Back
4Engineers
· Manufacturing Industry News and eMagazine
AI summary
The article argues that the main barrier to scaling AI in manufacturing isn’t the models but the foundation: fragmented data, disconnected IT/OT systems, and processes not designed for AI. It emphasizes building a unified data layer, integrating systems, standardizing and governing data, and aligning operations so AI can be deployed reliably against a few high-value, measurable use cases.
What’s been your biggest hurdle in unifying data and systems for AI, and which tactics (e.g., data governance, IT/OT integration, new middleware) have made the most difference?
The Real Reason Your Manufacturing AI Won’t Scale
The real issue is that most manufacturers are trying to scale AI on top of fragmented data, disconnected systems and operational processes that were never designed to support it.
Login to comment
LoginRelated Conversations
-
Why The Real Bottleneck in Physical AI Isn’t the Model—It’s Manufacturing
0 Replies
-
Manufacturing's AI Reality Check: Why Governance Is the Missing Link
0 Replies
-
AI Won’t Fix a Broken Supply Chain. People Will.
0 Replies
-
The Margin Blind Spot Facing Advanced Manufacturers
0 Replies
-
The Data Imperative for Smart Microfactories: Enabling Real-Time Agility and Resilience
0 Replies
Recent Conversations
Your Conversations
-
Engineering Students Design, Fabricate, and Build Real Steel Bridges
0 Replies
-
My Old Table Saw Is Better Than My SawStop… Except for One Thing
0 Replies
-
EWB-USA Restructures Global Partnerships to Build Local Capacity, Not Just Local Projects
0 Replies
-
Toray Industries wins RO membrane order for Singapore’s Changi NEWater Factory
0 Replies
-
Insight Works Adds Three Business Central Partners, From a Microsoft MVP to a German Energy Manufacturer
0 Replies