Evidence (13870 claims)
Adoption
8467 claims
Productivity
7558 claims
Governance
6805 claims
Human-AI Collaboration
6363 claims
Org Design
4132 claims
Innovation
4065 claims
Labor Markets
3526 claims
Skills & Training
2945 claims
Inequality
2066 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 749 | 196 | 98 | 892 | 1984 |
| Governance & Regulation | 817 | 394 | 188 | 121 | 1544 |
| Organizational Efficiency | 771 | 189 | 124 | 83 | 1177 |
| Technology Adoption Rate | 627 | 233 | 123 | 96 | 1088 |
| Research Productivity | 411 | 123 | 56 | 332 | 933 |
| Output Quality | 467 | 178 | 59 | 47 | 751 |
| Decision Quality | 320 | 174 | 75 | 42 | 618 |
| Firm Productivity | 435 | 55 | 88 | 20 | 604 |
| AI Safety & Ethics | 214 | 276 | 65 | 33 | 593 |
| Market Structure | 178 | 167 | 122 | 24 | 496 |
| Task Allocation | 207 | 64 | 71 | 32 | 379 |
| Skill Acquisition | 165 | 59 | 60 | 17 | 301 |
| Innovation Output | 203 | 27 | 43 | 18 | 292 |
| Employment Level | 105 | 52 | 107 | 13 | 279 |
| Fiscal & Macroeconomic | 131 | 69 | 43 | 26 | 276 |
| Consumer Welfare | 116 | 63 | 42 | 11 | 232 |
| Firm Revenue | 150 | 48 | 26 | 3 | 227 |
| Inequality Measures | 44 | 122 | 49 | 6 | 221 |
| Task Completion Time | 169 | 29 | 8 | 12 | 219 |
| Worker Satisfaction | 89 | 63 | 20 | 12 | 184 |
| Error Rate | 69 | 92 | 10 | 2 | 173 |
| Regulatory Compliance | 76 | 68 | 14 | 5 | 163 |
| Training Effectiveness | 93 | 21 | 13 | 19 | 148 |
| Wages & Compensation | 77 | 36 | 25 | 6 | 144 |
| Automation Exposure | 51 | 54 | 22 | 12 | 142 |
| Team Performance | 86 | 17 | 27 | 9 | 140 |
| Developer Productivity | 94 | 17 | 14 | 6 | 132 |
| Job Displacement | 12 | 80 | 20 | 1 | 113 |
| Hiring & Recruitment | 51 | 7 | 8 | 3 | 69 |
| Creative Output | 31 | 17 | 7 | 3 | 59 |
| Skill Obsolescence | 5 | 46 | 6 | 1 | 58 |
| Social Protection | 27 | 16 | 8 | 2 | 53 |
| Labor Share of Income | 17 | 17 | 17 | — | 51 |
| Worker Turnover | 11 | 12 | — | 3 | 26 |
| Industry | — | — | — | 1 | 1 |
Twelve testable hypotheses are proposed, with implications for agentic AI oversight and human-AI collaboration.
Paper statement that it proposes twelve testable hypotheses; verifiable by counting hypotheses in the paper.
Convolutional neural networks achieved 95.4% accuracy in identifying ulcers and hemorrhages.
Specific result reported from an included study using convolutional neural networks (accuracy = 95.4%) as cited in the review.
Technological innovation is the primary mediating mechanism through which NQPF affects supply chain efficiency, accounting for 84.6% of the effect.
Mediating-effect models applied to the 2012–2022 panel data (Shanghai and Shenzhen A-share listed firms) estimating mediation proportions; technological innovation mediation proportion reported as 84.6%.
New quality productivity forces (NQPF) significantly improve supply chain efficiency.
Empirical analysis using 2012–2022 panel data of Shanghai and Shenzhen A-share listed companies; results robust to robustness tests and reported as statistically significant in main regressions.
Persistent environmental state induces history sensitivity (dependence of long-run behavior on past trajectories and initial conditions) unless the overall system is globally contracting.
