With enterprises now rushing to integrate AI agents into their operations and security, the most imperative focus now becomes the AI model itself. However, Eric Tschetter, Chief Architect at Imply, believes the real challenge is within the data infrastructure that supports these systems.

In the recent episode of the Tech Transformed podcast, Kevin Petrie, BARC Vice President of Research, sat down with Tschetter to talk about how AI is actually increasing the current needs around scale, performance, and data access.

“Agents are always running queries. They’re always doing stuff,” Tschetter stated. 

Unlike human analysts, AI systems work continuously, producing much higher query volumes and putting more pressure on the data platforms underneath. This leads to a greater demand for observability architectures that can manage more data, more users, and more machine-to-machine interactions without losing speed.

For Tschetter, the solution is not to create new observability tools, but to rethink the data layer that supports them.