The Missing Piece in AI Security: Omdia Research on Why DSPM Needs Data Resilience

Every agent, copilot, and model in your enterprise relies on one shared resource: your data. It is the input, the output, and what is at stake when something goes wrong. Finding and fixing data risks before AI reaches them is only half the job. The other half is getting that data back when an agentic threat or a simple mistake damages it anyway.

Join us as Todd Thiemann, Principal Analyst at Omdia, shares new research on why DSPM needs data resilience, and why proactively remediating data risks and recovering data when something goes wrong are two halves of one strategic capability.

What you will take away:

• Where real-world AI deployments struggle to close data and AI trust gaps, and how leaders close them
• Why data is the one resource every agent shares, and why securing its full lifecycle is the basis of AI trust
• How integrating DSPM and data resilience turns two separate programs into one strategic capability
• What a unified lifecycle approach looks like in practice, and how to build it