Build the monitoring process for a production AI model

Focus on outlining a comprehensive monitoring process that ensures the AI model's performance and reliability in a production environment. Start by identifying key performance indicators (KPIs) that are relevant to the model's objectives, such as accuracy, latency, and user engagement metrics. Discuss how you would implement real-time monitoring tools to track these KPIs and set up alerts for any anomalies or performance degradation. Consider the importance of continuous feedback loops for model retraining and how you would incorporate user feedback into the monitoring process. Finally, address the need for regular audits and evaluations to ensure the model adapts to changing data patterns over time.