CategoryRethinking

“There is nothing so useless as doing efficiently that which should not be done at all.”— Peter Drucker The enterprise has one tool for B2B: the login screen. A partner needs to transact with you, so you build a portal, hand them credentials, and tell them to fill in forms. It took eighteen months and a budget. Your annual report calls it “digital B2B enablement” or...

The B2B transaction problem is not a people problem or a technology problem. It is a network problem — and it needs a network solution. When you build an Intelligent Transaction Network between systems and let AI operate inside it, systems that currently exchange data through documents and re-entry begin to understand each other. The transaction becomes intelligent, and the professional who...

Everyone argues about how to cushion the blow when AI eliminates knowledge-work jobs. This article asks a different question: what happens when the same AI that eliminated those roles also eliminates the operational barriers that kept those professionals trapped inside large institutions? The answer is market fragmentation — and a kind of redistribution that no policy paper is going to deliver.

Copilots and MCP-powered assistants are personal productivity tools — they make individual workers faster, but they do not automate enterprise operations. The same AI capabilities, relocated from the workaround layer to the integration layer, would connect the systems themselves and make the workaround unnecessary.

The instinct to keep data and AI in-house is understandable, but it rests on a claim that does not survive examination. Most of what intermediaries call “our data” is held under obligation, not owned. The slice that is actually yours — derived features, operational telemetry — is less exclusive than the moat argument assumes. And the assets that actually differentiate an intermediary or...

Headquarters designs the system. The periphery adapts around it. The adaptation layer grows back every time. In many years of working with global enterprises, I have never seen a headquarters-driven system propagate without generating a layer of local workarounds.

Every enterprise is racing to deploy AI in its operations. But there is a structural question that most AI strategies are not asking: is the AI being aimed at the right target? The answer depends on a distinction that the industry has spent thirty years obscuring.