J. Lowery, John E. Moore·British Journal of Biomedical Science, tier 3
A narrative review of antimicrobial-resistance therapeutics with no connection whatsoever to AI adoption, women and AI, or individual AI use.
Women & AIjournal
OpenAlex·5 February 2026·Mokgata Alleen Matjie, Andani Nethavhani, Mary Matlakala·Frontiers in Computer Science, tier 3
A narrative and comparative review of case studies arguing AI widens the education digital divide through language, culture and algorithmic bias. Tier 3, no primary data collected, purely a synthesis with policy proposals.
Women & AIjournal
OpenAlex·5 February 2026·Julianna Paola Ramirez-Lozano, May Portuguez Castro·Discover Sustainability, tier 3
Qualitative focus-group study (six groups) of a Peruvian university training program for women microentrepreneurs identifies two digital-adoption profiles and named barriers. Tier 3, no causal design, and the finding is framed about a specific local population.
Companies & AIjournal
OpenAlex·5 February 2026·Salma M. Abdalla, Bernard Banda, Madison Pickerel, Sam B. Rosenberg, Swati Sharma, Sandro Galea·Social Psychiatry and Psychiatric Epidemiology, tier 3
An eight-country survey linking loneliness to depression and anxiety has no AI content at all and does not address organizational adoption, women and AI, or individual AI deployment.
Companies & AIjournal
OpenAlex·5 February 2026·Xiao Zheng Xie, Lawrence Jun Zhang, Xing Xu·European Journal of Education, tier 3
Tier 3 venue with no causal design named, only a qualitative thematic analysis of interviews with university English teachers. It maps ethical principles to emotion categories but yields no number or generalizable mechanism, and confirms what the library already holds about emotion shaping tech engagement.
Companies & AIjournal
OpenAlex·5 February 2026·Dong Feng·Chaos Solitons & Fractals, tier 3
This is a stochastic-volatility mathematics paper about bistable oscillator switching risk. It has no connection to organizational AI adoption or gender and AI, so it fails the fit test entirely.
Companies & AIjournal
OpenAlex·5 February 2026·Song Liu, Jian Li, Yazhi Lin, Dennis Z. Yu, Y. Peng, Yi Liu, Xianting Ma·Symmetry, tier 3
A hazardous-materials logistics optimization model using CVaR and an ant colony algorithm. It has no bearing on AI adoption in organizations or on women and AI.
Companies & AIjournal
OpenAlex·5 February 2026·Barış Armutcu·Carbon Balance and Management, tier 3
A tier 3 correlational SEM-ANN survey (n=609) on AI marketing's effect on Gen Z green purchasing via brand trust and preference. It is about consumer marketing effects, not organizational AI adoption or workforce dynamics, and carries no causal design.
Companies & AIjournal
OpenAlex·5 February 2026·Hong Cai, Dongxia Wang, Yiqun Zhao, Chunhui Yang·Biosensors, tier 3
A review of microfluidic lab-on-a-chip diagnostics with AI integration mentioned in passing. It is a biosensor/laboratory medicine review with no connection to organizational AI adoption or gender and AI.
Companies & AIjournal
OpenAlex·4 February 2026·Mori W. Gouroubera, Morrisson Gouthon, Alcade C. Segnon, Faridah Dosso, Quentin Fiacre Togbévi, Ismail Moumouni-Moussa, Robert B. Zougmoré·Frontiers in Sustainable Food Systems, tier 3
A tier 3 meta-analytic SEM across 33 farmer studies finding perceived ease of use is a weak predictor of intention while usefulness dominates. The finding is solid but concerns agricultural technology acceptance among farmers, a population-framed result outside her core themes of company AI adoption or women and AI, and no causal design is present.
Companies & AIjournal
OpenAlex·4 February 2026·Isyaku Salisu, Mohammad Mulayh Alshammari, Nezar Mohammed Al‐Samhi·Frontiers in Education, tier 3
A tier 3 cross-sectional survey of Saudi computer-science graduates linking career programs to employability via self-efficacy and resilience. It has no AI-adoption content and is a locally framed population study (Hail, Saudi Arabia) with no causal design.
