Evidence (566 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).
Browse by theme
Nine broad, paper-level topics. Click one to filter the claims below.
Adoption
10085 claims
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Productivity
8974 claims
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Governance
8062 claims
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Human-AI Collaboration
7749 claims
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Org Design
5057 claims
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Innovation
4896 claims
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Labor Markets
4088 claims
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Skills & Training
3372 claims
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Inequality
2377 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 | 882 | 244 | 117 | 1097 | 2424 |
| Governance & Regulation | 1010 | 469 | 229 | 135 | 1875 |
| Organizational Efficiency | 977 | 235 | 149 | 90 | 1462 |
| Technology Adoption Rate | 781 | 299 | 143 | 128 | 1362 |
| Research Productivity | 506 | 155 | 74 | 363 | 1110 |
| Output Quality | 555 | 219 | 71 | 70 | 915 |
| Decision Quality | 395 | 200 | 95 | 54 | 751 |
| Firm Productivity | 523 | 67 | 101 | 27 | 724 |
| AI Safety & Ethics | 262 | 309 | 75 | 36 | 688 |
| Market Structure | 195 | 201 | 135 | 30 | 566 |
| Task Allocation | 248 | 77 | 96 | 38 | 464 |
| Innovation Output | 300 | 34 | 55 | 20 | 411 |
| Skill Acquisition | 207 | 75 | 65 | 21 | 368 |
| Employment Level | 138 | 67 | 119 | 24 | 350 |
| Fiscal & Macroeconomic | 156 | 80 | 53 | 33 | 329 |
| Task Completion Time | 211 | 38 | 13 | 16 | 280 |
| Firm Revenue | 183 | 52 | 29 | 5 | 270 |
| Consumer Welfare | 131 | 77 | 48 | 13 | 269 |
| Inequality Measures | 50 | 141 | 54 | 9 | 254 |
| Worker Satisfaction | 104 | 85 | 25 | 13 | 227 |
| Error Rate | 87 | 112 | 11 | 5 | 215 |
| Automation Exposure | 69 | 69 | 37 | 20 | 198 |
| Wages & Compensation | 102 | 49 | 31 | 11 | 193 |
| Team Performance | 115 | 30 | 30 | 11 | 187 |
| Regulatory Compliance | 88 | 74 | 17 | 7 | 186 |
| Training Effectiveness | 109 | 22 | 14 | 21 | 168 |
| Developer Productivity | 116 | 21 | 15 | 8 | 161 |
| Job Displacement | 12 | 92 | 26 | 1 | 131 |
| Hiring & Recruitment | 57 | 12 | 9 | 5 | 83 |
| Skill Obsolescence | 6 | 59 | 10 | 2 | 77 |
| Social Protection | 43 | 17 | 8 | 2 | 70 |
| Creative Output | 35 | 21 | 9 | 4 | 70 |
| Labor Share of Income | 18 | 23 | 17 | 1 | 59 |
| Worker Turnover | 15 | 16 | — | 4 | 35 |
| Industry | — | — | — | 1 | 1 |
Competition and alternative disclosure rules need not produce the same fee as a monopolistic certifier; market structure and rules matter for the fee outcome.
Comparative-statics in the model contrasting monopoly pricing with competitive or rule-governed certification mechanisms; theoretical demonstration that fees differ across institutional arrangements. No empirical tests.
The remaining clicks from ChatGPT are not a scaled-down Google stream: they skew toward specialized destinations and away from ad-supported sites.
Categorical analysis of destinations clicked from ChatGPT versus Google using URL-level Comscore U.S. desktop clickstream; comparison of destination types (specialized sites vs. ad-supported sites).
Under S3 alone the Electricity sector expands only +0.10% by 2030 despite a 14.87% per year IT investment surge, indicating binding generation capacity that the Green AI productivity shock relaxes in S4.
