Evidence (8570 claims)
Adoption
8570 claims
Productivity
7631 claims
Governance
6869 claims
Human-AI Collaboration
6491 claims
Org Design
4175 claims
Innovation
4114 claims
Labor Markets
3566 claims
Skills & Training
2966 claims
Inequality
2066 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 758 | 199 | 100 | 900 | 2007 |
| Governance & Regulation | 826 | 400 | 191 | 122 | 1563 |
| Organizational Efficiency | 777 | 193 | 124 | 84 | 1189 |
| Technology Adoption Rate | 635 | 233 | 124 | 97 | 1098 |
| Research Productivity | 422 | 128 | 57 | 336 | 954 |
| Output Quality | 476 | 179 | 59 | 47 | 761 |
| Decision Quality | 328 | 177 | 81 | 47 | 640 |
| Firm Productivity | 435 | 57 | 88 | 20 | 606 |
| AI Safety & Ethics | 218 | 277 | 65 | 33 | 599 |
| Market Structure | 180 | 170 | 123 | 24 | 502 |
| Task Allocation | 213 | 64 | 72 | 33 | 387 |
| Skill Acquisition | 170 | 61 | 61 | 17 | 309 |
| Innovation Output | 203 | 27 | 43 | 18 | 292 |
| Employment Level | 105 | 54 | 107 | 13 | 281 |
| Fiscal & Macroeconomic | 131 | 69 | 43 | 26 | 276 |
| Consumer Welfare | 117 | 63 | 42 | 11 | 233 |
| Firm Revenue | 153 | 48 | 26 | 3 | 230 |
| Task Completion Time | 173 | 31 | 8 | 12 | 225 |
| Inequality Measures | 44 | 122 | 49 | 6 | 221 |
| Worker Satisfaction | 89 | 65 | 22 | 12 | 188 |
| Error Rate | 69 | 92 | 10 | 2 | 173 |
| Regulatory Compliance | 77 | 69 | 14 | 5 | 165 |
| Automation Exposure | 56 | 56 | 26 | 13 | 154 |
| Training Effectiveness | 94 | 21 | 13 | 19 | 149 |
| Wages & Compensation | 77 | 36 | 25 | 6 | 144 |
| Team Performance | 86 | 17 | 27 | 10 | 141 |
| Developer Productivity | 95 | 17 | 14 | 6 | 133 |
| Job Displacement | 12 | 80 | 20 | 1 | 113 |
| Hiring & Recruitment | 52 | 7 | 8 | 3 | 70 |
| Creative Output | 31 | 18 | 8 | 3 | 61 |
| Skill Obsolescence | 5 | 46 | 6 | 1 | 58 |
| Social Protection | 27 | 16 | 8 | 2 | 53 |
| Labor Share of Income | 17 | 19 | 17 | — | 53 |
| Worker Turnover | 11 | 12 | — | 3 | 26 |
| Industry | — | — | — | 1 | 1 |
Adoption
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The effects of K_T adoption are heterogeneous across industries, firms, countries, and cohorts — early adopters and capital-rich firms/countries gain most — implying important transition dynamics for political economy.
Cross-country comparisons, industry- and firm-level panel heterogeneity analyses, and case studies demonstrating variation in adoption timing and gains; model simulations emphasizing transition path dependence.
Aggregate productivity (output per worker or per unit of inputs) can rise while labor’s share and employment decline due to substitution toward K_T.
Macro growth-accounting exercises decomposing output growth into contributions from labor, traditional capital, and technological capital; model simulations showing productivity gains coexisting with falling labor shares under substitution elasticities.
Neither MCP nor A2A defines the shared workspace in which humans and agents perform accountable work together.
Analytical claim by the authors contrasting existing standards with the missing specification of a shared human-agent workspace; no empirical evaluation provided.
In current practice the human judgement is recorded, if at all, in application code, chat threads, ticket comments, and tribal memory.
