Why Your AI Pilots Won’t Scale
You’ve built the use cases. Your AI champions are excited. The executive team believes. So why isn’t anything landing?
There’s a pattern I keep seeing in companies that have started their AI journey.
They’ve done the pilots. They’ve proven the concept. The AI champions are building use cases at speed. Ten a week sometimes. The executive team is bought in. Everyone at the top knows the value.
And yet nothing seems to stick.
If this sounds familiar, you might be about to hit a wall you don’t see coming. Because there are two kinds of “stuck” in AI adoption. And most people confuse them.
The Two Phases of Stuck
Phase 1: The Easy Kind
This is where daily business gets in the way. AI initiatives get deprioritized. Everything slows down. Other fires demand attention. The roadmap stretches.
But be aware: this is still the easy part.
In this phase, one motivated AI champion can build ten use cases a week. With ease. The technology works. The value is clear. It’s just about carving out time and focus.
If you’re stuck here, we can accelerate through it quickly. It’s mostly a matter of commitment and structure.
Phase 2: The Real Wall
But there’s another kind of stuck. And it’s the one that catches leaders off guard.
This is where your use cases exist but don’t touch the ground.
The executive team knows the value. You might even have a team of AI champions who are enthusiastic, building constantly, experimenting, tinkering. They’re eager to take this to the business.
But the layers beneath stall.
Middle management feels squeezed. Pressure from above to make AI happen. Resistance from below that doesn’t want to change how things work. And the people who actually need to use these tools? They’re not moving.
The Echo Chamber Problem
Here’s what I’ve noticed in these situations: the people driving AI adoption often don’t realize they’re in an echo chamber.
You believe in this. Your AI champions believe in this. The executives who sponsored the initiative believe in this. You’ve been building and experimenting together. You’ve seen what’s possible. You’re speaking the same language.
And then you try to roll out to the broader organization.
That’s when you hit the outside world.
The people on the receiving end haven’t been on this journey with you. They haven’t seen the experiments. They haven’t felt the wins. They’ve been doing their jobs the way they’ve always done them.
And now someone is asking them to change.
The Question Nobody’s Answering
The question that’s missing in most AI rollouts is simple: “What’s in it for me?”
Not “what’s in it for the company.” Not “what’s in it for productivity.” Not “what’s in it for the bottom line.”
What’s in it for the person who has to actually change how they work?
When that question gets answered, people roll along intrinsically. They want to adopt because they see personal value. They’re not being pushed. They’re pulling.
When that question stays unanswered, you get compliance at best. And quiet resistance at worst. The rollout stalls. The use cases sit unused. The AI champions get frustrated. The executives wonder why things aren’t moving.
Why This Happens
The Curse of Enthusiasm
The people driving AI adoption are usually excited about the technology. They’ve seen what it can do. They believe in the potential. This enthusiasm is what got the initiatives started in the first place.
But enthusiasm doesn’t translate automatically. What feels obviously valuable to someone who’s been experimenting for months isn’t obvious to someone who just sees another tool they need to learn.
The Communication Gap
Most AI rollouts fail at communication, not technology.
The message that lands with the executive team is not the message that lands with middle management. And neither is the message that lands with the people doing the work.
Executives care about strategic value and competitive positioning. Middle managers care about not disrupting what’s already working and not creating more problems to manage. Individual contributors care about whether this makes their day better or worse.
Same initiative. Three completely different conversations needed.
The Change Fatigue Factor
Your AI initiative isn’t happening in isolation. People have been through system changes, process changes, restructurings. They’ve heard “this will make things better” before.
If your message sounds like every other change initiative they’ve lived through, they’ll treat it the same way: nod along and wait for it to blow over.
What Actually Works
Start with the Individual
Before you can scale AI adoption, you need to be able to answer one question for every role that will be affected: how does this make their specific work better?
Not “better for productivity.” Better for them.
Less tedious work. Fewer interruptions. More time for the parts of their job they actually like. Less stress in specific situations they deal with regularly.
And even beyond that: What can we provide them, that they can take away into their private lives. This is where you have an opportunity to build that true identification. That true intrinsic motivation.
If you can’t articulate this for a specific role, you’re not ready to roll out to that role.
Make It Concrete
Abstract benefits don’t drive adoption. Concrete examples do.
“AI can help with customer service” means nothing. “When a customer asks about X, instead of searching through three systems, you can ask this tool and get the answer in 10 seconds” means something.
Get specific. Use real scenarios. Show the before and after in terms people can immediately recognize.
Let People See Themselves
The most effective AI rollouts I’ve seen let people discover value for themselves.
Not a presentation. Not a training session where someone demonstrates capabilities. An opportunity to play with a tool in the context of their own work and find their own wins. Bonus: This is where you collect feedback for further improvement.
When someone discovers for themselves that this thing can help them, they become advocates. When someone is told this thing will help them, they become skeptics.
What This Means for You
If you’re leading AI adoption in your organization, ask yourself honestly: are you stuck in Phase 1 or Phase 2?
If it’s Phase 1, you need the right approach, focus and commitment. The solutions are tactical.
If it’s Phase 2, you have a communication challenge. And that’s harder to solve, because it requires understanding perspectives very different from your own.
The technology isn’t the bottleneck. The message is.
This is exactly what I mostly work on with leaders in my Executive Sparring program. Not the AI strategy. Not the use case development. The communication. How to craft messages that land differently with different audiences. How to answer “what’s in it for me?” in ways that create intrinsic buy-in rather than forced compliance.
Because once people genuinely see the value for themselves, they don’t need to be pushed. They pull.
The Takeaway
Your AI pilots succeeded because you and your champions believed. Scaling requires something different: helping others believe too.
That doesn’t happen through better presentations or more training sessions. It happens through answering the question nobody’s asking out loud but everyone’s thinking: “What’s in it for me?”
Get that answer right, and the wall becomes a door.