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
0Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5068580433
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Kakhramon Khakberdiev (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Productivity: 1 paper
Claim outcomes
- Decision Quality: 1 paper
- Error Rate: 1 paper
- Governance And Regulation: 1 paper
- Organizational Efficiency: 1 paper
- Regulatory Compliance: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| Multinationals that adopt AI for governance and risk report large operational gains — 20% fewer disruptions, 30% better compliance accuracy and decisions 40% faster — while AI risk models outperform traditional approaches (92% vs 75% accuracy); however, results stem from an observational comparison with limited causal identification.semantic_scholar | Kakhramon Khakberdiev provider id |
Fetched 2026-07-06 | 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.