Evidence (20058 claims)
Search and filter individual claims pulled from the papers. Looking for a specific finding ("what's the effect on wages?"), you're in the right place. Want to compare whole outcome categories against each other instead? Use the Evidence Explorer.
The board below groups claims two ways: by broad theme (nine paper-level topics) and by outcome category (the 34 claim-level outcomes that the Explorer and Syntheses also use).
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Nine broad, paper-level topics. Click one to filter the claims below.
Adoption
20058 claims
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Productivity
17184 claims
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Governance
16099 claims
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Human-AI Collaboration
16034 claims
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Innovation
10501 claims
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Org Design
10496 claims
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Labor Markets
6444 claims
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Skills & Training
5385 claims
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Inequality
4148 claims
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Claims by outcome category
Counts by direction of finding. These are the same 34 outcome categories the Explorer compares and the Syntheses are written for. A linked row has a published synthesis.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 1820 | 479 | 278 | 1820 | 4588 |
| Organizational Efficiency | 2711 | 616 | 401 | 173 | 3922 |
| Governance & Regulation | 2075 | 886 | 459 | 246 | 3714 |
| Technology Adoption Rate | 1467 | 530 | 258 | 206 | 2488 |
| Decision Quality | 1281 | 496 | 289 | 152 | 2228 |
| Output Quality | 1227 | 447 | 207 | 138 | 2025 |
| AI Safety & Ethics | 634 | 754 | 207 | 83 | 1688 |
| Research Productivity | 826 | 241 | 114 | 422 | 1624 |
| Firm Productivity | 1052 | 154 | 163 | 66 | 1441 |
| Task Allocation | 685 | 211 | 331 | 99 | 1335 |
| Market Structure | 433 | 423 | 242 | 46 | 1150 |
| Innovation Output | 639 | 91 | 105 | 34 | 871 |
| Task Completion Time | 476 | 113 | 43 | 36 | 672 |
| Firm Revenue | 445 | 126 | 58 | 25 | 656 |
| Skill Acquisition | 364 | 119 | 109 | 34 | 626 |
| Consumer Welfare | 288 | 167 | 104 | 31 | 592 |
| Employment Level | 214 | 140 | 174 | 50 | 582 |
| Error Rate | 230 | 251 | 35 | 16 | 535 |
| Fiscal & Macroeconomic | 268 | 136 | 71 | 50 | 532 |
| Inequality Measures | 100 | 307 | 96 | 12 | 515 |
| Worker Satisfaction | 221 | 173 | 60 | 30 | 484 |
| Automation Exposure | 155 | 138 | 65 | 36 | 398 |
| Regulatory Compliance | 171 | 120 | 30 | 13 | 335 |
| Developer Productivity | 222 | 58 | 27 | 13 | 321 |
| Team Performance | 188 | 56 | 50 | 24 | 320 |
| Wages & Compensation | 146 | 104 | 46 | 16 | 312 |
| Training Effectiveness | 207 | 41 | 21 | 26 | 298 |
| Job Displacement | 23 | 153 | 52 | 4 | 232 |
| Hiring & Recruitment | 102 | 57 | 30 | 11 | 202 |
| Skill Obsolescence | 16 | 102 | 24 | 6 | 148 |
| Creative Output | 71 | 42 | 23 | 6 | 143 |
| Social Protection | 57 | 30 | 11 | 3 | 101 |
| Labor Share of Income | 29 | 42 | 24 | 2 | 97 |
| Worker Turnover | 43 | 29 | 6 | 4 | 82 |
| Industry | — | — | — | 1 | 1 |
Adoption
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Science has a positive local effect on co-located digital and artistic activity while exerting a negative regional backwash effect that draws creative capacity away from neighbouring districts.
Spatial Durbin model estimating within-district and between-district effects for digital technology, science, and arts segments.
Creative agglomeration in Slovakia is conditional on reaching segment-specific density thresholds and is shaped by asymmetric cross-district spillovers and industrial legacy.
