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
3Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5121041299
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Arif Uz Zaman Khan (openalex, provider refresh)
- Arif Uz Zaman Khan (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Organizational Efficiency: 1 paper
- Innovation Output: 1 paper
- Firm Revenue: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Other: 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 |
|---|---|---|---|
| Companies that build comprehensive AI capabilities outperform peers, showing a roughly 10.7 percentage-point shareholder return premium, but only about 1% reach maturity. The study finds organizational redesign and workflow reconfiguration—not plug-in tools—are the critical bottlenecks as many firms abandon AI efforts due to data, skills, and integration challenges.openalex | Arif Uz Zaman Khan provider id |
2025-12-25 | 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.