Judgment Assurance Adoption Pathway

Abstract

Judgment Assurance Adoption Pathway The Judgment Assurance Adoption Pathway introduces a phased governance progression for organizations navigating AI-enabled operations and consequential AI-mediated decision-making. The Pathway is designed to help institutions understand that Judgment Assurance is not intended as a starting point for all organizations, but rather as a Phase 3 governance discipline that builds upon foundational visibility and prioritization activities. The framework organizes institutional AI governance progression into three broad phases: Phase 1: AI Visibility & DiscoveryIdentification of AI systems, tools, workflows, vendor-embedded AI, shadow AI usage, and institutional data movement. Phase 2: Consequentiality MappingIdentification of workflows where AI materially influences consequential institutional decisions, including assessment of operational reliance, escalation structures, and potential institutional impact. Phase 3: Judgment GovernanceImplementation of attributable, reviewable, and evidentiary governance over human judgment within consequential AI-mediated decisions through the application of Judgment Assurance controls, evidence structures, and oversight mechanisms. The document also clarifies an important conceptual distinction: organizations asserting “human oversight” or “human-in-the-loop” governance over consequential AI-mediated decisions are implicitly making Phase 3 governance claims and should ensure that appropriate evidentiary and accountability structures exist to support those assertions. This publication is intended to serve as an implementation and onboarding bridge between high-level AI governance concepts and operational Judgment Assurance governance architecture.

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