The Meeting That Changed
How I Think About AI Strategy.
It Lasted 11 Minutes.
The best AI strategic insight I have encountered in the last two years did not come from a boardroom, a consultant, or a research report. It came from a warehouse manager who had never used the word “strategy” in his life — and it changed how we approach every AI engagement we run.
His name was Devon. He had been managing the inbound receiving dock for nine years. He did not attend the AI strategy sessions — he was not invited. He had not seen the vendor presentations or the roadmap slides or the projected ROI calculations. He just ran the dock. Every day. With a team of eight people and a set of operational realities that the people upstairs had only a theoretical understanding of.
I was there for a site visit. I had eleven minutes before my next meeting. I asked him one question: “Where does this operation break down?” He did not hesitate. He described three specific points of failure — in precise, operational detail — that none of the strategy sessions had surfaced. And then, almost in the same breath, he described exactly what an AI system would need to do to solve each one. Not in technical terms. In operational terms. He had been thinking about it for months. Nobody had asked.
Those eleven minutes generated more genuine AI strategic clarity than the twelve hours of boardroom sessions that had preceded them.
— A real conversation. Shared with Devon’s knowledge and permission.I have thought about that morning many times since. Not because Devon was exceptional — though he was — but because the dynamic he represents is universal. In almost every organization I work with, the most precise understanding of where AI creates value lives closest to the work. And in almost every organization, that understanding is the last thing the AI strategy process reaches for. We build strategy from the top down and wonder why it lands awkwardly on the ground.
What the Research Confirms About Where AI Strategy Goes Right — and Wrong
“The most valuable AI opportunity in any organization is almost never identified in the boardroom. It is identified by the person closest to the problem — if someone bothers to ask.”— Kelli Gilmore, COO, MindFinders
Top-Down AI Strategy vs. Problem-First AI Strategy — What Each Produces
Top-Down Strategy
- Starts with technology available, then finds problems to fit
- Built by people furthest from the operational reality
- Impressive in presentation, awkward in implementation
- Adoption requires convincing people it solves their problem
- Optimizes what leadership can see — misses what only operations knows
Problem-First Strategy
- Starts with the most painful operational problem, then finds the right tool
- Built from the people closest to the work — validated upward
- Lands more naturally — solves problems people actually have
- Adoption is organic — people asked for this to exist
- Captures the invisible operational value that no deck surfaces
The Problem-First AI Audit: Six Questions to Ask at Every Level of Your Organization
Run these conversations at four levels — frontline, supervisory, middle management, and senior leadership. The gaps between the answers are where your highest-value AI opportunities live.
The organization ran the problem-first audit. Six sessions at four levels. Forty-seven distinct operational problems surfaced. Fourteen of them were immediately actionable with existing technology. Three of them required new capability. One of them — a receiving dock handoff problem that Devon had described precisely — turned out to be the single highest-value AI opportunity in the entire organization. It was not on the strategy roadmap. It had never been in any deck. It had been in Devon’s head for two years.
The AI initiative that addressed it reduced inbound processing errors by 38% in the first quarter. The ROI calculation was straightforward. The adoption was immediate — because the people who needed it had asked for it to exist. And the strategy team finally understood something they had been missing: the most important AI strategy conversation is not the one you have in the boardroom. It is the one you have at the dock at 7:45 in the morning.
— The outcome of a problem-first approach. Measured. Real. Repeatable.The MindFinders Difference
We Start Every AI Strategy Engagement With the Devon Conversation.
Before any technology recommendation, any vendor evaluation, or any roadmap slide — we run the problem-first AI audit at every level of the organization. We listen to the people closest to the work. We map the gap between what leadership knows and what operations lives. And we build AI strategy from the problem up — ensuring that every initiative addresses something real, generates measurable value, and earns adoption organically because it solves problems people actually have.
- We conduct structured listening sessions at every organizational level before any strategic recommendation is made
- We run the six-question problem-first audit and map the full operational opportunity landscape
- We identify the highest-value opportunities — like Devon’s dock problem — that top-down strategy consistently misses
- We validate opportunities against data readiness, team capability, and measurable business impact
- We build strategy from the problem up — so every initiative is solving something real for someone real
“The people closest to the work almost always see the AI opportunity more clearly than the people closest to the strategy. The organizations that find a way to bridge those two views are the ones building AI that actually delivers.”— Kelli Gilmore, COO, MindFinders
Ready to Build AI Strategy From the Problem Up?
Let’s start with the Devon conversation in your organization — structured listening sessions at every level that surface the operational opportunities your current strategy is probably missing.
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