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1. Continuous Improvement

Purpose

Setting up the feedback loop to continuously improve the AI system based on data, user experiences and operational insights.

1. Purpose

AI systems are not static. After go-live the real learning process begins: user feedback flows in, data patterns shift and business objectives evolve. This module describes how to set up the feedback loop to continuously improve the system based on data, user experiences and operational insights.

Without a structural improvement process, an AI system deteriorates within months into a static product — with growing risk of performance degradation, compliance deviations and declining user trust.

2. Components

  • Retrospectives — Structured team reflection after each sprint or milestone
  • Kaizen Logs — Continuous registration of improvement ideas and small adjustments
  • Metrics & Dashboards — KPI monitoring and thresholds for timely action
  • Benefits Realisation — Quarterly assessment of realised benefits versus the original business case

Next step: Start by setting up a Retrospective cadence for your AI team. → See also: Metrics & Dashboards for establishing your monitoring baseline.