FROM THE ARCHIVE
An AI-enabled service still needs a recovery plan.
A useful system includes a way to continue when something goes wrong.
Retrospective editionPrepared for this archive on The edition date identifies its place in the weekly series.
AI can introduce a new dependency into a familiar workflow. If that dependency becomes unavailable or produces unreliable results, the team still has responsibilities to fulfil. I want recovery and continuity to be discussed as part of the service design.
Identify what can be paused
Some tasks can wait for a system to recover; others need a temporary alternative. Make that distinction with the business owner. Understand which information and approvals the alternative requires and whether the team can actually access them when the primary workflow is disrupted.
Practise the transition
A short exercise can test how people recognize the problem, decide to use the fallback, and communicate the change. Include the return to normal operation: work completed through another route may need to be reconciled. These steps are easier to improve during a rehearsal than during an urgent event.
Review dependencies with the partner
A technology partner should be able to explain relevant support arrangements and the limits of its responsibility. The organization should know what remains its own responsibility. I favour a shared view of the complete service, with realistic assumptions about the people available to operate it. Resilience is demonstrated when a team can make an orderly decision under pressure, not when a presentation contains a reassuring recovery diagram.
How Genellipse can help
Genellipse can help examine the dependencies and fallback requirements of an AI-enabled service. Our infrastructure, security, and digital teams can work with business owners on an operating model and a representative recovery scenario. The engagement can clarify which responsibilities belong to the organization, Genellipse, and any other providers involved.
FROM PERSPECTIVE TO PRACTICE
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