Companies & AIjournal
OpenAlex·4 February 2026·Furkan Ozbey, Büşra Yılmaz, Birkan Eyup Yilmaz·Acta Odontologica Scandinavica, tier 3
A tier 3 descriptive cross-sectional survey of 257 Turkish dentists on awareness of AI data security and ethics, with only mean-score comparisons and no mechanism. It is a locally framed population study with no causal design and weak fit to her adoption or gender themes.
Women & AIjournal
OpenAlex·3 February 2026·Soniya Ningombam, Abhishek Das, Ranjitha Puskur, Shalander Kumar·Regional Environmental Change, tier 3
A PRISMA review of 162 studies on gendered climate risk perception among farmers. It contains no AI content whatsoever, so despite the gender framing it does not serve her AI-focused themes.
Women & AIjournal
OpenAlex·3 February 2026·Shen Chen, Braulio M. Girela-Serrano, Martina Di Simplicio, Alexander Spiers, Iroise Dumontheil, Michael S. C. Thomas, Martin Röösli, Paul Elliott·BMC Medicine, tier 3
A longitudinal cohort study (SCAMP, n=2350) finding heavy social-network use predicts later depressive and anxiety symptoms in adolescents, with the association stronger in girls for total and weekend use. It concerns social media and adolescent mental health rather than AI adoption or workplace AI, so it falls outside her themes despite the gender detail.
Companies & AIjournal
OpenAlex·2 February 2026·Yosefa Birati, Roy Tzemah-Shahar·Journal of Medical Internet Research, tier 3
A scoping review of 17 studies mapping older adults' resistance to digital health tools onto innovation resistance theory categories. It is a synthesis with no causal design, sits in a tier 3 venue, and its focus on general digital health use in older adults is only loosely tied to her AI adoption themes.
Women & AIjournal
OpenAlex·2 February 2026·Lawrence N. Kazembe, Ndeyapo Nickanor, Jonathan Crush, Halima Ahmed·Sustainability, tier 3
A survey of 470 informal food traders in Windhoek finds women's adoption of digital payment and pricing tools is driven by education and startup capital while men's is driven by vendor type and financing. The finding is framed around this specific Namibian population rather than a general mechanism, and the venue is tier 3 with no causal design, so it drops to low.
Companies & AIjournal
OpenAlex·2 February 2026·Kamila Radlińska·Sustainability, tier 3
Eurostat data show only 31% of EU agricultural workers have basic digital skills and that better internet access correlates with reduced exclusion but not with higher-level skills. The claim is framed as being about EU farmers specifically, the venue is tier 3, and there is no causal design to invoke the exception.
Companies & AIjournal
OpenAlex·2 February 2026·Suhada Suhada, Novi Diah Wulandari, Fahmi Akbar Idries, Nurna Pratiwi, Ibra Oktariantra, Adinda Octa Romandhani, Ananda Riyadho·Asian Management and Business Review, tier 3
A PLS-SEM survey of 200 Yogyakarta youth finds digital self-efficacy fully mediates the link between digital skills and work readiness, with government support having no moderating effect. The sample is explicitly local, the venue is tier 3, and the mediation-by-self-efficacy finding is already well established in the library.
Companies & AIjournal
OpenAlex·2 February 2026·Miao Zhao, Dongli Rong, Ling Chen, Shuzhen Cai, Yongcheng Lu, Jingsha Dai, Youxiong Zhang, Xianhu Wei·Microorganisms, tier 3
A microbiology review of phage and probiotic therapy against drug-resistant Staphylococcus aureus. It has no connection to AI adoption, organisations, or gender and technology, and is a review with no primary data relevant to her themes.
Companies & AIjournal
OpenAlex·2 February 2026·Stavros Athanassopoulos, Aggeliki Tzavara, Spyridon Aravantinos, Konstantinos Lavidas, Vassilis Komis, Stamatios Papadakis·Education Sciences, tier 3
A mixed-methods survey of 314 teacher-education students describes common GenAI uses and concerns like over-reliance and reduced critical thinking. It is descriptive with no causal design, in a tier 3 venue, and adds no new mechanism beyond what is already documented about student AI use and concerns.
