AI-powered development is accelerating release cycles and quietly widening the gap between test coverage and production risk. Traditional testing wasn’t built for this pace, and the cost of an escaped defect has never been higher.

This playbook walks you through quality intelligence: a smarter approach to testing that connects code changes directly to risk, so your team knows exactly what to test, what to skip, and when it’s safe to ship.

You’ll find a practical implementation guide, real-world results from teams across regulated and high-stakes industries, and a self-assessment to show you where to start.

You’ll learn:

• Why traditional testing falls short in AI-driven development: And the specific gaps that let defects slip through to production
• How quality intelligence works in practice: From test gap analysis and impact analytics to quality gates and go/no go reporting
• How to implement it in your organization: Iincluding baseline metrics to track, common pitfalls to avoid, and a step-by-step checklist for rollout