The biggest risk to AI isn’t model safety. It’s the technical debt of the models it replaces.
Most enterprise AI projects are being built on top of messy legacies. AI doesn’t fix technical debt; it identifies it, gets confused by it, and then scales it.
If your data is a mess, your AI will be a faster, more confident mess.
We are seeing ‘The AI Refactoring Tax’. Companies are finding that for every $1 they want to spend on an AI application, they have to spend $3 fixing the underlying data architecture that should have been fixed a decade ago.
AI is the ultimate magnifying glass for bad processes. If you automate a broken process, you just get broken outcomes at the speed of light.
