AI Storage: Enhancing Processing & Data Protection

Historically data storage has been considered a rather stodgy topic, all about capacity, retrieval speed, and data organization. But as AI data demands grow and change, the role of storage has evolved. This makes sense as AI risks and incidents are becoming more common, and agencies with invaluable data assets recognize they are significant and pose an ongoing challenge for federal and state agencies.

Today storage is rapidly becoming an active data layer where the value of data is realized and having the right data foundation is key for activating an AI strategy

As deployments become more agentic, concurrent, and context-intensive, the data foundation must do more than store information. It must deliver data fast enough to keep expensive AI infrastructure productive, protect essential information against disruption or loss, and help agencies put more of their existing data to work.

Learning Objectives:

• Build a stronger data foundation for scaling public-sector AI initiatives.
• Improve the value of AI investments through greater performance and efficiency.
• Strengthen operational resilience by protecting and recovering critical AI data.
• Unlock greater value from existing data, including protected historical information, for future AI initiatives.