From Awareness to Institutionalization: A Change Management Framework for Organizational AI Epistemic Governance

This paper presents the organizational deployment layer of the AI Epistemic Governance Stack. While Papers 7–9 establish the theoretical, accountability, and enforcement foundations (AI Behavior Science, AEAL, and ZTEK), Paper 10 provides the change management framework required for real‑world adoption. The framework consists of five phases—Awareness, Assessment, Pilot, Institutionalization, and Continuous Improvement—each with defined deliverables, resistance patterns, and success criteria. The paper introduces the Epistemic Risk Map, a standalone tool for identifying where unverified AI output enters organizational workflows, and includes a pilot vignette with measurable before/after metrics from a multi‑year AI‑assisted research program. This work is intended for CIOs, AI governance leads, research directors, compliance teams, and organizational leaders responsible for deploying AI at scale.