Formal theorem and proof showing that persistence of environmental variables creates non-autonomous/memory-dependent closed-loop behavior, and that only the special case of global contraction removes this history dependence (mathematical analysis of sensitivity to initial conditions).
Under dissipativity assumptions the induced closed-loop system admits a bounded forward-invariant region, guaranteeing viability of the dynamics without requiring global optimality.
A proven structural result (theorem) in the paper: mathematical proof using dissipativity hypotheses on components of the feedback architecture showing existence of a bounded forward-invariant set for the closed-loop dynamics. (The claim is theoretical; no empirical sample size.)
AI tools—ranging from machine learning algorithms in inventory management to natural language processing in customer engagement—are applied in micro‑enterprise contexts.
Descriptive synthesis from included articles reporting specific AI applications (ML for inventory management; NLP for customer engagement) across the reviewed literature.
Global efforts toward establishing shared norms and multilateral cooperation are underway through initiatives led by the United Nations, OECD, UNESCO, and G7.
Qualitative document review identifying initiatives and normative efforts by multilateral organizations (organizations named; specific initiatives referenced qualitatively but not enumerated as a dataset).
We demonstrate three distinct workflows across five environments.
Paper lists and evaluates five target environments and describes three workflows (direct translation, translation verified against existing performance implementations, and new environment creation). Sample size: five environments.
These trends (increased demand for complementary skills and decreased demand for substitutable skills) hold across geographies including the United States, United Kingdom, and Australia, demonstrating robustness.
Replication/comparison of results within the dataset’s country-specific subsamples (US, UK, Australia) drawn from nearly 30 million job postings collected between 2018 and 2024.
AI-intensive roles are significantly more likely to require complementary non-technical capabilities such as analytical thinking, resilience, and digital literacy.
Empirical analysis of a dataset of nearly 30 million job postings from the United States, the United Kingdom, and Australia between 2018 and 2024; roles classified as AI-intensive and skill mentions extracted from job postings to compare prevalence of non-technical capabilities.
Mainstreaming shared input and embracing climate-resilient management approaches are fundamental action items for building institutional resilience.
Paper conclusion lists these recommended action items based on its analysis of governance and sustainability linkages grounded in SDG and global governance literature; the summary does not indicate empirical testing of these recommendations.
The study builds and calibrates an integrated system dynamics model that connects demographics, labor supply, economic output, and public finance.
Method: development and calibration of a system dynamics model using official statistics for demographics, labor, output, and fiscal variables (model structure and calibration described in paper).
The paper ends with policy implications and recommends periodic evaluation and the integration of AI-related risks into financial governance.
Policy recommendations section in the paper advocating for periodic evaluation and AI-risk integration into financial governance (method: prescriptive/policy analysis based on review findings).
Specialized SDE services that require further study are grouped and highlighted.
Section of the paper grouping and highlighting specialized services for future research (method: expert-driven identification from review; no quantitative prioritization stated).
We introduce a concise conceptual model of a 'shadow' project for designing SDE products or services, detailing participant roles and project composition.
Presentation of a conceptual model within the paper (method: model construction and descriptive exposition; no empirical testing/sample).
The paper proposes a clear classification of criminally oriented products and services in the SDE.
Taxonomy/classification produced in the paper (method: conceptual taxonomy from literature and analysis; no quantitative validation reported).
We identify a structured set of labor‑market roles within the SDE model.
Analytical identification and description of roles within the paper (method: conceptual modeling and qualitative role-mapping; sample size N/A).
We propose an integrated definition of the shadow digital economy that synthesizes technical and economic definitions.
Conceptual analysis and literature synthesis in the paper that combines technical and economic definitions into a single integrated definition (method: review/synthesis; no numeric sample).
Regional peer effects of DT improve firms' resource allocation (RA), which in turn bolsters enterprise resilience (ER).
Mediation/ mechanism analysis on the 2013–2022 Chinese A-share manufacturing panel showing that RA mediates the relationship between regional peer DT and ER.
Industrial peer effects of DT enhance firms' innovation capability (IC), which in turn strengthens enterprise resilience (ER).
Mediation/ mechanism analysis on the same 2013–2022 Chinese A-share manufacturing panel showing that IC mediates the relationship between industrial peer DT and ER.
