Your release process

What "AI-ready" looks like in this area

• AI-generated changes go through the same review, testing, and deployment path as human-generated changes.
• You can roll back an AI change as easily as you can roll back a human change.
• The time from "AI suggested a change" to "it is in production" is governed by the same gates as "a person wrote a change."

What we typically find on Day 1

• Release processes that work but have no written specification — institutional knowledge in the heads of the release engineers.
• Manual steps everyone has agreed to skip because they are slow, with no plan to make them fast.
• AI-generated changes being treated either too leniently (no review) or too strictly (unsafe regardless of content) — neither path is sustainable.

What changes during a Business Transformation

• AI tools become first-class participants in the release process — same code review, same tests, same deployment gates.
• Validation runs as part of every build: an AI-generated change cannot land if it does not pass.
• Rollback paths are explicit and tested. We do not rely on "we would notice within an hour" to catch AI regressions.

What stays the same

• Your CI/CD does not get replaced. The discipline gets extended.
• Your branching model stays — we adapt to it, not the other way around.
• The people who own the release process keep owning it. AI becomes a contributor in the system they already operate.

How this area connects to the rest

This is one of the seven areas an Enterprise Readiness review examines. The reference architecture that shows how all seven fit together is the agentic stack. The discipline that makes every engagement run the same loop is the repeatable process.