Industrial AI can’t afford to be wrong, says Dassault Systèmes’ Elisa Prisner
In most corners of the enterprise, an AI that is usually right is a triumph. A draft email that needs a tweak, a summary that misses a nuance, a forecast that lands close enough: these are acceptable margins of error.
Now put that same technology inside an aircraft wing, a drug trial or a car’s braking system, and the arithmetic changes. The error is no longer a rewrite. It is a recall, a regulator’s inquiry, or worse.
That gap between “impressive” and “certifiable” sits at the heart of a conversation with Elisa Prisner, Executive Vice President for Strategy, Industry, Marketing and Transformation at Dassault Systèmes. Speaking to us, Prisner set out why the French software group believes the next phase of enterprise AI will be won not by whoever has the biggest language model, but by whoever can explain why a machine did what it did.
An aerospace engineer...
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