Companies & AIjournal
OpenAlex·2 February 2026·Ali Ayoub·Processes, tier 3
A review of AI applications across the food processing value chain citing accuracy and cost figures from other sources. It is a narrative review with no primary data of its own, in a tier 3 venue, and reads as a technology round-up rather than adoption research.
Companies & AIjournal
OpenAlex·2 February 2026·Rami T. Y. Ismail, Almula Umay Karamanlıoğlu·Sustainability, tier 3
A PLS-SEM survey of 350 Malaysian SME owners finds AI capability raises innovation partly through transformational leadership, with digital culture moderating some but not all paths. The claim is framed around Malaysian SMEs specifically, the venue is tier 3, and there is no causal design to invoke the exception.
Companies & AIjournal
OpenAlex·1 February 2026·Yulong Cai·Digital Health, tier 3
A survey of 2,265 respondents finds digital access improves health outcomes not through information seeking but that socioeconomic status moderates who benefits from that access. This is about health equity and digital access generally, not AI adoption or gender and AI specifically, and sits in a tier 3 venue with a moderation design that is not a qualifying causal design.
Companies & AIjournal
OpenAlex·1 February 2026·Mohd Arif Hussain, Md Arshad Ur Rahman, Mohammed Ashfaq Hussain, Kasturi Bangla Vanitha, Prakash Kumar, Amrutha Kuril·International Review of Management and Marketing, tier 2
A survey of 380 Hyderabad bank customers finds satisfaction fully mediates AI-TAM factors and loyalty, with age but not gender moderating the relationship. This confirms the library's extensive TAM findings, is framed around a specific Indian city population which drops it a level, and carries no causal design.
Women & AIjournal
OpenAlex·1 February 2026·Nora I. Strom, Brad Verhulst, Silviu‐Alin Bacanu, Rosa Cheesman, Kirstin L. Purves, Hüseyin Gedik, Brittany L. Mitchell, Alex S F Kwong·Nature Genetics, tier 3
This is a genetics study of anxiety disorder risk loci and GABAergic signaling. It has no connection to technology, AI adoption, or workplace behavior, it belongs to a different field entirely and adds nothing to her themes.
Companies & AIjournal
OpenAlex·1 February 2026·Chika Judith Abolle-Okoyeagu, Chinedu Pascal Ezenkwu, Ebuka Ibeke, Ojotule Paul Onoja, Victor Ugochukwu Ezeonwumelu·Cogent Education, tier 3
A TAM survey of engineering students finds usefulness and ease of use predict AI adoption intention while attitude does not, which is a well-worn TAM result already covered extensively in the library. Tier 3 venue, cross-sectional survey, no causal design, and no new mechanism.
Companies & AIjournal
OpenAlex·1 February 2026·Magnus Liebherr, Ellen Enkel, Effie L-C. Law, Mohammad Reza Mousavi, Matteo Sammartino, Philipp Maximilian Sieberg·International Journal on Software Tools for Technology Transfer, tier 3
A conceptual review defining trust, trustworthiness and calibrated trust with no primary data collected. The library already holds calibrated-trust as a concept, so this adds no number or mechanism, and it is opinion-level synthesis from a tier 3 venue.
Companies & AIjournal
OpenAlex·1 February 2026·Emilio Ferrara·Future Internet, tier 3
An opinion and taxonomy essay on generative AI's erosion of shared epistemic ground, with no primary data or empirical test. It sits outside her adoption and gender themes and cannot pass the primary-evidence bar from a tier 3 venue.
Companies & AIjournal
OpenAlex·1 February 2026·Mohammad Hadra, Karleen Cambridge, Mostefa Mesbah·International Journal for Educational Integrity, tier 3
An empirical comparison of two AI content detectors' accuracy on student writing, useful for academic integrity questions but unrelated to organizational AI adoption or gender and AI, so it does not fit her themes.
