Evidence (3103 claims)

Evidence Matrix

Claim counts by outcome category and direction of finding.

Outcome	Positive	Negative	Mixed	Null	Total
Other	378	106	59	455	1007
Governance & Regulation	379	176	116	58	739
Research Productivity	240	96	34	294	668
Organizational Efficiency	370	82	63	35	553
Technology Adoption Rate	296	118	66	29	513
Firm Productivity	277	34	68	10	394
AI Safety & Ethics	117	177	44	24	364
Output Quality	244	61	23	26	354
Market Structure	107	123	85	14	334
Decision Quality	168	74	37	19	301
Fiscal & Macroeconomic	75	52	32	21	187
Employment Level	70	32	74	8	186
Skill Acquisition	89	32	39	9	169
Firm Revenue	96	34	22	—	152
Innovation Output	106	12	21	11	151
Consumer Welfare	70	30	37	7	144
Regulatory Compliance	52	61	13	3	129
Inequality Measures	24	68	31	4	127
Task Allocation	75	11	29	6	121
Training Effectiveness	55	12	12	16	96
Error Rate	42	48	6	—	96
Worker Satisfaction	45	32	11	6	94
Task Completion Time	78	5	4	2	89
Wages & Compensation	46	13	19	5	83
Team Performance	44	9	15	7	76
Hiring & Recruitment	39	4	6	3	52
Automation Exposure	18	17	9	5	50
Job Displacement	5	31	12	—	48
Social Protection	21	10	6	2	39
Developer Productivity	29	3	3	1	36
Worker Turnover	10	12	—	3	25
Skill Obsolescence	3	19	2	—	24
Creative Output	15	5	3	1	24
Labor Share of Income	10	4	9	—	23

Human Ai Collab Remove filter

Firms with large, integrated datasets and standardized processes can gain disproportionate returns, creating potential scale economies and winner-take-most dynamics.

Resource-based theoretical interpretation and illustrative patterns in the reviewed literature; the paper notes empirical evidence is limited and calls for further study.

speculative positive Integrating Artificial Intelligence and Enterprise Resource ... scale-dependent returns (e.g., differential ROI by firm data scale/integration l...

Explainable EEG tools can shift clinician workflows by enabling faster decision-making and reducing the requirement for specialized interpretation, with implications for training, staffing, and productivity.

Projected operational impacts discussed as implications of improved explainability; no longitudinal workflow study provided in the reviewed literature.

speculative positive Explainable Artificial Intelligence (XAI) for EEG Analysis: ... clinician workflow efficiency, training/staffing needs, productivity

Policy and managerial implication suggested: investing in short, targeted onboarding/training for GenAI tools (rather than only providing access) may deliver measurable performance gains and increase voluntary adoption.

Authors derive this implication from the randomized trial results showing increased adoption and improved scores with brief training (n = 164); this is an extrapolation from the trial findings.

speculative positive Training for Technology: Adoption and Productive Use of Gene... Organizational adoption and productivity (extrapolated from student trial outcom...

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