What does a 175-year-old farm equipment company have to teach us about the agentic era? More than most expect. Mano Mannoochahr, former CDAIO at Verizon and Travelers and a top 100 AI leader, spent 17 years at John Deere watching petabytes of farm data reshape everything from yield predictions to fuel tank sizing. His argument is simple and grounded: data transformation is not about technology, it is about the decisions it makes possible for the first time.

In this episode, Prat Moghe talks with Mano about the lessons from three decades of data leadership. At John Deere, precision agriculture data turned counterintuitive insights into real business models. And on the agentic shift, Mano points to the agricultural revolution as the most instructive parallel: in the early 1900s nearly half of the US workforce was in agriculture, today that number is 1.5%, and the overall impact on jobs and productivity was positive. His case for why AI follows the same arc is one of the most grounded takes you will hear from a leader at this level.

Topics discussed:

  • GPS-precision agriculture and petabyte-scale farm data
  • Counterintuitive field insights and new farmer business models
  • Optimizing fuel tanks and product engineering from fleet data
  • The "show me, advise me, do it for me" customer trust framework
  • Agriculture as a historical lens for workforce displacement and AI
  • Work AI can do that humans could never do at scale
  • How the CDAIO role has evolved from governance to transformation

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