District-level analysis using segment-specific location quotients, population density, manufacturing specialization, a spatial Durbin model, random-forest simulations, and breakpoint tests.
The paper distinguishes substantive peer competition from symbolic peer competition by measuring the former with peers’ real digital-transformation investments and the latter with peers’ disclosures or announcements.
Operationalization of the two peer-competition measures in the empirical analysis.
The effects of peer-driven digital transformation vary across industries and market structures.
Reported heterogeneity and supplementary analyses using industry and market-structure splits.
Educational data should be treated as an economic asset with potential negative externalities, including privacy harms and surveillance, requiring data-governance and property-rights analysis.
Normative political-economy implication drawn from the essay's analysis of platformisation and datafication; this is a proposed analytical framework rather than an empirically estimated result.
The platformisation and datafication of education are reshaping educational markets, data governance, and pedagogical practices while introducing new power asymmetries based on surveillance and data monetization.
Conceptual analysis of EdTech and platform actors, drawing on existing scholarship and contemporary developments in technology and education.
Funding mandates, international collaboration, journal prestige, and disciplinary norms are associated with systematic differences in Creative Commons license selection.
The study models categorical CC-license choice using multinomial logistic regression and examines funding-policy strength, international collaboration, subject category, and journal impact-factor percentile among 122,085 open-access articles.
Employee resistance to AI adoption is driven by fears of job displacement and skill obsolescence, and the paper argues that training programmes and transparent change management can help overcome this resistance.
Thematic synthesis and practical recommendations in the systematic literature review; the supplied text reports no employee survey sample or estimated intervention effect.
Twitter-derived signals and Google Trends signals provide complementary information for apparel demand forecasting; neither signal source uniformly dominates the other when used alone.
Pairwise head-to-head comparisons of signal sets, in which Twitter alone and Google Trends alone each won approximately 51%–57% of matchups.
Short-run disruption includes job churn and wage compression for affected groups, while long-run outcomes depend on reskilling, capital re-allocation, and institutions.
Asserted in the supplied example contribution; no longitudinal employment, wage, or reskilling evidence is provided.
Regions with higher human capital and adoption capacity capture more productivity gains, while disadvantaged regions face stagnation.
Presented as a regional heterogeneity claim; no regional panel, productivity measure, or comparative estimate is supplied.
AI substitutes for routine cognitive and manual tasks, shifting worker duties toward nonroutinized, interpersonal, and creative tasks.
Presented as a task-based displacement claim; no task-level dataset or estimates are supplied.
Net employment effects are modest short-run losses, with potential long-run gains if complementary skill investment and policy support occur.
Asserted in the supplied example contribution; the text provides no employment panel, identification strategy results, or quantified estimates.
High-skill cognitive tasks and complementary occupations gain earnings, while routine tasks and low-skill occupations face displacement and wage pressure.
Asserted in the supplied example contribution; no occupational employment or wage data are presented.
AI-driven automation accelerates occupational task reallocation, raising productivity but producing uneven wage effects.
Asserted in the supplied example contribution; no underlying paper, dataset, sample, or statistical analysis is provided.
AI-enabled recruitment is associated with a shift toward data-driven decision-making in which machine intelligence complements human expertise.
The paper's literature synthesis and qualitative examination of AI-powered recruitment practices, including chatbots, video interviews, targeted job advertisements, and predictive analytics.
The study advocates balancing automation gains with ethical safeguards and human oversight in AI-driven talent acquisition.
Qualitative exploration of AI-enabled recruitment experiences, including participants' concerns about privacy, organisational readiness, and ethical governance.
Organisational changes associated with AI adoption differ across phases of digital HR maturity.
The study interprets interview themes using Dave Ulrich's digital HR progression framework, comprising efficiency, innovation, information, and connection phases.
The strength of psychological barriers to enterprise AI adoption differs by enterprise size, industry type, and employees' prior AI experience.
