Enterprise AI is just expensive autocomplete with a compliance wrapper
Vision models for document extraction prove enterprise AI is just finding elaborate ways to avoid admitting they're building very expensive OCR.
Enterprise AI vendors have discovered the perfect formula. Take a commodity capability, wrap it in security theatre, slap “enterprise-grade” on the label, and charge accordingly. Document extraction models are the latest example of this playbook in action.
The premium OCR grift
Vision-language models for enterprise document processing are impressive engineering. They handle complex layouts, extract structured data, and work across formats. But strip away the marketing speak and you’re looking at optical character recognition that costs a fortune to run. The same task that used to require a scanner and some regex now needs GPU clusters and model serving infrastructure.
Compliance as a feature moat
The real genius isn’t the technical capability. It’s positioning regulatory requirements as product differentiation. “Enterprise-grade” means audit trails, data residency controls, and security certifications. These aren’t technical innovations, they’re operational necessities dressed up as competitive advantages. The compliance wrapper justifies the price premium whilst the underlying task remains fundamentally unchanged.
The efficiency paradox
We’ve optimised our way into absurdity. Modern document extraction models require more compute to read a form than it took to land on the moon. The irony is that enterprises pay gladly because the alternative is admitting they need better processes, not better AI. Sometimes the most sophisticated solution is just an elaborate way to avoid fixing the boring problem underneath.