The 40% Problem in Industrial AI

The 40% Problem in Industrial AI

Why Many Projects Stall and What Moves Them ForwardEndurance athletes talk about the “40% wall.” It is the point where the body feels spent, even though much more capacity remains. David Goggins uses it to describe…

What Industry Is Starting to Value Differently

What Industry Is Starting to Value Differently

For decades, industrial economics was simple. Hardware was expensive. Downtime was expensive. Skilled people were expensive. Decisions, by comparison, were cheap — meetings were free, delays were tolerated, and judgment scaled through hierarchy.That balance is reversing.Today,…

Why Stale Data Is More Dangerous Than Downtime

Why Stale Data Is More Dangerous Than Downtime

Most manufacturers track machine health obsessively — vibration, temperature, torque, throughput. Yet the earliest sign of trouble inside a plant rarely starts with the equipment. It starts with the data.At the Honeywell User Group in The Hague, Claudia…

When Industrial AI Learns the Wrong Lessons

When Industrial AI Learns the Wrong Lessons

Industrial AI learns from history — but in most plants, that history is a mess.Behind every AI pilot, there’s a decade of process data, maintenance logs, and scanned reports that were never designed to work together.…

Industrial AI’s Next Phase: Proof Before Scale

Industrial AI’s Next Phase: Proof Before Scale

At Infinite Uptime’s CXO Circle in Bangkok, the discussion around industrial AI felt different. The room was filled with people who run plants. They weren’t asking whether AI belongs in manufacturing anymore. They were asking how…