Every federal agency now has an AI mandate, yet far fewer have the data foundation needed to deliver on it. The government's AI readiness gap isn't about algorithms, it's about data readiness. Federal data remains sprawled across legacy on-premises systems, multiple commercial cloud platforms, SaaS applications, and decades-old file shares, compounded by governance and data fidelity issues. For high-impact service agencies, from those modernizing air traffic control to those rebuilding core citizen services, that sprawl quietly caps what every modernization investment can return.

AI is only as good as the data beneath it, and it is only as trustworthy as that data is protected and recoverable. The agencies that win will be the ones that treated their data as a strategic asset first, and secured its resiliency from the start.

Join this breakfast briefing for a candid, practitioner-level conversation on how to get federal data ready for the AI programs reshaping IT modernization. We'll move past the pilots to the real work: taming data sprawl, building a governed and AI-ready data foundation, embedding the cyber resiliency that keeps that data protected and recoverable, and navigating the policy and security requirements, including sensitive classification handling. You'll leave with a clear, executable view of how data readiness becomes the engine of modernization rather than the obstacle to it.