Operational Controls Beat Static AI Governance
AI risk management fails without continuous operational monitoring for drift, bias, and outputs—NIST and EU AI Act demand real-time logging, oversight, and escalation beyond initial docs.
Distinguish Governance Policies from Production Enforcement
Governance sets policies, accountability, and documentation like model cards, but operational risk management enforces them in real time against deployed systems. Without this, validated models degrade silently: a fraud detection system drifted after eight months, flagging 40% more legitimate transactions because monitoring alerted only on catastrophic failures, breaching EU AI Act post-market rules for high-risk systems. Build instrumented systems to detect drift, edge cases, disparate impacts, and escalate to governance workflows—static docs alone leave compliance gaps.
Four Core Production AI Risks and Mitigation Needs
Address bias/discrimination (e.g., Workday's AI screening rejected applicants over 40, leading to a May 2025 class action), data leakage (generative models reproducing PII or inferring attributes), output risks (hallucinations like Air Canada's chatbot causing 2024 liability for false bereavement fare info), and security (prompt injection, adversarial inputs, third-party supply chain). Deploy controls for visibility: automatic event logging, anomaly detection, and incident response to make these risks observable and actionable in production.
NIST and EU AI Act: Continuous Processes Over One-Time Checks
NIST AI RMF (Jan 2023, extended by Generative AI Profile NIST-AI-600-1 July 2024) requires ongoing Govern (accountability), Map (system inventory amid deployments/fine-tunes), Measure (quantitative risk analysis beyond pre-launch), and Manage (controls/incidents). EU AI Act (full high-risk effect Aug 2, 2026) mandates for Annex III systems (employment, credit, etc.): Article 26—monitor operations, report risks promptly, log events six months; Article 14—train overseers to detect anomalies with override authority; Article 12—build technical logging capability. Engineer these as infrastructure: dashboards for drift, human-in-loop overrides, and automated logs—not optional policies.