Descriptive statement about current recording practices; presented without empirical study or counts in the provided text.
The technical surface for this collaboration remains weakly specified.
Asserted by the authors as an assessment of current technical standards and interfaces; no audit or measurement cited in the provided text.
Macro-level correlation between Frey-Osborne (2013) and Eloundou-era rankings is Spearman rho = -0.750, p = 0.020 (against the original Oxford Martin appendix), indicating inversion.
Reported Spearman correlation and p-value comparing macro-level rankings between the original Frey-Osborne appendix and the paper's Eloundou-era results.
Tool-Mediated Physical (macro M2) has mean OAI = 0.054.
Reported macro-level mean OAI computed after projecting DWA OAI values into the 7-macro typology.
Board power disparity weakens the positive relationship between AI competitive actions and operational efficiency.
Interaction tests in the authors' empirical models using governance measures (power disparity) and NLP-identified AI actions from S&P 500 firms' press releases (2010–2022); reported as a negative conditional effect on operational efficiency.
This regulatory pressure creates a direct conflict between multi-stakeholder transparency and corporate data privacy.
Paper's conceptual argument describing a tension between transparency requirements and proprietary data protection; no empirical study provided.
Regulatory compliance demands have surpassed the capacity of manual corporate reporting.
Assertion in paper (conceptual observation about reporting capacity); no empirical measurement or sample size reported.
The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD), and Carbon Border Adjustment Mechanism (CBAM) introduce a severe governance bottleneck for advanced semiconductor manufacturing facilities ("Smart Fabs").
Declarative claim in paper based on policy convergence analysis; no empirical dataset or sample size reported (conceptual/analytical argument).
Learning specialized simulator input languages can cost domain scientists hours to days.
Stated motivating claim in the paper (no experimental sample size or formal measurement reported in abstract).
In moderate scenarios, AI increases levelised cost of energy (LCOE) by 35 EUR/MWh in key hubs.
Model results for moderate scenarios indicating regional LCOE impacts; reported LCOE increase value for key hubs.
AI risks cumulative emissions overshoots of 67-181 MtCO2 between 2030 and 2050.
Same spatially explicit optimisation model of Europe across 21 AI growth scenarios; reported cumulative emissions overshoot range for 2030–2050.
Transformational leadership negatively moderates the relationship between AI application and employees' job insecurity, buffering employees' insecurity responses across varying levels of AI application.
Moderation analysis reported in the study using the same employee survey dataset (411 valid responses), indicating a statistically significant buffering (negative) moderating effect of transformational leadership on the AI–job insecurity relationship.
Self-efficacy negatively moderates the relationship between AI application and employees' job insecurity by strengthening the insecurity-reducing effect of moderate AI application and weakening the insecurity-enhancing effect of excessive application.
Moderation analysis on the same cross-sectional survey data (411 valid employee questionnaires), reporting a statistically significant negative (buffering) interaction of self-efficacy with AI application intensity on job insecurity.
GenAI adoption may intensify informational imbalances in low-governance markets (asymmetric adverse effects).
Asymmetric effects observed in cross-market analyses and subgroup tests indicating worsening information asymmetries or related measures in low governance contexts.
In weaker governance environments, the benefits of GenAI adoption for institutional efficiency are limited.
Heterogeneity analysis / interaction models showing smaller or non-significant effects of GenAI on institutional efficiency in markets with low governance capacity.
Employees currently lack clear guidance on appropriate use of GenAI within organizations.
Background claim in paper motivating the study (statement that employees 'lack clear guidance on appropriate use').
Gains from autonomous AI agents (reduced search costs and improved matching) are not automatic because the behavior of current AI agents introduces frictions that limit competitive outcomes.
Theoretical argument drawing on economic search theory and the paper's analysis of agent behavior as described in the abstract; no empirical details or sample sizes provided in abstract.
Interviews provide expanded analysis on existing skill gaps and lifelong learning needs among wind-energy professionals.
