Governance Gap Closure: Assign accountability owners for each production AI system. Schedule structured review cycles aligned to NIST AI RMF 'Govern' and 'Measure' functions. Document and escalate any system where control assurance cannot be established.
Post-Incident
NIST 800-61r3 §4 — Post-Incident Activity: Lessons learned and governance improvement are post-incident functions; however, in the context of a structural governance gap (no active breach, but no control assurance), this step functions as a proactive post-assessment remediation cycle — the 'incident' is the discovery of uncontrolled AI systems, and closure is the corrective action phase equivalent to post-incident improvement.
NIST IR-4 (Incident Handling) — incident handling capability for AI systems requires named owners; without accountability assignment, there is no defined escalation path when an AI system behaves unexpectedly
NIST IR-8 (Incident Response Plan) — IR plan must be updated to include AI-specific roles: AI system owner, model risk officer, AI pipeline engineer, and escalation path to CISO for autonomous AI incidents
NIST IR-6 (Incident Reporting) — establish reporting thresholds for AI governance events: what constitutes an AI incident requiring escalation versus a tuning adjustment, and who is notified in each case
NIST CA-2 (Control Assessments) — schedule recurring control assessments specifically for AI systems on a cadence matching the system's autonomy level and data sensitivity — high-autonomy systems should be assessed quarterly
NIST PM-2 (Information Security Program Leadership Roles) — AI system accountability must be assigned at a named individual level, not a team or department, to ensure clear escalation and decision authority
CIS 7.1 (Establish and Maintain a Vulnerability Management Process) — AI governance review cycles must be integrated into the vulnerability management process, treating model version changes, prompt injection disclosures, and AI supply chain updates as vulnerability events requiring tracked remediation
CIS 7.2 (Establish and Maintain a Remediation Process) — for AI systems where control assurance cannot be established, remediation process must define the escalation path: document the gap, assign risk acceptance authority, and set a deadline for resolution or system suspension
Compensating Control
Use a free GRC tool (Eramba Community Edition, or a structured Git repository with Markdown risk register files) to track AI system accountability assignments, review dates, and open control gaps. For review cycles: create a recurring calendar event (monthly for high-autonomy systems, quarterly for advisory-only systems) with a structured agenda — pull the AI behavioral log summary, review any output anomalies, confirm accountability owner is still current, and update the risk profile if model version or use case has changed. For systems where control assurance cannot be established: document a formal risk acceptance or suspension decision in writing, with the date, decision maker name, and reasoning — this creates an auditable record if the system later causes harm and regulatory scrutiny follows.
Preserve Evidence
Before closing governance gaps, preserve: (1) the complete pre-remediation state of AI system configurations, permission assignments, and pipeline definitions as a forensic baseline — if an AI governance failure is later identified as having caused harm during the gap period, this snapshot establishes the control state at the time; (2) any existing risk acceptance or exception documentation that authorized AI systems to operate without full governance controls — these documents establish organizational knowledge of the risk and are relevant to regulatory and legal exposure assessment; (3) vendor communications and contractual terms governing AI system behavior, update notification, and incident response obligations — foundation model providers (OpenAI, Anthropic, Google DeepMind) have published responsible scaling policies and model cards that define expected behavioral bounds, and deviations from those bounds in your environment may constitute reportable events under your vendor agreement.
