Evidence (5877 claims)
Adoption
7395 claims
Productivity
6507 claims
Governance
5877 claims
Human-AI Collaboration
5157 claims
Innovation
3492 claims
Org Design
3470 claims
Labor Markets
3224 claims
Skills & Training
2608 claims
Inequality
1835 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 609 | 159 | 77 | 736 | 1615 |
| Governance & Regulation | 664 | 329 | 160 | 99 | 1273 |
| Organizational Efficiency | 624 | 143 | 105 | 70 | 949 |
| Technology Adoption Rate | 502 | 176 | 98 | 78 | 861 |
| Research Productivity | 348 | 109 | 48 | 322 | 836 |
| Output Quality | 391 | 120 | 44 | 40 | 595 |
| Firm Productivity | 385 | 46 | 85 | 17 | 539 |
| Decision Quality | 275 | 143 | 62 | 34 | 521 |
| AI Safety & Ethics | 183 | 241 | 59 | 30 | 517 |
| Market Structure | 152 | 154 | 109 | 20 | 440 |
| Task Allocation | 158 | 50 | 56 | 26 | 295 |
| Innovation Output | 178 | 23 | 38 | 17 | 257 |
| Skill Acquisition | 137 | 52 | 50 | 13 | 252 |
| Fiscal & Macroeconomic | 120 | 64 | 38 | 23 | 252 |
| Employment Level | 93 | 46 | 96 | 12 | 249 |
| Firm Revenue | 130 | 43 | 26 | 3 | 202 |
| Consumer Welfare | 99 | 51 | 40 | 11 | 201 |
| Inequality Measures | 36 | 105 | 40 | 6 | 187 |
| Task Completion Time | 134 | 18 | 6 | 5 | 163 |
| Worker Satisfaction | 79 | 54 | 16 | 11 | 160 |
| Error Rate | 64 | 78 | 8 | 1 | 151 |
| Regulatory Compliance | 69 | 64 | 14 | 3 | 150 |
| Training Effectiveness | 81 | 15 | 13 | 18 | 129 |
| Wages & Compensation | 70 | 25 | 22 | 6 | 123 |
| Team Performance | 74 | 16 | 21 | 9 | 121 |
| Automation Exposure | 41 | 48 | 19 | 9 | 120 |
| Job Displacement | 11 | 71 | 16 | 1 | 99 |
| Developer Productivity | 71 | 14 | 9 | 3 | 98 |
| Hiring & Recruitment | 49 | 7 | 8 | 3 | 67 |
| Social Protection | 26 | 14 | 8 | 2 | 50 |
| Creative Output | 26 | 14 | 6 | 2 | 49 |
| Skill Obsolescence | 5 | 37 | 5 | 1 | 48 |
| Labor Share of Income | 12 | 13 | 12 | — | 37 |
| Worker Turnover | 11 | 12 | — | 3 | 26 |
| Industry | — | — | — | 1 | 1 |
Governance
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Earlier high-risk technologies were slowed by capital intensity, physical bottlenecks, organizational inertia, and specialized supply chains.
Historical/analytic claim presented as background context in the paper; supported by conceptual comparison rather than a specific empirical study.
Scientific institutions, distinctively, manufacture legitimate judgment, so they do not merely adapt to AI; they compete with it for the same functional role.
Conceptual/theoretical assertion in the paper describing institutional roles; no empirical data or sample size provided in the excerpt.
No single governance setting dominates across all contexts; moderate governance becomes increasingly competitive as the learner accumulates experience within the governed action space.
Empirical finding reported from experiments with the contextual-bandit learner operating under different governance constraints and learning over time; comparative performance over learning horizon described in the paper. Sample size / trial counts not provided in the excerpt.
This workload-buffering effect (governance improving performance while reducing fatigue) contradicts the usual framing of governance as pure overhead.
Interpretation and comparison of empirical manufacturing results against prior framing in literature (qualitative claim within the paper). No sample size provided.
