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
4Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
1387190718
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Christophe Combemale (semantic scholar, provider refresh)
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
- Firm Productivity: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar 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 |
|---|---|---|---|
| Deep AI use among S&P 500 firms surged from about 5% in 2022 to 11% in 2025, driven overwhelmingly by technology companies that account for two-thirds of deep adopters; adopters show a J‑shaped relationship with profitability but no clear change in capital spending or standard productivity measures.arxiv | Christophe Combemale provider id |
2026-07-09 | 0 |
Citation observation summary
Semantic Scholar 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.