AI Risks Stage by Stage: Operation and Monitoring - The Silent Decay of AI Models

This article, part of a series on AI auditing, highlights the critical risks associated with the operation and monitoring stage of the AI lifecycle. It emphasizes that unlike traditional software, AI models can silently degrade over time due to 'drift,' leading to incorrect decisions without any system errors. The author stresses the importance of continuous monitoring of decision quality, clear ownership, robust logging, and defined incident response plans to mitigate these unique AI risks.