Speak then to me…
“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 global economy spends upward of $400 billion a year paying people to operate software manually — bridging gaps between systems that should be exchanging data directly. AI has the power to eliminate this labour. But nearly every deployment is using AI to perform it faster instead.
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.
Enterprise software companies have earned hundreds of billions of dollars making and selling software integration products and services. Why are enterprises spending such amounts; and what are software integration technologies? In my first article in the Process Integration Trilogy, I explained the term "business process", and discussed how software applications and systems were scattered in...
Let there be no doubt that what is called hyperautomation is singularly and principally founded on RPA. If RPA had not become well known there would not have been any definition of hyperautomation. Call it by any name, and augment it with any ancillary technology, but RPA and hyperautomation in the hands of business operations teams will always remain a technology that promises to reduce the...
Speak then to me…