Jonathan Wise, Chief Technology Architect at CESMII and veteran leader across Rockwell Automation, Microsoft, GE, and Amazon, joins The Manufacturing Intelligence Podcast to unpack what it really means to be “AI-ready” in manufacturing and what it takes to build real-world ai for manufacturing that works. Drawing from decades of experience and over 50 digital transformation projects, Jonathan discusses the hidden complexity beneath data structures, why unified namespaces aren’t enough, and how AI success depends on the right semantic and ontological foundation. He also offers a refreshingly honest perspective on standards adoption, hallucination risks in LLMs, and how to bridge both technological and generational divides on the factory floor. Topics Discussed: Why semantic consistency is the missing link in most manufacturing AI efforts How ontologies and knowledge graphs unlock decision automation The limitations of current standards and how modular “Lego block” approaches can work better Lessons from CESMII’s digital transformation projects across U.S. manufacturing The disconnect between LLMs and messy, real-world industrial data Strategies to capture tribal knowledge and embed it into next-gen AI tools Bridging generational divides between OT experts and digital-native workers Why repeatability is key to successful AI implementation The future role of humans in AI-augmented factory environments