Controlled AI Workflows

An already-live AI workflow has been changed, or is about to change, after its initial authorization. The operational issue is

Your AI workflow has passed its pre-production validations and received production authorization. It is now operating live, processing real data

A practical framework for testing an assembled AI workflow before production, from release criteria and realistic scenarios to must-pass failures, residual risk, and production authorization.

Troubleshoot a live AI workflow that has become unreliable. Learn how to contain harm, preserve evidence, localise failures, verify repairs, reconcile downstream effects, and return safely.

Assess a mapped business process across seven operational readiness dimensions, identify blockers, and determine whether to proceed with AI automation, remediate first, or defer implementation.

Map the process your team actually performs before adding AI. This five-step guide covers boundaries, roles, handoffs, wait states, exceptions, evidence, and a reusable 21-element template.