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
1Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5146401511
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Amanda Acevedo (openalex, provider refresh)
- Amanda Acevedo (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Adoption Rate: 1 paper
- Employment: 1 paper
- Output Quality: 1 paper
- Ai Safety And Ethics: 1 paper
- Decision Quality: 1 paper
- Governance And Regulation: 1 paper
- Hiring: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Generative and agentic AI are shifting audit work from routine testing to oversight and judgment, improving coverage but endangering the traditional entry-level training ladder; firms that redesign roles, governance, and training to enforce ‘digital skepticism’ will be best placed to protect audit quality and future leadership pipelines.openalex | Amanda Acevedo provider id |
2026-08-11 | 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.