Think AI Podcast

Why 90% of Manufacturing POCs Die | Ep. 8 with Naresh Mehta

May 12, 2026ยท1h 2m
Episode Description from the Publisher

๐ŸŽ™๏ธ Why 90% of Manufacturing POCs Die with Naresh MehtaAfter 20+ years building enterprise tech for global manufacturers across India, Mexico, and the US, Naresh Mehta has lived through every wave from Excel dashboards to digital twins to agentic AI to physical AI. In this conversation, he gets blunt about why most manufacturing AI projects never make it to production, names a brand new trap nobody is talking about (intelligence silos), and walks through two real deployments that prove what works when you stop chasing the model and start respecting the plumbing.We get into a real agentic AI build that automated 65% of supplier risk monitoring at an industrial conglomerate (200+ risk parameters, 8 multi-agent workflows, 20+ back office roles redeployed instead of fired), an auto OEM physical AI build that cut defect rates 25 to 30% by shifting inspection left with situationally aware robots, where quantum actually fits before manufacturing leaders even start asking, why every enterprise needs an AI control plane (and why the database-deletion horror stories happen without one), and what to tell the AI curious, the AI enthusiast, and the AI skeptic.In this episode:00:00 Cold open00:17 Welcome to Think AI Podcast01:24 Meet Naresh: 20+ years across India, Mexico, US02:00 The inflection point: when AI moved from read about to ship on04:30 Pace of innovation vs. pace of adoption07:03 The POC mindset that kills 90% of pilots10:00 Data silos. Org silos. Now intelligence silos.10:30 AI is 5%. The plumbing is 95%.13:42 Real win #1: 65% supplier risk automation, 20+ roles redeployed17:30 Real win #2: Auto OEM physical AI cuts defects 25 to 30%22:28 AI meets quantum: why manufacturing should care now30:19 The AI control plane: business outcomes + trust outcomes34:00 The agent that deleted the database35:57 Known patterns vs unknown patterns: the real implementation gap39:14 What surprised me. What stayed boringly true.46:01 Four things every manufacturer starting today must do49:54 The cake analogy: build the slice first50:58 Advice to your early 2000s self53:09 Dave on building from a different lens (disabled, dyslexic)54:45 Naresh's 10-year-old kid published a coloring book on Kindle57:41 One message each: AI curious, AI enthusiast, AI skeptic1:00:43 The unsolved problem: AI optimization for live video1:02:36 Take one idea and turn it into actionIf you lead a plant, a network of plants, or any operation where AI has to survive shift three at 2am, this one is for you.Subscribe for weekly conversations on what AI is actually delivering for manufacturers and healthcare. Drop a comment on which silo (data, org, or intelligence) is biting you hardest right now.---๐Ÿ”— Links & Resources- Naresh on LinkedIn: https://www.linkedin.com/in/naresh-mehta-53b1b437/- Think AI Consulting: https://thinkaicorp.com- Dave on LinkedIn: https://linkedin.com/in/davegoyal/#ManufacturingAI #AgenticAI #AIStrategy #DigitalTransformation #ThinkAIPodcast

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