Session 5 · Operations

Scaling What Works: Operating AI at Mission Speed

Tuesday, November 3, 2026 · 11:30 AM ET

MLOps, model governance, and continuous delivery in environments where "move fast and break things" isn't an option.

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More about the webinar

Congratulations, you got your first AI capability into production. Now the hard part begins — keeping it accurate, keeping it secure, and scaling it to the next ten use cases without rebuilding your entire operational model every time. In this session, we'll cover moving from "one-off AI project" to "repeatable AI operating model" in environments where failure has consequences and "move fast and break things" is not an option.

Who should attend

Leaders who've proven the value of AI in one use case and need to scale it across the organization — without proportionally scaling cost, risk, or headcount.

What you'll learn

  • MLOps for secure environments — model monitoring, retraining, and versioning when your data can't leave a classified boundary
  • Governance without gridlock — practical model risk frameworks that give leadership confidence without creating a review-board bottleneck
  • The platform play — how to build a shared AI foundation so team #2 deploys in weeks instead of months
  • Detecting model drift before it becomes mission risk — automated guardrails that flag when models stop performing
  • Scaling people, not just technology — building AI fluency across mission teams without requiring everyone to become a data scientist

Part of the series

1Accelerating Federal Missions with AWS Cloud2Bringing AI to Your Most Sensitive Missions — Without the 18-Month Wait3Your Data is the Weapon System: Building Secure Data Pipelines for AI4From Sandbox to ATO: Accelerating AI from Prototype to Production5Scaling What Works: Operating AI at Mission Speed