Original Broadcast Date: 03/01/2026

Presented by ServiceNow & Carahsoft

On this episode of Fed Gov Today, agencies reveal how artificial intelligence is rapidly shifting from experiment to infrastructure.

At the Interior Department, Associate CIO John Montel explains how an ancient Greek icon inspired a modern AI transformation strategy. Dubbed the “Parthenon Framework,” the model brings contracting, cybersecurity, policy, training, and communications together into one agile structure designed to modernize 1,100+ mission-critical systems. The goal: eliminate “click fatigue,” embed regulations directly into workflows, and deliver AI-powered services that function as seamlessly as ordering a pizza or tracking an Uber. With dashboards measuring KPIs, risk, and cyber posture in real time, AI is becoming foundational—not optional.

ServiceNow’s Geoff Browning builds on that momentum, proposing an “AI control tower” to help agencies scale responsibly. As AI use cases surge across government, success hinges on governance, asset management, workforce upskilling, and measurable return on investment.

Finally, Treasury’s Bureau of the Fiscal Service’s Justin Marsico spotlights its expanding Do Not Pay program, which prevented, detected, or recovered $11.7 billion in improper payments in FY25—a 63% increase year over year. With permanent access to the Social Security Death Master File and 614 million screenings conducted, Treasury is scaling data-driven fraud prevention across government.

The Parthenon Strategy: How Interior Is Rebuilding Government AI from the Ground Up

The Department of the Interior is taking an architectural approach to artificial intelligence—literally. Associate CIO John Montel explains how the “Parthenon Framework” serves as a structural model for AI transformation, ensuring agencies don’t just bolt AI onto legacy systems but rebuild processes with strong foundations. The framework integrates contracting, cybersecurity, policy, training, communications, and data governance into one agile implementation model. With 75,000 employees and more than 1,100 mission-critical systems, Interior’s challenge is massive.

Montel emphasizes that AI is only as good as the data and governance behind it. The strategy focuses on eliminating manual “click fatigue,” embedding regulations like the Code of Federal Regulations directly into workflows, and building dashboards that monitor KPIs and risk in real time. The goal isn’t workforce reduction—it’s elevation. By training employees in data stewardship and embedding intelligence into everyday systems, Interior is transitioning from high-friction processes to an AI-ready ecosystem that improves mission delivery and citizen experience.

Key Takeaways:

• Build the foundation first: AI success depends on governance, data readiness, and cybersecurity.
• Data drives everything: Clean data and clear KPIs are critical before scaling.
• Modernize without disruption: Upgrade systems while keeping mission work moving.

Inside the AI Control Tower: The Blueprint for Governing Government’s AI Explosion

As federal AI use cases surge—HHS alone reports a 64% increase—governance is becoming mission-critical. Geoff Browning of ServiceNow outlines a vision for an “AI Control Tower,” a centralized governance approach designed to help agencies scale AI responsibly. The premise is simple: the agencies that succeed aren’t the fastest movers—they’re the ones that establish guardrails first.

The control tower model helps agencies answer tough questions: What can AI touch? What requires human oversight? How are risks tracked? How are assets managed across their lifecycle? Browning stresses that AI asset management becomes more complex with agentic systems and multi-cloud dependencies. He also highlights a sharp rise in demand for AI governance and data stewardship skills, underscoring the need for workforce development. Ultimately, agencies must measure value—testing, validating, and quantifying ROI. AI isn’t just about deployment; it’s about disciplined oversight that ensures security, compliance, and measurable mission impact.

Key Takeaways:

• Govern first, scale second: Clear guardrails enable responsible AI growth.
• Track your AI assets: Models, data, and dependencies must be managed closely.
• Prove the value: Agencies need AI skills and measurable ROI.

$11.7 Billion Saved: How Treasury’s AI-Driven Do Not Pay System Is Crushing Fraud

Treasury’s Bureau of the Fiscal Service’s Justin Marisco joins the program as one of government’s most powerful fraud-fighting tools—and the numbers are staggering. In FY25, Treasury prevented, detected, or recovered $11.7 billion in improper payments and suspected fraud, a 63% increase over last year. At the heart of that effort is the Do Not Pay system, a platform combining 23 data sources and advanced analytics to flag high-risk payments before they go out the door.

Usage is surging, with 614 million screenings conducted this year alone—double last year’s volume. A major milestone: Congress granted Treasury permanent access to the Social Security Administration’s Death Master File, strengthening efforts to prevent payments to deceased individuals. Treasury is also pushing for broader access to Social Security number verification data to combat synthetic identity fraud. The mission is clear—scale data, scale prevention, and protect taxpayer dollars through smarter, faster, technology-driven oversight.

Key Takeaways:

• $11.7B impact: Fraud prevention efforts surged 63% in FY25.
• Stronger data access: Death Master File improves screening accuracy.
• Identity is next: Verifying SSNs helps stop synthetic fraud.