Governance is not a binary switch but a tunable design variable: tighter constraints predictably convert autonomous AI assignments into supervised collaborations, with domain-specific costs and benefits.
Empirical finding reported from experiments using the HAAS benchmark across the two domains (software engineering and manufacturing); qualitative and/or quantitative comparisons of allocations under varying governance constraints. Paper does not state sample size in the provided text.
AI learns indiscriminately from implicit knowledge, acquiring both beneficial patterns and harmful biases.
Asserted in the paper as a conceptual point about training data and learned patterns; no empirical evaluation or quantified bias measures provided.
Whether the futures these configurations help create remain governable and worth inhabiting will depend on leaders who can see, early enough, where and how consequential decisions are actually being shaped.
Normative/prognostic claim linking future governability to leaders' detection capabilities (conceptual; no empirical test provided in the excerpt).
These configurations will shape how power, responsibility, and trust are distributed in organizational life.
Theoretical/prognostic claim in the paper linking configurations to distribution of power, responsibility, and trust (no empirical quantification in the excerpt).
In operational meteorology, adjoint-based methods derive value from the forecast model itself but require full data assimilation infrastructure.
Technical background in paper describing adjoint-based methods and their infrastructural requirements (methodological literature references; no new empirical data).
The rise of digital agents will transform the foundations of production, labour markets, institutional arrangements and the international distribution of economic power.
Synthesis and theoretical projection across sections of the paper; presented as a broad conclusion without reported empirical quantification in the provided text.
There is a fundamental asymmetry between economic and social reproduction: digital agents can compensate for productive functions of the population but are unable to substitute the population's functions of social reproduction.
Theoretical argument and conceptual distinction in the paper; no empirical study measuring substitution in social reproduction provided.
The retrieved sources are substantially different for each search engine (average pairwise Jaccard similarity < 0.2).
Computed average Jaccard similarity of source-domain sets returned by each engine (Google organic results, Google AIO, Gemini Flash 2.5) across the 11,500 queries; reported average similarity < 0.2.
The rapid growth of AI and automation offers Sub-Saharan Africa economic opportunities as well as labor market challenges.
Systematic review of the literature reported in the paper; scope and number of studies not specified in the abstract/summary provided.
Susceptibility to visual priming varies across state-of-the-art VLMs.
Comparative experiments run across multiple state-of-the-art vision-language models showing differential changes in IPD behavior when exposed to the same visual primes and color cues. (Paper notes variation in susceptibility and mitigation effectiveness across models; specific model list and per-model sample sizes not given in the abstract.)
Color-coded reward matrices alter VLM decision patterns.
Experimental condition varying the visual presentation of the IPD payoff matrix (color-coding of rewards) and measuring resulting decision patterns of multiple VLMs in IPD trials. (Reported as part of the experimental setup across models; exact counts not provided in abstract.)
VLM behavior can be influenced by image content depicting behavioral concepts (kindness/helpfulness vs. aggressiveness/selfishness).
Experimental manipulation in the Iterated Prisoner's Dilemma (IPD): VLMs were exposed to images labeled/connoting 'kindness/helpfulness' versus 'aggressiveness/selfishness' and subsequent choices in IPD rounds were recorded across multiple state-of-the-art VLMs. (Paper reports experiments across multiple VLMs; exact sample sizes per model/condition not stated in the abstract.)
AI adoption leads both to job displacement and job creation, including the emergence of new occupational categories.
Abstract states the review examines empirical evidence on both job displacement and creation and the emergence of new occupations; no numeric counts or sample sizes provided in abstract.
The study identifies short-term transitional risks and long-term productivity gains associated with AI integration in the workforce.
Abstract states the paper evaluates both short-term risks and long-term productivity gains from AI integration based on the reviewed literature; no empirical quantification given in abstract.
AI-driven automation and augmentation are reshaping employment landscapes, with emphasis on sector-level disruption, skill transformation, and socioeconomic consequences.