CGE simulation of S3 (exogenous IT investment surge at 14.87% per year) and comparison with S4 results in the 23-sector model calibrated to 2019 I-O table.
Green AI’s export surge causes real exchange rate appreciation that displaces output in Textiles by 5.5% and in Leather and Footwear by 16.1%, while Heavy Manufacturing expands by 12.9% and IT Hardware by 10.9%.
Sectoral output changes reported from the CGE model under scenario S2 (Green AI) calibrated to Vietnam 2019 I-O table.
The impact of productivity gains differs depending on whether AI production is competitive or monopolistic.
Comparative theoretical analysis in the model contrasting competitive vs monopolistic AI production. No empirical sample reported.
Micro-level efficiency improvements often come at the cost of heightened macro-level fragility.
Theoretical trade-off derived from the dual analytical framework and conceptual argumentation in the paper (no empirical validation reported).
Displacement (asymmetric substitution between brand pairs) was industry-dependent, ranging from co-recommendation in consulting (0.4:1) to one-directional substitution up to 4.3:1, with an unweighted mean of 2.4:1 across the five industries.
Computation of the Displacement Score across brand pairs within each of the five sampled industries; manuscript reports per-industry ratios and the unweighted mean.
Cross-model agreement on the top-recommended brand was 41.6%; a top position on one model did not reliably hold on another.
Empirical comparison of top-recommended brands across the three models for the sampled queries, yielding a 41.6% cross-model agreement rate.
While localized speculation and valuation excesses may exist in AI markets, the underlying economic foundations of the AI cycle differ substantially from those that characterized the collapse of the internet bubble.
Comparative evaluation using financial market data, historical analyses of the dot-com collapse, and contemporary literature cited in the paper (qualitative comparative review).
After 2030, the geography of AI infrastructure will be shaped more by firm power and system flexibility than by the mere abundance of clean energy.
Modelled spatial deployment outcomes across the 21 AI growth scenarios indicating determinant factors for infrastructure siting after 2030.
By redefining discoverability metrics and authority signals, LLM-integrated search ecosystems are reshaping digital marketing economics.
Argumentative claim in the paper linking shifts in discoverability and authority to broader digital marketing economic effects; presented as conceptual synthesis without quantitative evidence in the excerpt.
The rapid integration of large language models (LLMs) into search engines and conversational AI platforms is fundamentally transforming the landscape of search engine optimization (SEO).
Statement in paper's introduction asserting observed integration of LLMs into search engines and conversational platforms; based on conceptual analysis and literature synthesis (no empirical sample or quantified measurement provided).
AI-mediated financial decisions are reflexive: they reshape organizational workflows, prices, liquidity, credit allocation, and the future data on which subsequent decisions rely.
Conceptual argument supported by literature across finance and related fields (review-level synthesis; no single empirical sample size reported).
Our findings show qualitative and enduring differences between hyperscaler-based platforms and non-hyperscaler providers.
Stated as a conclusion based on the paper's taxonomy and comparative analysis; phrasing indicates interpretive/qualitative evidence rather than longitudinal empirical demonstration (no temporal sample or size reported in abstract).
Non-hyperscaler providers embody distinct value-creation logics beyond hyperscaler efficiency.
Claim arises from the taxonomy and comparative analysis contrasting hyperscaler-based platforms with non-hyperscaler alternatives; evidence appears qualitative and conceptual as presented in the paper summary (no empirical sample size reported in abstract).
Widely used conversational systems increasingly function as interfaces through which users access information, digital services, and online markets.
Descriptive claim presented in the recommendations; no quantitative metrics (e.g., usage statistics, market share) or empirical study cited in the text.
The capability-level theory explains when digital modularization extends to organizational disaggregation and when accountability keeps capabilities integrated.
Author claim about the explanatory scope of the developed theory; supported by conceptual argumentation and illustrative examples across several domains rather than empirical tests.
Seven propositions link agentic assembly-cost reductions, accountability assets, appropriability, orchestrator intent capture, and boundary misconfiguration to boundary strategy, value appropriation, and rule debt.
