Artificial Intelligence (AI)

AI failures can disrupt critical operations and damage customer trust. Boards and executives must treat AI operational resilience as a core governance responsibility—not just a technical issue—to safeguard business continuity and reputation.

NIST’s August 2026 TEVV-Athlon draft makes real-world AI evaluation a current governance issue. Businesses should connect every test to pre-agreed acceptance thresholds, a named decision owner and clear retest triggers.

ASD’s Australian Cyber Security Centre and the UK National Cyber Security Centre show why AI supplier assurance must cover the full lifecycle and extended supply chain. Moffatt v Air Canada demonstrates that business accountability remains with the organisation using the automated service.

AI risk assessments often stall innovation when unclear ownership and inconsistent evidence requirements create bottlenecks. Business leaders must own AI risk decisions, supported by clear triage and third-party evidence standards to speed value delivery without compromising controls.

The UK Information Commissioner’s Office expects AI transparency and supply-chain due diligence to evolve as processing purposes become clearer. NIST’s AI Risk Management Framework shows how privacy risk should be documented, measured and monitored throughout the AI lifecycle.

Microsoft Azure AI Foundry and Amazon Bedrock show how model retirement can shorten notice periods, stop requests and require code changes. The EU's DORA framework shows why notification, objection and exit rights must connect to a tested operational response.