What if AI could design your business in minutes—and still pass audit? We sit down with Pega CEO Alan Trefler to unpack how Blueprint uses generative AI to reimagine complex processes while preserving the predictability enterprises demand. Instead of asking models to improvise outcomes at run time, Blueprint captures objectives, proposes stages and data flows, and feeds a best-in-class workflow and decisioning engine that’s built for change.

We get into the core challenge every leader faces: turning AI hype into production reality. Alan breaks down three kinds of AI that matter in the enterprise—statistical next best action, generative features that assist workers, and generative process design that rethinks how the business should run. The twist is timing. Let the model be expansive at design time, then lock the logic, policies, and decision frameworks before go-live. That keeps outcomes consistent, explainable, and ready for regulators and auditors.

You’ll hear how this approach reshapes sales and consulting. With just a few inputs and a client’s website, a first meeting can produce a tailored blueprint that feels shockingly complete. Consulting partners can now embed their proprietary IP via partner-branded blueprints, marrying their best practices with Pega’s runtime to deliver four to five times faster. We also cover trust guardrails—data isolation, no training on client data, transparency into decisions—and why predictable AI will separate pilots that stall from systems that scale.

If you’re evaluating AI for process transformation, customer engagement, or operational excellence, this conversation will give you a practical framework for choosing the right AI for the right job—and a playbook for moving from idea to production with confidence. Subscribe, share with a colleague who owns transformation, and leave a review with the one process you’d redesign first.