TA-14 AI GOVERNANCE LIBRARY
AI Governance Lifecycle
Explore the responsibilities, evidence, authorities, decisions, and execution boundaries required to govern an AI system from initial planning through controlled retirement and final record preservation.
LIFECYCLE CONTROL DESK
Governance must remain continuous from intent to retirement.
A system does not remain governed merely because it was once approved. Evidence, authority, context, risk, performance, configuration, and operating conditions can change throughout the lifecycle.
Governance Planning
Establish governance policies, objectives, roles, authorities, boundaries, and accountability before AI development begins.
Define the conditions under which the system may be designed, evaluated, approved, operated, challenged, changed, and retired.
Design & Development
Apply governance requirements during architecture, data preparation, model development, integration, and control design.
Ensure governance is engineered into the system rather than added after technical decisions have already been made.
Validation & Approval
Verify readiness through testing, risk review, documentation, independent challenge, and execution authorization.
Determine whether available evidence supports admissibility for the declared purpose, environment, users, and operating boundaries.
Deployment
Release AI systems with approved configuration, documented controls, monitoring, rollback capability, and preserved evidence.
Ensure the system entering operation is the same governed system that was reviewed and approved.
Operations & Monitoring
Continuously monitor performance, incidents, drift, authority, compliance, execution integrity, and operational outcomes.
Maintain admissibility after deployment by detecting changes that could invalidate prior evidence, assumptions, or approvals.
Change & Revalidation
Govern updates to models, data, integrations, policies, thresholds, environments, and operating purpose.
Prevent material changes from bypassing the evidence, authority, testing, and approval conditions that governed the original system.
Incident Response
Detect, contain, investigate, correct, report, and learn from failures, anomalies, misuse, harm, or governance breakdowns.
Convert operational failure into a preserved and reviewable governance sequence with accountable corrective action.
Retirement & Preservation
Retire systems responsibly while preserving governance records, execution history, dependencies, and audit evidence.
End active operation without losing accountability, historical truth, legal evidence, or control over residual system effects.
TA-14 LIFECYCLE GOVERNING SEQUENCE
Every stage must preserve the evidence required by the next.
Declare purpose, authority, and boundaries.
Engineer governance into the system.
Test evidence against requirements.
Issue an authorized gate decision.
Release the approved configuration.
Preserve runtime evidence and drift.
Govern changes and incidents.
Close execution and preserve history.
LIFECYCLE CONTINUITY BOUNDARY
Approval at one point in time does not govern the entire future.
AI systems change through new data, model updates, integrations, user behavior, environmental conditions, policy changes, incidents, and operational drift. Lifecycle governance must preserve the relationship between the system that was approved, the system that is operating, the evidence available now, and the authority permitting continued execution.