Companies & AIjournal
OpenAlex·1 February 2026·Ignacio Monedero-Recuero, Xiangxu Wei, Fabienne Jouberton, Raquel Duarte, María Rodríguez-Ortega, Mary Rosary T. Santiago, Adekola Oyedokun Adekunle, Paul Daru·BMJ Global Health, tier 3
A scoping review of drug-resistant tuberculosis care in war zones has no AI or technology content whatsoever and does not touch her themes.
Companies & AIjournal
OpenAlex·1 February 2026·Abdullah Al Sakib, SM. Masfequier Rahman Swapno, Fahim Ahamed, Arafath Bin Mohiuddin, Md Imranul Hoque Bhuiyan, Shakil Khan, Katura Gania Khushbu, Rezaul Haque·Digital Health, tier 3
A deep-learning skin cancer classifier study with no connection to organizational AI adoption or gender, purely a clinical diagnostic tool paper.
Women & AIjournal
OpenAlex·31 January 2026·Subhasis Bera, Ishita Bera, Dil Rahut·Humanities and Social Sciences Communications, tier 3
A UTAUT-MIMIC survey of 305 urban Indian Gen Z and millennial respondents finds gender negatively moderates AI adoption, echoing the adoption-gap finding the library already holds in far larger and more varied datasets. It is a small local sample in a tier 3 venue with no causal design, so it cannot move above confirmatory status.
Companies & AIjournal
OpenAlex·31 January 2026·Emine Can Yurt, Asuman Seda Saracaloğlu·Kastamonu Eğitim Dergisi, tier 3
A study of Turkish teachers' curriculum literacy self-efficacy and cognitive flexibility has no AI or technology adoption content and does not fit either of her themes.
Companies & AIjournal
OpenAlex·31 January 2026·Ronald Hayes, Darrell Norman Burrell·Public Governance Regulation and Law, tier 3
A qualitative narrative inquiry with 12 subject matter experts on trust in automated decision-making offers interpretive themes on transparency and accountability but no primary quantitative evidence or causal design, and sits in a tier 3 venue.
Companies & AIjournal
OpenAlex·31 January 2026·Ronald Hayes·Safety and Security Advances, tier 3
A literature-driven qualitative synthesis on trust in healthcare automation, not an empirical study with new data, and it lands in a tier 3 venue with no causal design to invoke the exception.
Companies & AIbusiness
IBM·8 January 2026·tier 2
Based on conversations with only 14 organisations and framed as a revenue breakout narrative, this is thin, promotional case commentary rather than primary data.
Companies & AIbusiness
Harvard Business Review·tier 1
This is a summary of a subscriber roundtable discussion with no reported findings, numbers or study design, just a list of questions the panel intended to address.
Companies & AIbusiness
Harvard Business Review·tier 1
A single-company anecdote from an IBM executive about tripling entry-level hires, with no study design or data beyond the interview quote.
Companies & AIbusiness
Harvard Business Review·tier 1
An opinion piece recommending redesigning entry-level roles around AI, with no primary data or study cited in the opening.
Companies & AIbusiness
Harvard Business Review·tier 1
An event announcement for the same subscriber roundtable as another candidate, with no findings reported, only the list of questions to be discussed.
Companies & AIbusiness
Harvard Business Review·tier 1
This is a newsletter teaser pointing to other content, not a research summary. There is no data, mechanism or finding to evaluate.
Companies & AIbusiness
BCG·tier 2
A macro strategy essay on capital reallocation and shifting value pools across industries, with market figures but no study of organizational or employee-level AI adoption. It reads as consultant opinion about market structure, not primary evidence on her themes.
Companies & AIbusiness
BCG·tier 2
Vendor marketing copy for BCG's AI consulting services, restating the familiar 10/20/70 split with no new data or mechanism.
Companies & AIbusiness
BCG·tier 2
A generic vendor capability page describing generative AI's potential, with no primary data or specific finding.
