Continuous AI Learning vs Model Stability

Overview

Organizations increasingly deploy AI models capable of continuous improvement through new data. However, uncontrolled model evolution may introduce unexpected risks and reduce reliability. RegulatoryTRIZ resolves this contradiction by requiring controlled retraining, version management, validation before deployment, and continuous performance monitoring. Evidence includes model version histories, validation reports, and change records, while effectiveness is measured through model performance stability and validation success rates.