Theoretical development consisting of seven formal propositions in the paper; propositions are reasoned and illustrated but not empirically validated.
Digitalisation is making data and algorithmic systems increasingly important economic resources, thereby changing the way markets operate, how labour is organised, how productivity is measured and how income is distributed.
Conceptual analysis and theoretical model developed via literature synthesis and comparative approach (no empirical sample reported).
The integration of artificial intelligence (AI) agents into payment systems signals a profound shift in the architecture of financial transactions.
Conceptual and technical analysis presented in the paper (argumentative claim in abstract). No empirical sample or quantitative data reported in the abstract.
AI redistributes resource control to stakeholders, challenging the Stakeholder Resource-Based View by changing who holds and controls strategically valuable resources.
Theoretical argument within the Stakeholder Resource-Based View stream; conceptual synthesis asserting redistribution of resource control to external stakeholders and algorithmic actors; no empirical evidence reported.
AI reconfigures ecosystems and platforms around foundation models, shifting how complementary actors interact and altering platform/ecosystem structure.
Analytical review of Ecosystems and Platforms literature; conceptual claim that foundation models act as central coordinating technologies; no empirical data or sample.
Yapay zekâ teknolojilerindeki hızlı ilerleme, küresel üretim ve ticaret organizasyonunu köklü biçimde dönüştürme potansiyeline sahiptir.
Kavramsal değerlendirme ve literatüre dayalı tartışma; çalışmada ampirik örnek veya nicel örneklem sunulmamaktadır.
This lack of focus creates uncertainty about whether regulatory technology helps legitimate economic recovery or instead strengthens exclusion and informality.
Interpretive observation from gaps identified in the reviewed literature; no empirical resolution provided.
The study provides new empirical evidence that technological innovation (specifically generative AI) reshapes financial spillover networks and highlights the importance of considering both the level and structure of connectedness in assessing systemic risk.
Overall empirical results from the TVP-VAR analysis of connectedness across AI equities, cryptocurrencies, and traditional assets, and discussion of implications for systemic risk assessment.
The impact of AI on financial markets is better understood as a structural transformation of interconnectedness rather than a simple intensification of linkages.
Synthesis of empirical findings from the TVP-VAR showing changes in network structure and heterogeneous directional roles across asset groups, rather than a monotonic increase in aggregate connectedness.
The structure of spillovers undergoes significant changes over the sample period.
TVP-VAR estimated time-varying spillover/connectedness network showing changes in directional spillovers and network topology (paper states 'significant changes').
The strategic interplay between antitrust regulation and vertical integration materially influences the evolutionary transitions of the computing power ecosystem.
Core focus of the paper's tripartite evolutionary game model which explicitly models government regulators, incumbents, and downstream innovators and analyzes resulting equilibria and transitions (method: theoretical evolutionary game + analytical derivation).
The evolution of the AI computing power innovation ecosystem manifests distinct stage-based progressions and threshold-driven bifurcation characteristics, potentially transitioning from an initial 'natural monopoly and passive dependence' state through intermediary states (e.g., 'comfort zone trap' or 'regulatory stalemate') toward a mature configuration of 'co-opetition and endogenous growth.'
Derived from the paper's tripartite evolutionary game model and analytical derivation of evolutionarily stable strategies, with supporting numerical simulations exploring parametric sensitivities (method: theoretical evolutionary game + numerical simulation).
The computing power industry is undergoing a paradigm shift from traditional linear supply chains toward complex, interdependent innovation ecosystems driven by the rapid proliferation of generative artificial intelligence.
Conceptual claim presented in the paper's introduction/motivation; supported by the paper's theoretical framing and literature-based motivation rather than empirical data (method: narrative/theoretical framing).
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.
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.
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.
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 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.
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).
Analysis of more than two decades of M&A deals reveals shifts in acquisition activity and allows mapping of corporate linkages and overlapping investments.