Multi-group comparison analyses examined heterogeneity across enterprise and employee subgroups in a three-enterprise survey.
Realizing a required distinction may require revealing additional information, creating a tradeoff between privacy and the ability to make the required judgment.
Conceptual analysis of realization and informational repair; illustrated across institutional and automated decision contexts.
For middle managers, AI has both positive and negative effects: it supports data analysis and managerial decision-making while creating concerns about automation of some managerial responsibilities.
Cross-study synthesis of findings differentiated by organizational level.
Leadership effects in studies of AI adoption and productivity are endogenous to firm selection and internal processes, so causal studies should use instruments or quasi-experimental designs.
The paper's methodological implication concerning endogeneity and causal inference in AI adoption and productivity research.
Digital-era leadership research increasingly frames leadership as distributed and technologically mediated, with AI systems serving as decision aids, communication intermediaries, or partial substitutes for leader tasks.
Synthesis of emerging e-leadership and digital leadership literatures.
The effects of transformational leadership operate through cognitive and affective mediators and vary according to contextual moderators.
Review synthesis of meta-analytic findings concerning mediators and boundary conditions.
The interaction of the AI Act and GDPR creates synergies in governance and accountability but can also compound compliance burdens, producing trade-offs between reduced harms and trust on one hand and efficiency and innovation on the other.
Synthesis of the doctrinal analysis and the paper's discussion of compliance costs, trust, innovation, and regulatory interaction; no quantitative trade-off estimate is provided.
The combined regulatory regimes may induce firms to relocate activities, partition product lines, or maintain dual compliance tracks, thereby affecting the location of data processing and AI development.
Analytical inference from the interaction of extraterritorial obligations, compliance costs, and regulatory differences; no firm-level relocation data are reported.
EU rules may diffuse globally as de facto standards because firms adopt uniform EU-aligned practices to preserve market access, potentially reducing regulatory fragmentation while exporting EU norms.
Comparative legal analysis of extraterritoriality and market-access incentives, interpreted through the regulatory-governance and regulatory-capitalism literature.
Governance-by-design may shift innovation toward safer and more auditable systems, while potentially slowing time-to-market.
Theoretical and interpretive analysis of how embedded compliance requirements may affect product design and innovation incentives; no quantitative innovation or time-to-market estimate is provided.
The two banks studied use different primary performance metrics: one relies on Unit Profitability, while the other has begun adopting Customer Profitability.
Comparative qualitative case study of two national commercial banks, using document analysis and stakeholder insights.
The relationships between AI adoption orientation, entrepreneurial intention, entrepreneurial behaviour, and business performance vary by venture stage, supporting the characterization of AI adoption as a stage-contingent capability.
The study used measurement-invariance testing and PLS-SEM multi-group analysis to compare 108 new and 86 established women entrepreneurs.
AI perspective is primarily associated with entrepreneurial outcomes among established women entrepreneurs rather than equally across both venture stages.
Multi-group PLS-SEM analysis of new and established women entrepreneurs; the abstract reports that AI perspective becomes significant primarily in established ventures.
Rapid technological change in diagnostics, pharmaceuticals, and digital health is shifting which countries produce key health inputs.
Qualitative policy analysis based on observed technological diffusion and changes in production capacity.
Digital transformation has stronger positive associations with substantive carbon disclosure components—carbon-related business practices, carbon governance, and carbon performance—than with the disclosure carrier or reporting format/channel.
Component-level regressions separating substantive content elements from the disclosure-carrier component of the multidimensional CIDQ index.
Hallucination-detection approaches based on response dispersion can provide sample-level evidence of hallucination without access to model internals, but they cannot detect confident, consistent errors.
Formal review of reference-free, internal-state, and retrieval-alignment detection methods, including the worked example in the paper.
The AI Publication Footprint is an absolute cumulative Scopus publication count and therefore serves as a proxy for knowledge-production capacity rather than a normalized measure of research intensity or efficiency.
