While we all know AI can boost productivity, agencies everywhere are trying to figure out how that will relate to the government workload.
In this episode of Feds At The Edge, experts familiar with the Department of Energy’s Genesis Mission unpack what it takes to move from AI experimentation to secure, scalable, mission-ready infrastructure across national laboratories and research environments.
Dana Grisham of Sandia National Laboratories explores a fundamental architecture question: how do you balance centralized control with the flexibility of a federated model, especially when innovation is moving fast and compliance can’t take a back seat?
David Henderson takes the conversation deeper into data governance, examining how agencies can maintain control and visibility as information moves from databases to data lakes, warehouses, and beyond. A common data catalog, he argues, can help create the consistency and accountability these environments demand.
Frank Reyes of Maximus looks at architecture as more than infrastructure. Done well, it becomes a set of guardrails, helping federal organizations optimize performance while operating within demanding security, governance, and mission constraints.
The conversation also tackles some of the toughest realities of AI modernization: technical debt, data-sharing agreements, cross-organizational collaboration, and the security requirements that can determine whether innovation scales, or stalls.
For agencies working to turn AI ambition into operational capability, this is where the real work begins. Tune in on your favorite podcasting platform today.
To view this webinar: Data Ready Architectures: Operationalizing AI, HPC, and Trusted Science at Scale.
Featured Speakers:
Chief Data Officer for Consolidated Nuclear
Security, Y-12 National Security Complex