Abstract states this as a conclusion of the review drawing on interdisciplinary empirical literature; no specific studies or sample sizes cited in abstract.
The accelerating deployment of artificial intelligence across industries has fundamentally altered the structure of global labour markets.
Statement in abstract summarizing a systematic review of interdisciplinary literature (economics, computer science, organizational behaviour, public policy); no specific sample size reported in abstract.
Firms may continue to exist as legal and physical entities, but their coordinating function will be displaced as they become data nodes within regionally governed AI infrastructure.
Predictive/conceptual claim within the framework; no empirical sample reported in the excerpt and presented as a theoretical outcome of Interface Internalization.
The Structural Dissolution Framework challenges the Coasian view that organizational boundaries are determined by transaction cost minimization, arguing that AI makes such boundaries economically obsolete.
Theoretical critique of transaction-cost-based explanations for firm boundaries presented in the paper; argumentative and conceptual rather than supported by empirical tests in the provided summary.
Regional data sovereignty entities will emerge as organizational forms that replace the coordinating role of firms and markets.
Normative/predictive claim within the paper's framework arguing for new organizational forms (regional data sovereignty entities); illustrated conceptually (e.g., through resource-dependent regional economies) rather than empirically tested in the provided text.
Domain-specific data refinement infrastructure will become the new basis of positional control in industries.
Theoretical claim in the framework asserting a shift in positional control to data refinement infrastructure; presented as a predicted structural outcome rather than supported by empirical data in the provided text.
AI adoption moves value creation away from physical resources and human collaboration toward continuous token flows produced through data refinement loops.
Theoretical/analytical claim within the Structural Dissolution Framework and illustrative discussion; no empirical quantification provided in the text excerpt.
The mechanism driving this restructuring is 'Interface Internalization', through which inter-agent coordination is absorbed into intra-system computation.
Conceptual mechanism defined and argued in the paper; presented as the central theoretical mechanism rather than as an empirically validated finding.
AI dissolves the boundaries that once separated firms, markets, experts, and consumers by internalizing human multimodal interfaces (language, vision, and behavioral data) into computational systems.
Theoretical argument and conceptual framework introduced in the paper (Structural Dissolution Framework); no empirical sample or quantitative analysis reported for this claim in the text provided.
Architectural interventions can instead be used to trade off personalization against preference privacy.
Proposed solution described in the paper (architectural interventions) as an alternative to prompt-level fixes; presented as a design tradeoff rather than empirically validated mitigation in the excerpt.
AI-driven automation marks the beginning of a new political era—one in which the role of work in society becomes a central axis of welfare conflict.
Theoretical and interpretive claim in the paper, motivated by the survey findings and broader argumentation about political consequences.
This hybrid Make governance form has qualitatively different economics, capability requirements, and governance structures than pre-AI in-house development.
Paper's conceptual comparison between pre-AI hierarchy and post-AI hybrid Make governance (theoretical reasoning and examples; no empirical quantification).
AI reshapes seven canonical decision determinants for make-or-buy choices: cost, strategic differentiation, asset specificity, vendor lock-in, time-to-market, quality and compliance, and organizational capability.
Paper's factor-level conceptual analysis enumerating and discussing seven determinants (theoretical synthesis rather than empirical measurement).
Demographic characteristics intersect with AI exposure—i.e., exposure varies by demographic groups.
Paper reports that it examines how demographic characteristics intersect with exposure based on recent empirical studies; no demographic breakdowns or sample sizes provided in the abstract.
Recent studies combine task-level exposure metrics with employment and usage data to assess AI exposure and impacts.
Paper notes that it draws on studies that use task-level exposure metrics alongside employment and usage data; methodological claim rather than a quantitative result.
Generative large language models (LLMs) present organizations with a transformative technology whose labor market implications remain nascent yet consequential.
Statement in paper synthesizing emerging empirical research; no specific study, method, or sample size reported in the abstract.
