Evidence (14055 claims)

Evidence Matrix

Claim counts by outcome category and direction of finding.

Outcome	Positive	Negative	Mixed	Null	Total
Other	758	199	100	900	2007
Governance & Regulation	826	400	191	122	1563
Organizational Efficiency	777	193	124	84	1189
Technology Adoption Rate	635	233	124	97	1098
Research Productivity	422	128	57	336	954
Output Quality	476	179	59	47	761
Decision Quality	328	177	81	47	640
Firm Productivity	435	57	88	20	606
AI Safety & Ethics	218	277	65	33	599
Market Structure	180	170	123	24	502
Task Allocation	213	64	72	33	387
Skill Acquisition	170	61	61	17	309
Innovation Output	203	27	43	18	292
Employment Level	105	54	107	13	281
Fiscal & Macroeconomic	131	69	43	26	276
Consumer Welfare	117	63	42	11	233
Firm Revenue	153	48	26	3	230
Task Completion Time	173	31	8	12	225
Inequality Measures	44	122	49	6	221
Worker Satisfaction	89	65	22	12	188
Error Rate	69	92	10	2	173
Regulatory Compliance	77	69	14	5	165
Automation Exposure	56	56	26	13	154
Training Effectiveness	94	21	13	19	149
Wages & Compensation	77	36	25	6	144
Team Performance	86	17	27	10	141
Developer Productivity	95	17	14	6	133
Job Displacement	12	80	20	1	113
Hiring & Recruitment	52	7	8	3	70
Creative Output	31	18	8	3	61
Skill Obsolescence	5	46	6	1	58
Social Protection	27	16	8	2	53
Labor Share of Income	17	19	17	—	53
Worker Turnover	11	12	—	3	26
Industry	—	—	—	1	1

Research gaps include the need for causal evaluations (RCTs or quasi-experiments) of bundled interventions (training + placement + income support), cross-country comparisons of informality's moderating role, and better data on platform employment dynamics.

Identified research agenda and priorities summarized from the literature review and gap analysis in the paper; recommendation rather than empirical finding.

speculative positive Who Loses to Automation? AI-Driven Labour Displacement and t... evidence on effectiveness of bundled interventions and cross-country moderation ...

Empirical work on automation should distinguish task vs job displacement, measure platform algorithmic effects on labour demand, and quantify fallback employment options available to displaced informal workers.

Methodological recommendation based on gaps identified in the reviewed literature and limitations of existing studies; no new data collection presented.

speculative positive Who Loses to Automation? AI-Driven Labour Displacement and t... quality of empirical measurement (ability to isolate task vs job displacement an...

Policy responses should go beyond reskilling to include mechanisms addressing informality and job quality (e.g., portable benefits, minimum standards for platforms, guaranteed work or public employment schemes, wage floors, and training linked to placement).

Policy recommendation synthesized from literature on platform labour, social protection, and training program design; normative prescription rather than empirically validated intervention within this paper.

speculative positive Who Loses to Automation? AI-Driven Labour Displacement and t... worker welfare and employment security under combined policy interventions

Unchecked shifts toward K_T-dominated production can amplify political risks (rising inequality, fiscal strain) that may fuel populism, protectionism, and demands for renegotiated social contracts.

Theoretical political‑economy discussion supported by historical analogies and model scenarios linking fiscal stress and distributional change to political-instability risks; qualitative case evidence.

speculative positive The Macroeconomic Transition of Technological Capital in the... political risk indicators (populist support, policy volatility) — discussed qual...

To make AI a driver of structural change, policy interventions must link AI investment to comprehensive energy subsidy reform and accelerated development of the new and renewable energy sector.

Policy recommendation based on integrated analysis showing that subsidy burdens and import dependence limit AI's macro impact; proposed linkage is derived from the study's scenario/logic assessment.

speculative positive (conditional) AI-Based Technological Transformation as a Driver for Develo... potential for AI to drive structural change conditional on subsidy reform and re...

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