Design-Time vs. Runtime AI in Government: Why Most Agencies Get It Backwards | Doug Averill

Your AI pilot probably isn't failing because the model is weak. It's failing because you pointed it at the wrong end of the process.

Doug Averill has spent half his career in government and half in technology, and now serves as Vice President, Global Industry Market Leader, Government at Pega. In this episode of GovCon Unscripted, he draws a line most modernization teams never think to draw: the difference between runtime AI (burning tokens to execute the process you already run) and design-time AI (reimagining the process from the source policy before you build anything).

Apply AI at runtime to a broken workflow, Doug argues, and you pave the cow path: you carry the skipped steps, the noncompliance, and the suboptimal outcomes straight into the new system, only faster. He and Chelsea get into why the fix starts with the source policy document rather than the current application, why the power users have to be in the room from the first pilot, why procurement belongs at ideation and not at the end, and why speed, from OTAs to fast pilots, is never the same thing as the outcome you actually needed.

Timestamps:

• 00:01 — Why the US is now leading on AI uptake while process and policy slow everyone down
• 00:04 — Context is the ceiling: why the smallest gap derails an AI tool
• 00:11 — Blueprint for Government, source policy, and paving the cow path
• 00:13 — Design-time AI vs. token-maxing runtime AI
• 00:16 — Local models, warrants, and where a contracting officer should focus
• 00:24 — Dropping point solutions on the front porch of IT
• 00:25 — Getting procurement, CISO, and ISOs in the room to go idea-to-live in 90 days

Resources:

Doug Averill's LinkedIn profile

Chelsea Roberts' LinkedIn profile

Other resources:

Pega Blueprint for Government

Pega Government Website

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