The Operations Bridge

Point two in the AI Strategy Points series. The first post was about timing and honest self-assessment. This one is about a word that gets used constantly in AI conversations without ever quite being defined: value.

Everyone agrees on the principle. Almost nobody agrees on the definition

AI initiatives have to create value to stick. Say that sentence in any leadership meeting and you’ll get universal nods. Nobody disagrees with it in the abstract.

The disagreement shows up the moment you ask a follow-up question: value to whom, measured how? A tool that saves an executive twenty minutes a week and a tool that removes a genuine bottleneck on the production floor can both be described as “creating value,” but they’re not remotely the same thing, and they don’t get sustained the same way.

Value depends on who’s defining it

A leadership team often defines value in terms of strategic positioning — being seen as an AI-forward organization, keeping pace with competitors, satisfying a board that’s asking questions. That’s a legitimate form of value, but it’s abstract, and it doesn’t automatically translate into anything a frontline employee experiences.

An end user defines value very differently: does this tool make my actual day easier, faster, or less frustrating? If the answer is no, it doesn’t matter how strategically important the initiative looked in the boardroom. The tool quietly stops getting used, and the initiative dies from disuse rather than from any formal decision to kill it.

Most AI initiatives I’ve seen struggle didn’t fail because the technology didn’t work. They failed because the leadership definition of value and the end-user definition of value were never reconciled. The project was declared a success at the strategic level while quietly dying at the point of use.

Define value before you build anything

Before starting an AI initiative, I now push for an explicit answer to a simple question: whose problem does this solve, and how will that person know it worked? If I can’t name the person and the specific improvement they’ll feel, I don’t yet have a value definition — I have a hope.

This sounds obvious written down. In practice, it’s the step most initiatives skip, because it’s much more exciting to talk about the technology than to sit down with the people who will actually use it and ask what would genuinely help them.

A question for leaders

Pick an AI initiative underway in your organization right now. Can you name, specifically, whose day it makes better and how they’d describe that improvement in their own words?

If you can’t, that’s not a technology problem yet. It’s a definition problem, and it’s worth solving before you spend another dollar on the tooling.

Next up: a realistic assessment of AI end users and AI builders — and why conflating the two roles causes so much friction.