Qualitative interview data are reported to highlight skill gaps and lifelong learning needs; specific counts of interviewees not provided in the summary.
The framework reframes the education–employer gap as a structural failure in the pathway and outlines implications for universities, employers, accreditors, and policymakers.
Conceptual claim and implications drawn by the author(s) in the paper (stated in the abstract).
The architecture of the undergraduate degree is structurally incapable of replacing the informal post-degree apprenticeship system through curricular revision alone.
Argument presented in the paper, supported by the systematic review of eighteen peer-reviewed studies and labor-market analyses cited in the abstract.
The informal post-degree apprenticeship system that historically completed graduate formation no longer reliably exists.
Claim based on the paper's systematic review of eighteen peer-reviewed studies and current labor-market analyses (as described in the abstract).
Higher education has misdiagnosed the resulting challenge as curriculum misalignment—a content problem assumed to be solvable through revised syllabi, AI electives, and marginal expansions of experiential learning.
Argument presented in the paper, supported by the paper's systematic review of eighteen peer-reviewed studies and labor-market analyses (as described in the abstract).
Artificial intelligence and automation are restructuring early-career knowledge-work roles by compressing the entry-level functions through which graduates historically built portfolios, developed professional judgment, and earned professional credibility.
Statement supported in the paper by a systematic review of eighteen peer-reviewed studies and current labor-market analyses (as described in the abstract).
Private-market valuations are concentrated in a small number of firms.
Paper reports concentration of private-market AI valuations (distributional evidence across firms in private markets); exact counts or percentages not provided in the abstract.
Capital expenditure has accelerated faster than observed monetization in some layers of the AI stack.
Comparative analysis of capex trends vs monetization metrics presented in the paper (layered AI stack comparison); specific sample counts not provided in the abstract.
Entropy dissipation corresponds to organizational complexity, coordination frictions, energy constraints, regulatory uncertainty, talent mobility pressures, and opportunities to strengthen industrial absorption.
Definition/mapping provided in the paper as part of the HCLM framework; conceptual.
Apart from earnings adequacy, occupations characterized by dimensions of precarity were associated with lower LLM exposure (i.e., higher precarity on those dimensions corresponded to lower LLM exposure).
Abstract statement summarizing regression results across separate models for each precarity dimension (exact coefficients not provided in abstract).
Occupations most likely to be exposed to LLM are those where precariousness is lowest.
Summary conclusion based on the reported comparisons of mean LLM exposure across precarity categories using the Labour Force Survey and regression analyses described in methods.
Apart from earnings adequacy, LLM exposure was lower among occupations exhibiting each separate dimension of precarity (contractual instability, schedule unpredictability, working-time mismatch).
Separate multivariate linear regression models (one per precarity dimension) estimated associations between occupational LLM exposure and each dimension using Canada's Labour Force Survey; results reported in abstract (no per-dimension effect sizes provided in abstract).
Using the multidimensional precarity index, occupations characterized by low exposure to precarity had a significantly higher mean LLM exposure (mean 0.386, 95% confidence interval 0.356-0.417) compared to occupations with medium (mean 0.258, 95% CI 0.221-0.295), high (mean 0.260, 95% CI 0.194-0.328) or very high precarity (mean 0.205, 95% CI 0.136-0.275).
Analysis of Canada's Labour Force Survey; constructed multidimensional precarity index; multivariate linear regression models with cluster-robust standard errors; model coefficients used to produce mean estimates of occupational LLM exposure. (Sample size not reported in abstract.)
Algeria lags behind peer countries on key indicators of digital infrastructure, human capital, and institutional frameworks as evidenced by World Bank (2022) and Oxford Insights indices.
Specific comparative claim based on the paper's use of World Bank (2022) indicators and Oxford Insights Government AI Readiness Index scores; the summary does not report numeric index values or sample sizes.
