This week’s pattern is simple: AI is no longer just a policy topic. It is starting to affect recovery, third-party risk, and how critical work keeps going when systems fail. The useful question for BCM leaders is not whether AI is present, but where it could break a service, slow recovery, or create a new dependency that was never exercised.
GOVERNANCE
The UK FCA, Bank of England, and HM Treasury are treating frontier AI as a live cyber resilience issue, not a future policy debate. For BCM, that means AI-enabled attack paths and supplier exposure belong in scenario testing. Ask whether AI/ML tools, model providers, and managed services are in scope of recovery plans, and whether manual processing still works if the AI layer is removed.
GOVERNANCE
The European Commission’s draft guidance could change how organizations classify and prove control over AI in important workflows. That matters when AI sits inside customer service, triage, claims, or decision support. Ask process owners what evidence they can produce today for oversight, human review, fallback, and continuity if the model is unavailable or gives the wrong answer.
SIGNAL
A live AI agent deleting production data is a direct continuity warning. If AI tools can write to business systems, they need named ownership, logging, rollback, and approval gates before go-live. Add this to the next exercise: the agent corrupts records, and the team must restore service, prove who approved the action, and decide when to stop automation.
SIGNAL
Self-hosted sandboxes and private tunnels make AI agents easier to use inside enterprise systems, but they also create a new dependency path. For resilience teams, the key question is not whether the model is secure in theory, but what fails if the tunnel, sandbox, or access broker is down. Check ownership, fallback, and incident recovery now.