Companies & AIbusiness
BCG·tier 2
A market-sizing report on agentic AI's $200 billion opportunity for tech service providers, framed around vendor economics rather than organizational or psychological adoption mechanisms relevant to her themes.
Women & AIbusiness
BCG·tier 2
An India-specific BCG report on GenAI and gender gaps in tech leadership, framed around a local population rather than a general mechanism, and dated outside the twelve-month window for business pieces. It also largely restates gender-adoption-gap findings the library already holds in more numerous and more recent forms.
Women & AIbusiness
BCG·tier 2
The article's opening could not be fetched, so only a title claiming women leaders outpace men in generative AI adoption is available. A title alone carries no mechanism or number to weigh, so it cannot support any higher rating.
Women & AIbusiness
BCG·tier 2
Title-only duplicate of the same 2019 BCG gender-diversity report as another candidate. No opening could be fetched, so there is no number or mechanism to weigh, and it cannot clear even a medium bar.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Women & AIbusiness
BCG·tier 2
A thin 2023 opinion piece framed around Denmark's AI market position, recycling a 2019 BCG or MIT executive-survey statistic rather than presenting new primary evidence. No mechanism or number of its own is offered.
Women & AIbusiness
BCG·tier 2
The page 404'd, so only a title and a one-line snippet remain. Per the opening rule that cannot carry any tier above low.
Companies & AIbusiness
BCG·tier 2
PDF slideshow version of the same 2026 BCG survey, title-only with no opening fetched, so there is no evidence to weigh beyond the title.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
BCG·tier 2
PDF duplicate of the modelling report above, title-only with no opening fetched, so it cannot be judged on any evidence.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
BCG·tier 2
A promotional piece for BCG X's 'Frontline Ops AI' product built around four vendor use-cases, citing only one incidental figure from a separate 1,000-person survey on joy and attrition. It functions as a tool round-up, not primary adoption research.
Companies & AIbusiness
BCG·tier 2
An evergreen capability-page overview recycling the 2023 survey's numbers and restating the already-catalogued 10-20-70 rule. It offers no new primary evidence and reads as marketing copy rather than research.
Women & AIbusiness
Deloitte Insights·tier 2
Only a title and one-line snippet could be fetched, dated June 2024, so there is no mechanism or number to weigh, and the topic is already thoroughly covered in the library's adoption-gap section.
Open the article →Judged on the title alone: only 58 characters of readable text, which is a teaser or a paywall rather than an opening
Companies & AIbusiness
Deloitte Insights·tier 2
The fetched opening is generic marketing language about generative AI's potential with no data, number, or study design behind any claim.
Companies & AIbusiness
Deloitte Insights·tier 2
An anecdote about an AI running a vending machine and a single unattributed survey stat (36% of managers expect to manage digital agents) frame a forthcoming Deloitte research programme, not a finished finding; there is no mechanism or dataset to evaluate yet.
Companies & AIbusiness
Deloitte Insights·tier 2
This is a predictions roundup for 2026 built on citations to news articles and other Deloitte pieces, with no primary data or measured effect of its own.
Companies & AIbusiness
Deloitte Insights·tier 2
The stats cited (37% deployment, spending to top $79 billion by 2022) date this piece to roughly 2018, far outside the twelve-month window for business pieces.
Companies & AIbusiness
Deloitte Insights·tier 2
A landing page of links to reports, case studies, and press mentions; it is a promotional index with no primary data of its own.
Companies & AIbusiness
Deloitte Insights·tier 2
A forecasting essay about TMT's economic weight and AI scaling narrative, entirely opinion and macro commentary with no primary study or measured effect.
Companies & AIbusiness
Deloitte Insights·tier 2
A conference recap describing panel discussions and speaker names, with no data, number, or study design.
Companies & AIbusiness
Deloitte Insights·tier 2
A system dynamics simulation comparing two hypothetical S&P 500-style organizations; this is modeled speculation, not empirical evidence of what actually happens in firms.
