AI Crisis Governance

AI failure is the new cybersecurity risk — not driven by hackers, but by overconfidence, opacity, and complexity. For boards, the threat isn’t if AI breaks, but when. Models drift, hallucinate, and bias reemerges — often without clear forensic trails or external intrusions. The board’s role is not to debug, but to ensure resilience: observability, accountability, and rapid recovery.

Unlike cyber incidents, AI failures harm trust before systems. A chatbot invents facts, a model discriminates, or an algorithm breaches regulation — each incident eroding reputation and exposing governance gaps. Boards must demand AI-specific crisis playbooks, clear ownership of AI risk, and communication protocols that translate technical faults into human impact with speed and credibility.

The test of AI governance isn’t perfection — it’s preparedness. Audit. Test. Rehearse. Because in the AI era, failures won’t just leak data — they’ll leak confidence, fairness, and brand integrity. And recovery will depend on how well the board planned before the headlines hit.