Empirical longitudinal analysis of M&A deals over a period exceeding 20 years; method: mapping corporate linkages from M&A data (sample size/dataset not specified in the excerpt).
AI is becoming a geopolitical tool that defines trade, finance, supply chains, surveillance abilities, and diplomatic bargaining power.
Conceptual/qualitative synthesis in the paper's argument; no empirical methods or sample size reported in the abstract.
Targeted prompt interventions significantly alter the magnitude of market bubbles (they can amplify or suppress bubble size).
Randomized (or otherwise experimentally manipulated) prompt interventions applied to LLM agents in the simulated open-call auction, with resulting differences in measured bubble magnitude reported.
Outcomes are shaped not only by benchmark quality but also by competitive pressure, including user switching, routing decisions, and operational constraints.
Argument/assertion in paper framing motivations for Marketplace Evaluation; conceptual reasoning listing mechanisms (user switching, routing, operational constraints); no empirical tests or sample size reported.
The organization of AI innovation differs sharply: U.S. AI patenting is concentrated among large private incumbents and established hubs, whereas Chinese AI patenting is more geographically diffuse and institutionally diverse, with larger roles for universities and state-owned enterprises.
Analysis of assignee types, geographic dispersion, and institutional composition of AI patents in the two countries (concentration metrics and assignee categorizations described in paper).
Algorithmic credit scoring is being transformed by new actors, techniques, and shifting regulations.
Ethnographic fieldwork documenting the entry of new actors, novel technical techniques, and regulatory changes affecting credit scoring in Nairobi's digital lending ecosystem.
Professional and Technical Services, Information, and Finance and Insurance account for approximately 86 percent of the base-case direct contribution.
Sectoral decomposition of base-case direct contribution in the model; paper explicitly reports the three sectors' combined share as ~86%.
The positive effect of big data applications on firms' markups exhibits heterogeneity across organizational, technological, and environmental dimensions.
Paper reports heterogeneity analysis showing variation in the magnitude of the positive markup effect across organizational, technological and environmental factors; based on model implications and empirical subgroup/interaction tests using micro-level firm data (sample size not reported).
Three analytical results characterise non-linear financial fragility, regime-contingent risk premium divergence, and the general equilibrium alignment squeeze.
Stated analytical results in the paper derived from the theoretical model describing three named phenomena (non-linear fragility, regime-contingent divergence, alignment squeeze).
Whether AI is equity-bullish or equity-bearish depends on which channel dominates—a condition that differs sharply between deep financial markets, where the ARP is the dominant driver of elevated risk premia (Regime D), and shallow markets, where participation compression dominates (Regime E).
Model regime analysis in the paper distinguishing Regime D (deep markets, ARP-dominated) and Regime E (shallow markets, participation-compression-dominated) and stating comparative dominance determines net bullish/bearish outcome.
The equilibrium equity risk premium decomposes into three additively separable terms corresponding to these three channels (Proposition 1).
Formal proposition (Proposition 1) in the paper deriving an additive decomposition of the equilibrium ERP into the productivity, participation compression, and alignment risk terms.
We develop a heterogeneous-agent framework in which AI-driven labour displacement affects the equity risk premium (ERP) through three co-equal channels.
Stated model contribution in the paper: a theoretical heterogeneous-agent framework that posits three channels linking AI-driven labour displacement to the ERP (productivity, participation compression, alignment risk).
The paper draws comparisons between inference tokens and established commodities such as electricity, carbon emission allowances, and bandwidth to motivate financialization.
Theoretical comparison and historical analysis (drawing on the historical experience of electricity futures markets and commodity financialization theory) as presented in the paper.
The fragility of 'Pax Silica' has implications for global capitalism, technological governance, and geopolitical stability.
Analytical inference and concluding assessment based on theoretical framework and comparative analysis; no empirical quantification provided in the abstract.