Companies & AIbusiness
IBM·tier 2
A forward-looking opinion piece about corporate venture capital and startup partnerships in 2026, with no primary data or measured finding.
Companies & AIbusiness
IBM·tier 2
A marketing-heavy conference recap promoting IBM's Bob product, citing an unspecified survey stat (70% say governance is slowing transformation) without methodology, and mainly restating the already-held finding that leadership and governance, not technology, are the bottleneck.
Companies & AIbusiness
IBM·tier 2
This is a glossary-style explainer defining agent sprawl, built entirely from other outfits' numbers (Gartner, IBM IBV, US Chamber of Commerce) rather than IBM's own primary study. It offers no mechanism of its own, just a definition dressed with borrowed statistics.
Companies & AIbusiness
IBM·tier 2
A genuine IBM-Morning Consult survey of over 2,000 respondents, but it is about K-12 school readiness and parental trust, not companies adopting AI, women and AI, or an individual using AI. The population and topic sit outside her themes.
Women & AIbusiness
IBM·tier 2
A list of prominent women in AI ethics roles with no data, no design, and no mechanism, pure advocacy framing for Women's History Month. It adds nothing beyond names already well known.
Women & AIbusiness
IBM·tier 2
Title-only community post announcing a cohort program, no fetched opening, no data or mechanism to evaluate. Cannot carry any read above low.
Women & AIbusiness
IBM·tier 2
Title-only teaser for what appears to be the same IBM female-leadership report as another candidate, but with no opening text there is no evidence here to weigh, so it cannot be rated on its merits.
Open the article →Judged on the title alone: only 117 characters of readable text, which is a teaser or a paywall rather than an opening
Companies & AIbusiness
IBM·tier 2
A generic explainer on generative AI use cases in the enterprise, built from marketing framing and general claims rather than any primary study or mechanism.
Companies & AIbusiness
IBM·tier 2
A topic-glossary piece on AI workflow automation citing a single IBM IBV statistic about executive expectations for 2027, with no study design or mechanism behind it.
Companies & AIbusiness
IBM·tier 2
An explainer on AI in recruiting that leans on a WEF jobs-report projection and IBM upskilling figures, with no primary data collection or mechanism specific to this piece.
Companies & AIbusiness
IBM·tier 2
A topic explainer on AI asset management citing an IBM executive survey in passing; it is about physical asset management, not organizational AI adoption dynamics relevant to her themes.
Companies & AIbusiness
IBM·tier 2
A marketing-style explainer on how AI supports change management, citing a stray engagement statistic without describing any study design or mechanism worth updating her library with.
Women & AIbusiness
IBM·tier 2
Title-only community blog post on inclusion strategies, no opening text available, so there is no finding or mechanism to assess.
Women & AIbusiness
IBM·tier 2
Title-only community document with almost no readable text, giving no evidence to judge beyond the title itself.
Open the article →Judged on the title alone: only 36 characters of readable text, which is a teaser or a paywall rather than an opening
Women & AIbusiness
IBM·tier 2
A bare community usergroup landing page with no article content, summary, or data of any kind.
Women & AIbusiness
IBM·tier 2
Title and one line snippet only, no fetched opening, so per the opening rule it cannot carry a must read and there is no number or mechanism to weigh; also reads as a vendor blog on representation and leadership, not primary evidence.
Companies & AIbusiness
Accenture·tier 2
A vendor and consultancy framework launch with a marketing quote citing one stray adoption stat, not a study with disclosed method or primary data. This is a tool round up dressed as research.
Companies & AIbusiness
Accenture·tier 2
An investment and partnership announcement for a compliance AI vendor, no primary data, no mechanism, pure vendor promotion.
Companies & AIbusiness
Accenture·tier 2
Product launch blog for a media AI suite, no empirical claim beyond a marketing stat about media type fragmentation, vendor promotional content.
Companies & AIbusiness
Accenture·tier 2
Investment announcement for a customer service AI vendor, no primary data, vendor promotion of a partnership.
