The End-User Awards the Prize
What the “Hat-Cam” Taught Me
Necessity may be the mother of invention, but it's the end-user that awards the prize.
For thirty years I've developed markets for new technologies and implemented them across a wide range of organizations and environments—from boardrooms to classrooms, medical environments to drilling rigs.
I've watched organizations spend a small fortune rolling out a solution with the goal of improving productivity and outcomes. The business case was airtight. Leadership was on board. The vendor's demos were impressive. Training was scheduled, change management consultants were hired, the go-live date was circled on every calendar.
Months later, most people were quietly working around the technology. The original enthusiasm faded. The vision withered. The investment was lost.
In classrooms, interactive whiteboards were rejected in favor of trusted habits and the comfort of a dry-erase marker, and in some cases, transparencies (if you remember those). In boardrooms, sophisticated audioconferencing systems were bypassed for the familiarity of a Polycom speakerphone in the middle of the table. In oilfields, I watched workers deploy the "hat-cam"—a baseball cap draped over the top of a videoconference camera to guard against prying eyes.
My point:
There is a huge gap between an innovative idea, its implementation, and its adoption by actual users. That pattern is the rule, not the exception—which is why the current AI discourse reads like a play I've seen before.
AI discourse has become a buffet. Choose your conclusion and there is an article, study, or authority to confirm your opinion of the day. AI is destroying entry-level jobs, or AI has no employment effects. AI makes workers dramatically more productive, or AI delivers minimal real-world gains. AI is hitting a wall, or AI capabilities are accelerating.
The forecasts contradict each other for three reasons. First, the new and unpredictable is, by definition, impossible to forecast accurately. Second, many of these projections have self-interest baked into their core. And third—the one I find most overlooked—most attempt to peer into the future from the wrong end of the supply chain. They're measuring what AI can do, and what companies are buying, and projecting from there.
But that's not where technology's impact gets decided.
Innovation, implementation, and user adoption are three entirely different things—but headlines, forecasters, and pundits routinely present the first as if it determines the third.
It doesn't.
Someone has an idea—maybe a brilliant one. They develop it into a concept, build a company, attract investors, hire engineers, ship a product. Marketing and sales generate demand. Leadership decides to buy in. Procurement signs the contract. The rollout and training schedules are planned.
Every one of those steps is hard. Every one of them is where good ideas die. And even after all of them go right, one hurdle remains—the one that decides whether any of the previous work matters.
User adoption.
This is the variable the forecasters can't see—or don't want to—because markets are fickle. They often work to protect existing, less efficient methods out of habit, comfort, or self-interest.
Here's what I mean.
I deployed my first videoconferencing system almost thirty years ago. Apple put the capability in our pockets in 2010. Yet the technology didn't become mainstream until the arrival of COVID forced mass adoption and transformed how we live, work, and learn.
IT and technical support staff exert the same kind of drag, though for different reasons. On more than one occasion I've seen projects blocked because adoption would mean another system to support—and another set of responsibilities to absorb. And now consider the question no forecast accounts for: how eager will these teams be to implement their own potential replacement?
This stiff-arm shows up at the individual level too. I remember a client implementing a digital signage system to cut the material and labor costs of producing and posting paper signs. There was only one problem: the person whose job it was to produce those signs felt threatened by the change, and never fully embraced the vision. The system was installed. The signs kept going up on paper.
Yes, many in these roles are personally enthusiastic early adopters of AI. But enthusiasm has a way of cooling when the waves of change start lapping at your desk.
The individuals and companies developing AI have enormous stakes in its success, and in seeing it deployed in a manner that matches their grandest visions. But "AI" is like the word "sports"—which one? AI is a vast subject with equally vast capabilities and uses, and no single forecast can speak for all of it.
Selling an idea is what you do when you take it to market. But it's you and me—the market—who decide whether it succeeds, and in what ways.
The prize is still ours to award. A Seeker's Mindset is to award it with both feet on the ground and both eyes on the horizon.