Measurement definition and methodological caveat; publication counts were not normalized per capita or per researcher.
The cluster analysis identifies four country types arranged along a gradient from high digital maturity and high national readiness to low readiness and a low AI publication footprint.
Cluster analysis of country profiles combining AI publication footprint and national AI readiness.
Coding was the only reported domain showing mild forgetting for Thomson-1.0-Large relative to its base model, while general mathematical and abstract reasoning remained within the Qwen performance level.
Authors' interpretation of cross-domain results, including coding scores of 39.9% for Thomson-1.0-Large versus 40.9% for Qwen3.5-397B and reasoning scores of 68.4% versus 66.8%.
In the 150-request Claude-MCP command benchmark, 73.3% of requests were executed directly, 22.7% required clarification, and 4.0% requested unavailable operations.
Command-profile analysis of the deployed interactive Claude-MCP agent.
AI enforcement may generate heterogeneous distributional effects across firms, individuals, large businesses, small businesses, and the informal sector.
Policy implication concerning differential exposure to AI-enabled tax enforcement; no distributional estimates are reported.
Automation of audit, risk-scoring, and tax-processing tasks is expected to reconfigure public-sector labor demand toward data-science and governance roles.
Economic interpretation of the likely labor-market effects of automating tax-administration tasks; no employment dataset or causal estimate is reported.
In settings where strategic and operational authority are fused, the decision to delegate tasks to AI or retain human discretion is endogenous to the GM's locus of authority.
Conceptual implication applying the locational-assumption finding to AI task allocation; it is not directly tested with AI deployment data.
AI adoption and performance in hospitality-like settings should be expected to vary across managers because blended strategic-operational roles, managerial adaptability, leadership style, and governance context can produce heterogeneous implementation choices and returns.
Conceptual implication derived from the hospitality GM framework; no direct AI adoption experiment or quantified treatment-effect estimate is reported.
The organizational context affecting GM decisions should be modeled as co-constituted by GM actions and governance structures rather than treated solely as an exogenous moderator.
Cross-domain theoretical synthesis emphasizing governance, institutional constraints, stakeholder interactions, and operational feedback loops.
Static models linking stable managerial traits to stable decisions are insufficient because the effects of GM characteristics depend on dynamic competence, situational expression of values, leadership adaptability, and recognition of gendered traits.
Thematic synthesis of studies on GM characteristics and leadership styles, used to qualify the dispositional assumption.
In hospitality, general managers often combine strategic and operational authority, so the relationship between leader characteristics and organizational outcomes is conditional on the GM's blended role.
Cross-domain synthesis of hospitality GM literature addressing the locational assumption and the convergence of strategic and operational authority.
Upper Echelons Theory does not function as a universal set of assumptions for hospitality general managers; its locational, dispositional, situational, and temporal assumptions operate as boundary conditions that require qualification in high-contact service settings.
Integrative review and cross-domain theoretical synthesis of 92 empirical and conceptual studies on hospitality general managers, covering GM characteristics, leadership styles, and succession.
Widespread adoption of similar explainable ESG models could increase herd behavior or model correlation across financial institutions, creating ambiguous systemic-risk effects.
Conceptual risk assessment in the paper's AI-economics implications; the supplied text reports no empirical test of systemic effects.
The reviewed research is methodologically concentrated in quantitative, model-centric studies, while qualitative and mixed-method research is limited.
Methodological coding in the systematic review, including analysis of research designs and evaluation approaches.
The company-level version of SCAF conceptualizes vulnerability as exposure created by product deployment reach, coping as features that help users respond to and recover from failures, and adaptive capacity as features and practices that reduce future failures and improve learning.
Table 2's operational definitions of company contributions to vulnerability, coping, and adaptive capacities.
Companies that deploy AI agents increase societal vulnerability to agentic-AI risks, while the same companies can also build societal resilience through design decisions that improve responses to failure.
The paper's explicit claim that deployment increases exposure, paired with its framework for coping and adaptive contributions.