The correct answer isA. Pre- and post-deployment testing ensuresbias, accuracy, and fairnessare evaluated and corrected as needed, which isessential for reputational risk mitigation.

From the AIGP Body of Knowledge:

“Testing AI systems before and after deployment is critical to ensure performance, fairness, and compliance. Failing to do so may result in reputational damage and legal exposure.”

AI Governance in Practice Report 2024 (Bias/Fairness and Risk Sections):

“System impact assessments, testing, and post-deployment monitoring are necessary to identify and mitigate risks… This supports both compliance and public trust.”

Testing is proactive, unlike indemnification (which transfers risk after damage), or requiring manual review (which defeats automation).