The adoption of AI in Israel constitutes a systemic transformation of employment relations, necessitating doctrinal adaptation and institutional reform to keep the labor market aligned with foundational legal principles.
Synthesis and conclusion from the paper's combined legal and empirical analysis; presented as the author's overarching interpretive claim rather than as a specific quantified finding.
Within the public sector, there is an emerging policy trend to incorporate AI considerations into workforce planning, including examining whether human positions may be substituted by technological solutions prior to recruiting new employees.
Paper reports an observed policy trend in public-sector workforce planning; specific policy documents, jurisdictions, or counts not provided in the excerpt.
We identify significant differences between human and AI negotiation behaviors, finding that humans favor lower-complexity deals and are significantly less reliable partners compared to LM-based agents.
Results from the user study comparing human vs LM-based agent negotiation behavior (statements in the results section).
High-value uses require broader authority exposure — data access, workflow integration, and delegated authority — when governance controls have not yet decoupled capability from authority exposure.
Conceptual/mechanism claim articulated in the paper (motivating assumption for the analytical model; no empirical sample given in the abstract).
Firms are deploying more capable AI systems, but organizational controls often have not kept pace.
Stated as background context in the paper's abstract/introduction (observational claim; no empirical sample or experiment reported in the abstract).
There is a strict policy reversal in optimal editorial policy sign: tightening is optimal pre-transition, loosening is optimal post-transition.
Analytical proof in the model showing the sign reversal of the editor's optimal constrained response as AI capability crosses the critical threshold.
After the AI transition, editors must loosen acceptance standards while investing in AI detection, because further tightening only amplifies dissipative polishing without improving sorting.
Analytical characterization of the constrained optimal editorial response in the post-transition regime within the model; argument relies on the discontinuous reviewer-effort collapse and comparative statics.
The reviewer-effort collapse creates a welfare misalignment: authors benefit from a weakened 'rat race' while editors suffer from degraded signal informativeness.
Comparative statics and welfare analysis in the theoretical model showing authors' equilibrium payoffs rise as competition/polishing dissipates, while editor's signal informativeness declines due to lower reviewer effort.
In academic peer review, generative AI enters both sides of the market: authors use AI to polish submissions, and reviewers use it to generate plausible reports without exerting evaluative effort.
Model assumption and motivation in the paper's three-sided equilibrium framework; described as the dual adoption mechanism analyzed analytically (no empirical sample size reported).
AI influences innovation performance in organizations.
Discussion and synthesis of studies and reports on AI adoption and innovation performance presented in the review.
AI adoption is producing organizational implications, including changes in project management practices.
Findings synthesized from conference papers, case studies and industry reports included in the review.
Automation, generative AI, and intelligent systems are reshaping task structures, leading to both job displacement risks and the creation of new AI-driven roles.
Synthesis of empirical studies, conference findings, and industry reports reporting both displacement risks and new role emergence (review paper).
AI is rapidly transforming the nature of work, the demand for skills, and the professional roles of Information Technology (IT) practitioners.
Stated as a synthesis result from a narrative review of recent empirical studies, conference findings, and industry reports (review paper).
Semiconductors are a representative case study for analyzing weaponized interdependence in advanced technology sectors.
Methodological claim in the paper: selection and focus on the semiconductor sector as illustrative of broader advanced-technology sector dynamics under export restraints and chokepoint activation.
Previous literature is based primarily on the short-term effectiveness of coercion; this paper shifts attention to the longer-term structural consequences of technological restraints.
Literature review and positioning in the paper contrasting prior studies' short-term focus with the paper's longer-term structural emphasis (methodological/literature-critique claim).
Over time, U.S.–China reaction–counterreaction interactions generate three structural transformations: supply-chain reconfiguration, substitution, and regulations reinforcing segmentation.
Synthesis from the paper's longitudinal/case-analysis of semiconductor-related export restraints and subsequent industry and regulatory responses (qualitative identification of three emergent structural outcomes).