AI Lifecycle

Noun · AI & Machine Learning

Definitions

  1. The full sequence of stages an AI system goes through, from ideation and data preparation to training, evaluation, deployment, monitoring, updates, and retirement. Managing the AI lifecycle well helps prevent drift, hidden risk, and operational surprises.

    In plain English: The full life cycle of building, running, and maintaining AI systems.

    Example: "Governance focused on the AI lifecycle end to end, not just model launch day, because monitoring and retraining carried just as much risk."

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