Governing at Machine Speed: An Adaptive Intelligence Architecture for Real-Time AI Policy Enforcement

arXiv cs.AIen

Governing at Machine Speed: An Adaptive Intelligence Architecture for Real-Time AI Policy Enforcement

arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifies and characterizes the attestation deficit, a structural condition in which organizations maintain governance policies but cannot produce auditable, tamper-evident evidence of enforcement within regulatory timelines. Drawing on empirical data from the Stanford 2026 AI Index Report (362 documented incidents), the IBM/Ponemon 2026 Cost of a Data Breach study (USD 4.99M average cost, 92% lacking access controls), and the EY/AIUC-1 Consortium survey (38% end-to-end monitoring, 17% agent-to-agent co

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  • Forskning
  • Agenter
  • Reglering

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