Digital transformation (DT) exhibits significant industrial and regional peer effects.
Empirical analysis using panel data of Chinese manufacturing enterprises listed on the Shanghai and Shenzhen A-share markets from 2013 to 2022; peer-effect regressions conducted within interlocking directorate networks (IDNs).
AI significantly enhances supplier stability in sports enterprises (SE).
Empirical estimation using a dual machine learning (DML) model on panel data of 45 Chinese listed sports enterprises (2012–2023); authors report a statistically significant positive effect of AI on supplier stability.
Extending existing behavioral frameworks (e.g., TAM, JD–R, Organizational Trust) to the AI-augmented workplace constitutes a theoretical contribution of the paper.
Theoretical elaboration and integration presented in the paper; contribution characterized as an extension of pre-existing models to AI contexts (no quantitative validation described in the summary).
The paper proposes a five-phase strategic roadmap for phased organizational implementation that integrates HRM practice redesign, psychological support systems, and evidence-based governance mechanisms.
Prescriptive/strategic proposal based on the paper's theoretical synthesis and applied recommendations (roadmap described in the paper; summary contains no implementation trial data).
The paper develops a comprehensive, multi-dimensional organizational psychology framework for preparing the U.S. workforce for AI integration composed of six interdependent dimensions: human–AI symbiosis, trust and transparency, job redesign, AI-enabled recruitment and selection, learning and adaptation, and ethical AI governance.
Conceptual framework derived from theoretical integration (TAM, Human–AI Symbiosis Theory, JD–R Model, Organizational Trust Theory) and review of AI–HRM literature; framework construction is a theoretical contribution of the paper (no empirical validation reported in the summary).
Grid-Scale Battery Energy Storage Systems (GS-BESS) play a crucial role in modern power grids, addressing challenges related to integrating renewable energy sources (RESs), load balancing, peak shaving, voltage support, load shifting, frequency regulation, emergency response, and enhancing system stability.
Synthesis of prior literature reported in this systematic review (methodology: literature review following PRISMA guidelines). The excerpt does not specify the number or identity of primary studies summarized for this claim.
General US employment for prime age workers (age 25–54) is currently high (~80%).
Paper cites a current employment rate of 80% for prime-age workers; likely based on national labor statistics though the exact data source and year are not specified in the excerpt.
The growth effect of AI exhibits industry heterogeneity: high‑tech manufacturing industries benefit more significantly.
Heterogeneity/subgroup regressions on the 2003–2017 Chinese industry panel showing larger estimated AI effects in high‑tech manufacturing sectors.
The positive effect of AI on industry growth increases over time.
Dynamic/DID analysis across the 2003–2017 panel showing that the estimated treatment effect grows larger in later periods.
The industry growth rate of the treatment group (industries with intensive AI application or high AI patent concentration) is significantly higher than that of the control group.
DID comparison between treatment and control industry groups in the China 2003–2017 panel, where treatment is defined by intensive AI application or AI patent concentration.
AI technology innovation has a significant positive impact on economic growth.
Industry panel data for Chinese industries from 2003 to 2017 analyzed using a differences-in-differences (DID) approach; main specification estimates effect of AI-related innovation on economic growth.
There is a significant positive direct relationship between Generative AI (GenAI) adoption and business performance.
PLS-SEM results from the cross-sectional survey (n = 312) showing a statistically significant positive path coefficient from GenAI adoption to business performance.
One-way ANOVA confirmed that observed improvements in yield, water use, WUE, and energy consumption were highly significant.
Statistical validation reported as one-way ANOVA with F and p values for wheat yield (F(1,18)=1335.66, p<0.001), water use (F(1,18)=15228.16, p<0.001), WUE (F(1,18)=13065.49, p<0.001), and energy consumption (F(1,18)=24312.67, p<0.001). Degrees of freedom imply 20 total observations (df between=1, df within=18).
Water-use efficiency (WUE) improved by 109% under AI-assisted irrigation (ANOVA F(1,18) = 13065.49, p < 0.001).