Companies & AIbusiness
Accenture·tier 2
Forward looking opinion piece on private equity and agentic AI, market deal value figures are not primary adoption research, and the cited 250 PE professional survey is not detailed. Credible opinion at best.
Companies & AIbusiness
Accenture·tier 2
Launch announcement for a new Accenture mid-market business line, no primary research, pure vendor promotion.
Companies & AIbusiness
Accenture·tier 2
PDF link with no fetched opening, title only, cannot carry a must read and there is nothing here to weigh beyond a title.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
Accenture·tier 2
A single client case study of one AI assistant deployment at a European Commission directorate, usage counts only, no comparative or causal design, vendor client story rather than research.
Companies & AIbusiness
Accenture·tier 2
Vendor blog previewing research not yet released, the 61% versus 29% production stat is teased without method, and the piece is written in marketing register promoting Accenture's own multi model capability.
Companies & AIbusiness
Accenture·tier 2
Product expansion blog for Accenture and AWS, the single stat that only 32% of leaders report sustained AI impact is embedded in a capability launch, not presented as research findings, and duplicates figures the library already holds on the gap between AI use and AI value.
Companies & AIbusiness
Accenture·tier 2
PDF link with no fetched opening, title only, so per the opening rule it is judged on title and snippet alone and cannot carry a must read.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
Accenture·tier 2
Only a title and PDF link could be retrieved, so there is no number or mechanism to weigh. It is also an Accenture-produced vendor report with no visible primary data, which the rubric treats as would-not-read regardless of its title.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
Accenture·tier 2
Title-only PDF from Accenture with no fetchable opening. No evidence is available to judge, and vendor-funded promotional reports without visible data are would-not-read by definition.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
Accenture·tier 2
Title-only PDF, no opening could be fetched. Nothing in the snippet gives a number or mechanism, and it is vendor marketing collateral, so it cannot be more than would-not-read.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
Accenture·tier 2
This is Accenture's own pitch for a cost-accounting framework (tokenomics) linking AI spend to business value, illustrated with an internal anecdote about token routing. It is vendor content with no primary research on organizational or workforce adoption mechanisms, so it does not fit her themes or the evidence bar.
Companies & AIbusiness
Accenture·tier 2
A marketing landing page linking out to other Accenture service pages, with isolated stat fragments and no methodology or study attached. This is a vendor tool round-up with no primary data.
Companies & AIbusiness
Accenture·tier 2
A product and partnership announcement for Accenture's Cyber.AI offering built on Anthropic's Claude. It contains no adoption research, only a launch narrative, so it is would-not-read vendor content.
Companies & AIbusiness
Accenture·tier 2
A descriptive careers page explaining how Accenture uses AI in its own hiring process. There is no study, number, or mechanism here, just a vendor policy description.
Companies & AIbusiness
Accenture·tier 2
A corporate investment announcement ($3 billion into Accenture's Data & AI practice) with executive quotes and no research findings. Pure vendor promotion, no primary evidence.
Companies & AIbusiness
Accenture·tier 2
An internal reorganization and leadership-appointment announcement. It contains no findings about AI adoption, workers, or organizations beyond restructuring Accenture itself.
Companies & AIbusiness
Accenture·tier 2
A partnership announcement between Accenture and OpenAI to roll out ChatGPT Enterprise internally and to clients. It is a business deal announcement with no adoption data or mechanism.
Companies & AIbusiness
Accenture·tier 2
Title-only PDF with no opening retrievable. No number or mechanism is available to assess, and it is vendor collateral.
Open the article →Judged on the title alone: the link is a PDF, which this stage does not read
Companies & AIbusiness
Accenture·tier 2
A vendor case study describing how Accenture built its own responsible-AI governance program, with a couple of unsourced stat fragments (96% of orgs support some regulation) but no methodology or comparative data. It is self-report vendor content, not primary evidence.
Companies & AIbusiness
Accenture·tier 2
This is vendor-funded marketing content from Accenture reporting executive belief percentages about trust and AI autonomy, not a mechanism or a number that changes anything. It restates the already-well-documented claim that trust matters for AI adoption without new evidence.