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Best Chain of Thought Episodes for Enterprise AI Leaders

Getting AI past the pilot — ROI, rollout, and the data underneath it.

Most enterprise AI budgets are still funding pilots that never graduate. What strands them is usually mundane: data the agent can’t reach, or a rollout nobody sequenced past the demo. Every operator here got out of that, and they’re specific about what it cost.

  1. 1 EP 48 50 min Transcript How Block Deployed AI Agents to 12,000 Employees in 8 Weeks w/ MCP | Angie Jones Angie Jones, Block Block put AI agents in front of 12,000 employees in eight weeks. Angie Jones on the security guardrails that made that defensible, and why letting people choose their own model was what drove adoption.
  2. 2 EP 4 41 min Transcript Why Most Enterprise AI Projects Fail to Show ROI | HP, ServiceNow & Accenture Vikram Chatterji, Alex Klug, Sriram Palapudi & Jay Subrahmonia The ROI question asked directly, with HP, ServiceNow, and Accenture answering it. Still the clearest entry point on why AI spend so often fails to show a return.
  3. 3 EP 64 58 min Transcript Stop Token Maxxing: Find Where AI Actually Pays Off | Jiaona Zhang Jiaona Zhang, Laurel Jiaona Zhang on the token-max trap that blanket “use AI everywhere” mandates create, and using time data to see where AI is returning something instead of assuming it is.
  4. 4 EP 66 53 min Transcript Data Federation, Not Centralization, Is What Enterprise AI Needs Jitender Aswani, Starburst The argument that every stalled enterprise AI project is fighting the same hidden battle: the agent queries the model fine, it just cannot reach the data spread across 52 to 200 sources.
  5. 5 EP 17 45 min Transcript Inside IBM's watsonx: Building Enterprise AI That Ships | Dr. Maryam Ashoori Maryam Ashoori, IBM IBM’s Dr. Maryam Ashoori on what separates enterprise AI that ships from enterprise AI that demos, with findings from a survey of 1,000 developers behind it.

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