AI Governance, Operations, Risk & Compliance
AI change control: treat prompts, models and tools like production changes
An AI system can materially change even when the application name stays the same. Model swaps, prompt edits, new tools, permission changes and retrieval updates can all change operational behavior.
Define meaningful change
Not every edit needs a committee. Establish thresholds based on autonomy, data sensitivity, user impact and reversibility.
Record the baseline
Keep enough information to understand what version was evaluated, which tools were enabled and what policies were expected to hold.
Re-test proportionately
A wording correction may need a focused regression check. A new action-capable tool or privileged data source may justify broader evaluation.
Preserve rollback
For consequential workflows, the ability to restore the last known-good configuration is itself an important control.
Keep exploring
Turn the idea into an operating move.
Continue with a practical resource, a structured system, or an advisory conversation when context matters.
