In this episode of the Earley AI Podcast, Seth Earley and Axonis CEO Todd Barr challenge one of enterprise technology's longest-held assumptions: that all data must be centralized before it can create value. As agentic AI becomes a reality, Barr argues that if autonomous systems must wait for data to be synchronized before they can act, the entire premise of autonomy is broken.

It's an engaging conversation that ranges from the industry's never-ending pursuit of centralized data lakes to the emerging role of federated AI, while also exploring how growing compute and power demands are shaping the future of AI innovation and global competitiveness from Silicon Valley to China.

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The discussion dives into decision intelligence, governance, and ownership in the AI era. Topics include preserving institutional knowledge, creating traceability through decision artifacts, managing long-term AI costs, and avoiding dependency on external platforms. The conversation explores why AI success is no longer just about selecting the right model; it's about building the infrastructure, workflows, and governance frameworks that organizations can trust, control, and scale over time.

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For enterprise leaders navigating AI adoption, the conversation offers a practical look at the architectural and strategic decisions that will shape long-term success.