Continuous Learning
An AI system's ability to continuously learn and adapt from new data inputs without human intervention, improving over time.
Also known as online or incremental learning, where models update their parameters on streaming data rather than full retraining. This enables rapid adaptation to changing patterns (e.g., new fraud tactics) but raises governance challenges around stability, version control, and ensuring that incremental updates don’t amplify bias or violate compliance.
A cybersecurity firm deploys an intrusion-detection AI that continuously incorporates log data from new network events. Monthly, the model updates itself to detect novel attack patterns - but governance rules require that any performance drop triggers a rollback and human review before proceeding.
“What used to take weeks of manual reviews and policy work is now structured and auditable in Enzai within minutes. It’s the first time AI governance has felt operational, not theoretical.”
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