AI Lifecycle +

Govern every stage.

Guide AI assets from initial requirements to retirement, with evidence, accountable tasks, and approval gates throughout.

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For AI product owners and governance teams

Inside AI Lifecycle +

What you can do.

Seven-stage lifecycle

Follow requirements and planning, data acquisition and processing, model development, pre-release impact assessment, deployment, operations, and retirement.

Evidence & governance tasks

Keep supporting materials and accountable governance tasks connected to the relevant asset and lifecycle stage.

Stage approval gates

Review each stage against its controls. Progress to the next stage only after the current approval gate has been passed.

Connected governance

Where it fits.

Start with an asset recorded in AI Asset Identification. Lifecycle governance organizes its stage decisions and supporting evidence, which AI Audit + can use during review.