{
  "id": 19111,
  "url": "https://arxiv.org/abs/2608.12352",
  "title": "Why AI Governance Frameworks Are Hard to Adopt: A Role-Based Stress Test of the NIST AI RMF",
  "summary": "arXiv:2608.12352v1 Announce Type: new Abstract: AI governance frameworks can be known, used, and implemented in form without becoming governance in practice. This paper examines that problem through a role-based stress test of the NIST Artificial Intelligence Risk Management Framework (AI RMF) in consumer lending. We treat framework adoption as a governance translation problem: whether RMF language can become role-usable, cross-level, authority-connected governance over the AI system-in-use, rat",
  "authors": "Joseph R. Simons, David A. Broniatowski",
  "category": "research",
  "topics": "regulation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-14T04:00:00.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/19111",
  "original_url": "https://arxiv.org/abs/2608.12352",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}