Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
2Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5067703538
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Sharma Anil Kumar (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Skill Acquisition: 1 paper
- Automation Exposure: 1 paper
- Employment: 1 paper
- Governance And Regulation: 1 paper
- Other: 1 paper
- Research Productivity: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| AI's impact on jobs is uneven: routine-heavy industries face the greatest automation risk, whereas knowledge sectors see augmentation and rising skill demands. Policymakers and firms must prioritize targeted re-skilling and sectoral risk assessments to manage workforce transitions.openalex | Sharma Anil Kumar provider id |
2026-04-23 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.