What does it take to move generative AI from pilot projects to real productivity in complex automotive environments? Rick Sturgeon, global engineering and technology leader, brings a practitioner’s view to this question, shaped by decades of experience leading transformation at General Motors, Johnson Controls, Dassault Systèmes, Infosys, and others. Rick shares what he’s learned from helping large OEMs modernize legacy systems, scale digital platforms, and implement AI in the real world. He explores how manufacturers can unify siloed knowledge across thousands of systems, the importance of expert oversight in tuning AI models, and why success depends on more than just technology. From aligning engineering teams around change to unlocking cross-functional productivity with AI, Rick offers grounded, forward-looking advice for manufacturers ready to move beyond buzzwords and start delivering value at scale. Whether you’re a product development leader, transformation strategist, or operations executive, this episode delivers hard-earned lessons on building the next generation of connected, intelligent factories.   Topics Discussed: Why generative AI is different from previous technologies—and what that means for implementation How to modernize engineering workflows without getting stuck in legacy complexity The hidden value of cross-system knowledge and how AI can scale it Common blockers that prevent pilot projects from turning into enterprise impact What it really takes to empower teams for AI-driven change Why domain expertise and model tuning are essential to trustworthy AI The new metrics for measuring generative AI success in manufacturing What’s next for AI in automotive product development and production