Integration Governance and Accountability [INT-07]
Integration Governance and Accountability defines who may approve, change, pause, expand or retire AI participation in work. It applies decision rights and evidence to behaviour-changing configurations, ongoing health, shadow integration and readiness gates at increases in operating exposure.
Workflow integration needs clear operational ownership. Connect AI action boundaries, service responsibilities and escalation routes across teams and systems.
Explore the holistic AIDIVE frameworkWhy this matters
Prompts, permissions, thresholds, models and tool settings can change production behaviour without an application release. Governance must track their operational effect and remain active after deployment.
Questions to bring to the work
- Who may authorise this change in participation or exposure, and what evidence is required?
- Can the organisation reconstruct the configuration, approval and result of a material operating change?
Explore this chapter
I.7.1Ownership and Decision Rights Across Human, AI and System FlowsKeep one named outcome-accountable role while separating the people, agents and systems that prepare, approve, validate or execute the work.
I.7.2Change Classes, Approval Rights and TransitionRoute prompts, models, thresholds, permissions and tool changes according to their potential operating effect, with clear approval and transition rights.
I.7.3Audit Trail and End-to-End TraceabilityDesign evidence around the questions reviewers must answer about material operating and governance events, with sensitivity and retention constraints.
I.7.4Oversight, Escalation and Health ReviewsMaintain post-deployment review with evidence, cadence or triggers, authority and follow-through for as long as material exposure remains.
I.7.5Governance of Shadow and Ungoverned IntegrationAssign authority and a lifecycle decision to material ungoverned integration, based on its operating exposure rather than visibility alone.
I.7.6Staged Readiness GatesRequire proportionate fresh evidence before moving to production, broader populations, Act authority, wider tools or additional operating contexts.
What useful evidence looks like
- Change-class and approval records for prompts, models, tools, permissions and orchestration.
- Readiness and health-review evidence showing conditions, owners, follow-through and authority to narrow or stop expansion.
Move from understanding to practice
AR-I16AR-I16 · Integration Governance and Accountability Setup
AR-I17AR-I17 · Integration Maturity Calibration
AR-I18AR-I18 · 90-Day Integration Improvement Roadmap
Framework source
Editorial adaptation from the supplied AIDIVE Version 1 master documents.
- AIDIVE Integration Dimension Version-1.docx · I.7 Integration Governance and Accountability [INT-07]; AIDIVE Integration - Practices & Playbook Version-1.docx · AR-I16, AR-I17, AR-I18
Integration
Dimension overview ↗01Enterprise Work, Decisions and AI Participation02AI Participation, Autonomy and Controls03Context Continuity Across the Flow04Operational Continuity, Resilience and Fragility05Integration Estate: Systems, Tools, Identity and Observability06Decision-to-Execution and Closed-Loop Learning07Integration Governance and Accountability [INT-07]Find a practiceLEARN. CONTRIBUTE. APPLY.Put AI transformation
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