Findings reveal that Algeria exhibits significant lag in digital infrastructure, human capital, and institutional frameworks compared to peers (Morocco, Egypt, Turkey).
Result reported from the paper's comparative analysis using World Bank indicators, the Oxford Insights Government AI Readiness Index, and sector-specific studies comparing Algeria to Morocco, Egypt, and Turkey; specific quantitative comparisons not provided in the summary.
Algorithmic scenario planning is being used for tax avoidance.
Presented in the abstract as an example of algorithmic technologies applied to international tax purposes (scenario planning for tax avoidance); no empirical details provided in the abstract.
Existing research has significant shortcomings in terms of local empirical evidence, micro task mechanisms, and the impact of cutting-edge AI.
Critical appraisal in the paper's discussion of gaps identified through the systematic literature review; no single-study sample size.
Skill mismatch constitutes the core contradiction of labor force transformation.
Interpretive conclusion from the literature review asserting that mismatches between worker skills and job/task requirements are central to the labor-market effects of AI.
Current results show that the hardest tier remains far from saturated: across mainstream harness and backbone configurations, the average full pass rate is 2.6%.
Empirical evaluation results reported by the authors summarizing ALE benchmark performance across mainstream harness and backbone configurations (no further detail on exact configurations or task/sample counts in excerpt).
The gap is largely an evaluation problem: widely used benchmarks lack sustained performance measurement on real and economically valuable workflows.
Author argument presented in the paper; motivated by benchmarking limitations rather than an empirical test in the excerpt.
These gains have not translated into economically meaningful deployment across many professional domains.
Assertion in paper arguing a deployment gap between benchmark performance and real-world economic adoption; no quantitative deployment data provided in the excerpt.
Manual processing of these documents is time-consuming, inconsistent across reviewers, and unscalable.
Author claim / background motivation; no quantitative time or consistency metrics reported in the statement.
Actuaries rely primarily on structured numerical data for reserving and ratemaking, while valuable predictive information in unstructured text including medical records, adjuster notes, and call transcripts remains largely unused.
Author statement/observation in paper introduction; no empirical data or sample size provided to support prevalence claim.
The paper critically analyzes the implications of LLM-integrated search for brand trust, content authenticity, algorithmic bias, and market concentration.
Stated scope of analysis in the paper; presented as critical analysis rather than empirical claims in the provided text.
This paradigm shift raises critical questions regarding brand visibility, content authority, and digital marketing strategy.
Analytical claim in paper discussing implications; supported by theoretical argumentation rather than empirical measurement in the provided text.
The emergence of AI-generated summaries and answer-driven search experiences is shifting consumer discovery from link-based navigation to synthesized, context-aware responses.
Stated observation in the paper; argued via conceptual reasoning about AI-generated summaries and answer-driven interfaces rather than reported empirical metrics or sample-based experiments in the excerpt.
Collaborative filtering and graph-based recommendation models are highly effective because they leverage observed user interactions, but this dependence creates a fundamental cold-start challenge when newly added content has no interaction history.
Statement in paper framing problem; references to general properties of collaborative filtering and graph-based recommenders (conceptual / literature-backed claim, no specific experiment reported in this excerpt).
The determining barrier to adoption observed in the two studied public-service units was not technological but training-related.
Qualitative analysis and intervention observations across two auditable case studies (SES/CONT in 2024 and UCI/SEDET in 2025); author-developed intervention and outcome changes used to support inference.
The adoption of generative artificial intelligence in the public sector has been treated predominantly as a technological problem, with the expectation that productivity gains would follow from more capable models.
Author statement / literature-positioning in paper (assertion about prevailing treatment); no quantitative data provided in text to support prevalence.
The COVID-19 pandemic reduced tourism’s GDP share by approximately 37%.
Fixed-effects panel estimation including a COVID-19 indicator on 33 countries (2017–2023); reported coefficient β = –0.455, p < 0.001 (interpreted as ~37% reduction in the dependent variable).