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If you’ve ever asked a frontier AI model to plan a ridiculously complex weekend trip to London, you’ve likely walked away convinced that Silicon Valley has finally built a digital deity. It can tell you the exact tube line to take, the best pie and mash shop, and even translate British slang into corporate jargon. But ask that same omniscient digital oracle to fix a hiccup in your company’s global supply chain, and it suddenly looks like it’s trying to solve a Rubik’s cube in the dark.
We are living through a peculiar technological delusion. Enterprises look at models from OpenAI, Google, and Anthropic—behemoths that have ingested practically the entire internet—and assume that because these systems know the mating habits of North American tree frogs, they must inherently understand how to approve an invoice in Accounts Payable. Spoiler alert: they don’t.
The Digital Knower of All Things (Except Your Business)
As Alex Rinke, CEO and co-founder of process intelligence firm Celonis, recently pointed out on TechTarget’s Targeting AI podcast hosted by Esther Shittu and veteran journalist Shaun Sutner, the disconnect comes down to a glaring lack of local intel.
Think of it like choosing your tech gear. Relying on a raw, uncontextualized frontier model for core enterprise tasks is a bit like forcing yourself to use wireless charging when you know a wired connection is faster and more reliable, or trusting a sleek sport smartwatch when you actually need deep, gritty data. Sure, the tech looks shiny, but it misses the nuances of your specific environment.
“The difference is that AI knows a lot about London and a lot about tourist attractions, but it doesn’t know how this particular customer operates the supply chain, doesn’t have that 360-degree context about everything that’s going on in that organization,” Rinke explained.
Context is Your Corporate Moat
In the grand tradition of business survival, your internal workflows, how you build products, and the quirky ways your team handles customer complaints are your true competitive moats. You wouldn’t hand your company’s secret recipe to a random tourist on the street just because they asked nicely, yet enterprises routinely surrender their operational data to AI vendors, hoping for magic ROI.
According to Celonis, the secret to making AI agents actually useful isn’t just throwing a bigger model at the problem. It’s about building a digital twin of your organization that captures how work is actually performed. Without process intelligence acting as the bridge between raw AI horsepower and messy corporate reality, your fancy new AI agents are just expensive tourists wandering aimlessly through your warehouse.
So, before you bet the farm on an off-the-shelf model to reinvent your operations, remember this: an AI that knows the capital of every country on earth is utterly useless if it can’t figure out why your Tuesday morning shipments are stuck in Ohio.
(By the way, much like my trusty collection of iPhones—yes, I own several, though I still judge the lack of a headphone jack—frontier AI models are undeniably impressive. But just because an iPhone is great doesn’t mean I’d trust it to drive my car or run my logistics without a map.)
Source reference: techtarget
Disclaimer: This article was generated and formatted with the assistance of Artificial Intelligence.