Introduction

Deploying AI in a company shifts risk from theoretical concerns to operational realities that can impact customers, regulators, and business performance. This section equips you to identify and manage the core AI risks that typically emerge during deployment and scaling. You’ll learn how to assess model, data, and third-party risks and how to respond effectively when incidents occur in production.

Learning Objectives

• Classify AI deployment risks across legal, ethical, safety, and operational categories to support consistent assessment.

• Evaluate model and data risks (e.g., bias, drift, provenance, consent) to determine appropriate mitigations before and after launch.

• Define third-party and incident response criteria to enable timely escalation and controlled remediation in production.