Why AI Governance Frameworks Are Hard to Adopt: A Role-Based Stress Test of the NIST AI RMF
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
Record details
Published: 14 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Regulation
Retrieved: 14 August 2026
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ethics.ai (14 August 2026), “Why AI Governance Frameworks Are Hard to Adopt: A Role-Based Stress Test of the NIST AI RMF,” evidence record 19111, https://ethics.ai/record/19111 (originally published by arXiv cs.CY).
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