AI Governance Study

Managing and monitoring AI systems after deployment: inventory, drift, and champion/challenger testing

A model's quiet failure mode is the world changing underneath it. Monitoring after deployment exists because performance at launch says little about performance a year later.

Why this matters for the AIGP exam

Post-deployment scenarios almost always involve some form of drift, and the tested skill is naming it correctly and knowing the governance response.

The essentials

What the exam asks

Distinguish data drift from concept drift in a scenario, and pick the response: investigate, retrain, roll back, or escalate.

Going deeper

This page is the condensed version. The full topic — with the detail above expanded and practice questions attached — is in the app, inside Domain III. Domain I, a quarter of the course, is free to try first.

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AI Governance Study is an independent study aid. It does not represent a government entity: it is not affiliated with, endorsed by or authorised by any government, government agency or regulatory authority, and it does not provide government services or legal advice. Laws and frameworks are described in our own words — the official texts are listed at official sources. It is also not affiliated with, endorsed by, or sponsored by the IAPP. The AIGP name is used only to identify the exam this material helps you prepare for.