Walk into almost any large IT organization and the shape is familiar. Intake forms, ticket queues, tiers of support, service catalogs, SLAs.
From the outside, that shape looks like the nature of IT. But it is closer to a reflection of the conditions it grew up in. The work under the hood was intricate, often unstructured, sometimes chaotic. The expertise to run it was scarce, and the demand for it was not.
When a thousand people need help and fifty can provide it, you build machinery to protect the scarce side. You queue demand, tier responders, and write catalogs to standardize what can be asked. The friction people feel in IT is mostly rationing, done professionally.
And demand kept trying to escape it.
Shadow IT was unmet demand finding supply it could buy with a credit card. DevOps and platform engineering were a more disciplined escape, rebuilding the interface as self-service. Each move was locally rational, and each took something with it. Context, spend visibility, and accountability moved up to the enterprise and sat there, unowned.
The pattern across all of it was the same. Expertise could not reach demand, so demand routed around IT.
AI can change the supply side. It does not just make the fifty people faster. It can put usable expertise directly where the thousand people already are, so IT can meet demand where it lives instead of asking demand to come to the queue.
If every function does this alone, the old pattern repeats with better tools. If IT does it deliberately, the old reason to route around IT goes away.
The layers do not disappear. They get rebuilt around what stays scarce: judgment about risk the requester cannot see, accountability when something breaks, and the view of how a thousand local changes add up.
Little of this is unique to IT. Any function that built its shape around scarce expertise faces the same question.
The question is no longer how to protect the fifty from the thousand. It is how to stand behind what the thousand can now do.
First published on LinkedIn, July 29, 2026.