Reported WUE improvement percentage and one-way ANOVA treatment effect for WUE: F(1,18) = 13065.49, p < 0.001 from the field experiments.
AI-assisted irrigation decreased energy consumption by 30% (p < 0.001).
Field experiment results with one-way ANOVA showing treatment effect for energy consumption: F(1,18) = 24312.67, p < 0.001. Percentage change reported in the paper.
AI-assisted irrigation reduced water use by 36% (p < 0.001).
Field experiment results with one-way ANOVA showing treatment effect for water use: F(1,18) = 15228.16, p < 0.001. Percentage change reported directly in the paper.
AI-assisted irrigation increased wheat yield by 35% (p < 0.001).
Field experiment results with one-way ANOVA showing treatment effect for wheat yield: F(1,18) = 1335.66, p < 0.001. Percentage change reported directly in the paper.
State-owned enterprises and high-tech firms with robust digital infrastructure experience the largest productivity and innovation gains from AI adoption, indicating absorptive capacity matters.
Heterogeneity analysis on the same panel data comparing subgroups (state-owned vs. non-state-owned; high-tech vs. others; firms with stronger digital infrastructure), showing larger estimated AI effects in those subgroups.
Adoption of AI strengthens firms' innovation outcomes.
Same panel dataset (A-share-listed design firms, 2014–2023) with AI indicators derived from annual reports and patent texts; regression analyses linking AI indicator to innovation metrics (patent-related measures and/or firm-level innovation proxies referenced in the study).
Integrating AI technologies significantly enhances Total Factor Productivity (TFP) in design-oriented, project-based firms.
Panel regression analysis using firm-level panel data of A-share-listed design-oriented enterprises in China (2014–2023). AI exposure measured via an enterprise-level AI indicator constructed from NLP-based text analysis of annual reports and patents; TFP estimated at the firm level as the dependent variable. Robustness checks (e.g., Propensity Score Matching) reported.
The weeder was equipped with a Raspberry Pi microcontroller and a camera module to detect crops and weeds in real-time, enabling autonomous operation.
Design description in the paper: hardware integration of Raspberry Pi and camera module for real-time detection (method: system design and implementation). No sample size or quantitative test data reported for detection accuracy in the provided summary.
AI adoption in Slovakia increased across all enterprise size classes between 2021 and 2024.
Analysis of harmonised Eurostat enterprise-level adoption indicators for 2021–2024 using descriptive statistics and dynamics-of-change methods, disaggregated by enterprise size class. (Sample: enterprises in Slovakia as reported in Eurostat; exact n not specified in the paper summary.)
Platform work accounts for 12.8% of labor income for participants in the studied sample.
Earnings and income calculations using platform transaction records combined with labor force survey and administrative income data for the 24-country sample (2015–2025).
Platform-mediated gig work has grown to represent 4.2% of total employment across 24 OECD countries (2015–2025).
Aggregate analysis of administrative data, national labor force surveys, and platform transaction records covering 24 OECD countries over the 2015–2025 period.
The study moves beyond treating AI as a monolith by empirically investigating how distinct AI features jointly influence the consumer decision journey.
Methodological claim supported by the study's modeling of three specific AI feature constructs (recommendation engines, chatbots, comparison tools) and analyzing their joint effects via SEM on decision-related outcomes.
Medicaid, as the largest public purchaser of healthcare services in the United States, occupies a strategic position to drive systemic change through its supply chain.
Descriptive evidence from publicly available statistics and literature on Medicaid's scale and purchasing role (cited policy/literature sources within the paper); conceptual argument linking purchasing scale to leverage in supply chains.
AESP is implemented as an open-source TypeScript SDK with 208 tests and ten modules.
Implementation claim in the paper: TypeScript SDK, 208 tests, ten modules; verifiable by inspecting the repository and test suite.
AESP is built on an ACE-GF-based cryptographic substrate.
Paper states ACE-GF is used as the cryptographic substrate; implementation referenced in SDK.
AESP employs HKDF-based context-isolated privacy with batched consolidation.
Cryptographic design described in the paper; HKDF-based isolation and batched consolidation listed as mechanisms.