I advise CEOs and senior leaders on why technology and AI investments stall, and what it takes to make them pay off. I've sat in every seat at that table: led transformation at Verizon, built platforms at Adobe, advised the room at Code and Theory.
When an AI investment underperforms, the instinct is to treat it as a technology problem. Pick a better model. Find a better use case. Run another pilot. Replace the integrator. Comfortable answers, because every one of them can be outsourced.
The uncomfortable answer is the one I keep finding inside organizations: the tools are deployed and the organization is untouched. Roles were never redesigned. Workflows were never rebuilt. The middle of the company is still paid to run the process the investment was supposed to replace. The technology arrived. The operating model never did.
The gap between what the technology can do and what the company absorbs is never in the code. It lives in decision rights, incentives, and roles nobody redesigned.That's not a technology problem. It's structural.
Stalled investments look different from inside each company. From across enough tables, they repeat. Three patterns account for most of what I see, in Fortune 500 enterprises and growth-stage companies alike.
The demo worked, the metrics were green, and the P&L never noticed. Pilots get declared successful because nobody defined what the production version would displace. Success without a denominator isn't success. It's theater.
Leadership announces the transformation. The front line experiments. And the layer in between, the one paid to keep the current process running, quietly absorbs the change and returns the system to baseline. The middle isn't resisting. It's doing exactly what it was designed to do.
The licenses are bought and the copilots are on. But nobody can tell the person doing the work what their job is on Monday morning. Adoption without role redesign produces what most companies have: activity in the tools, and a number that won't move.
Every organization I've worked inside, from Fortune 500 enterprises to growth-stage companies, runs on the same underlying dynamics. Different context, same patterns. The politics, the friction, the talent problems, the strategic drift. None of it is new.
The value I bring isn't answers. It's pattern recognition. Seeing the thing you're standing inside of, from the outside.
When you see the pattern, the path forward gets simpler. Not easy. Simpler. You stop solving symptoms and start addressing the thing underneath. That's what an advisor is for.
My role is to uncover the patterns: the ones blocking progress and the ones that accelerate value. Acting on them takes capacity. Sometimes that's your own people, pointed at the right problem. Sometimes it's my network: management consultants, global systems integrators, offshore developers, brand and marketing agencies. I don't run a delivery arm, so the recommendation is never about feeding one. Whatever the job takes, I bring to the table.
I hold back until I understand what's actually stuck, which is rarely what the status report says.
"Here's what I'd do" doesn't transfer. "Here's the question I'd ask of this investment." That's something your team carries forward.
The measure isn't how long the engagement runs. It's whether you're seeing the system more clearly than when we started. The point is your judgment, not my retainer.
"Who owns the number this investment was supposed to move?"
"If the platform disappeared tomorrow, what would actually break?"
"Whose job has been redesigned since the tools went live?"
"What's the thing you're not saying?"
Most of my thinking is public. I write about why AI investments stall, how enterprises absorb new technology, and what it does to the people inside them. A few places to start:
Why enterprise AI ends as either the most convincing false picture a company has ever produced of itself, or the first record that can argue back.
The tools are deployed. The organization is untouched. The failure narrative is comfortable because it can be outsourced.
Adobe chose its last transformation before a crisis could force it, and changed what the street measured for a decade.
The layer being cut is the only one close enough to the work to lead the change the CEO is announcing.
Twenty years in enterprise transformation, from every seat at the table. Led it at Verizon: a digital marketing engine that drove $484 million in incremental revenue. Built it at Adobe: enterprise partnerships behind more than $1 billion in pursuits. Advised it at Code and Theory: how to get value from AI, for a Midwest retailer, a West Coast quick serve, a financial institution, and a global software provider. Grew up in Iowa, spent two decades in New York and the Bay Area, and came back.
Standing counsel to a CEO or senior leader. A monthly rhythm, an open line for the decisions in between, and a sparring partner with no stake in your org chart.
A bounded look at why a technology or AI investment isn't paying off. Weeks, not quarters. You get the pattern, named, and what it will take to move the number.
For leaders in transition: new to the seat, navigating a transformation, or making calls nobody around them can help with. Separate from advisory. No pitch behind it.
If any of this sounds like the conversation you've been trying to have, let's talk.
Twenty minutes to see if there's a fit. I keep the practice deliberately small, and if I'm at capacity, I'll say so honestly.
me@coryhaldeman.com