I spend a lot of my time in rooms where artificial intelligence is being built. Not used. Built. And the longer I sit in those rooms, the clearer one thing gets. Almost none of what's said in them is meant for the person who has to actually put this technology to work.
Lately I've been in Silicon Valley more than usual. Panelist Q&A's, private gatherings, the kind of rooms where the people who make this technology talk to each other about where it's headed. Engineers from Nvidia, OpenAI, Anthropic, Google, xAI. The people whose actual hands are on the thing.
The conversations are brilliant. They're about making the models more efficient. Making the chips faster and cheaper. The algorithms underneath, the raw computing power that makes any of this possible at all. I learn something every time, and I walk out impressed by the minds in the room.
But I walk out with the same thought every time.
None of these conversations help the person running a 500-person organization who has to decide, this quarter, whether her team is even allowed to touch these tools.
That gap is the entire reason I have a job.
The people building AI are not the problem
Let me be clear about something, because it would be easy to turn this into a story about Silicon Valley being out of touch. It isn't that.
The people building this technology are doing exactly what they should be doing. They're builders. Their work is to push the tool further, make it better, make it cheaper, make it possible at all. Without them, none of the capability we now take for granted would exist. The tool is powerful, and it's powerful because of them. It's democratizing building, which is its own article by itself.
So they are not the enemy in this story. There's no villain in the room where the tool gets made.
The trouble is the distance between that room and yours.
In one room, people talk about inference costs and how much more efficient next year's models will be. In the other room, your room, someone is trying to figure out what happens when the tool confidently tells a customer something that isn't true.
Picture the person running a healthcare organization with 500 employees. The questions keeping her up have nothing to do with chip efficiency. She's asking whether she can use these tools without violating patient privacy law. She's asking what happens the day the tool makes something up and a staff member trusts it. In her world, a confident wrong answer isn't an embarrassment. It's a patient harmed. She cannot afford mistakes, because the mistakes are measured in lives. Nobody in the room where the tool gets built is answering those questions. They were never trying to.
Those are not the same conversation. They're barely the same language.
Somebody has to stand in the middle and translate. That's the work I do.
Simplifying is half the job. The judgment is the other half.
I'm good at taking something complicated and making it simple. That's the part people notice first. I can sit across from a leadership team, take the thing that sounded like a foreign language an hour ago, and hand it back to them in words they can use that afternoon.
But simplifying is only half of it. If all I did was translate the frontier conversation word for word into plainer English, I'd be a glorified dictionary.
The real value is judgment.
Most of what comes out of the rooms I sit in with AI engineers does not matter to your organization. A small slice of it matters enormously. The job is knowing the difference, and most leaders can't, because they don't live in both worlds.
Knowing what to ignore is worth as much as knowing what to act on. You don't need to understand how the engine is built. You need someone who can say, plainly: this part is real and it should change how you think about the next two years, and this part is noise you can safely tune out. That discernment is the thing you're actually paying for. Not the translation. The judgment underneath it.
Here is where it actually goes wrong
Now to the part that keeps me up at night.
The disconnect I just described is not the builders' fault. It's a leadership failure, and it happens the same way almost every time.
A leader hears that AI is important. They're not wrong about that. They want what it promises. Efficiency. Better margins. New features and faster output. All reasonable things to want.
But they're chasing the fruit without understanding the tree. They can't see the forest for the trees, because they don't understand the technology well enough to know what actually produces efficiency or better margins in the first place. So they do the only thing that feels like action. They buy the licenses, push the tools out to their teams, and say figure it out.
No strategy. No plan for how it fits the way the organization actually runs. And no real training, because the leaders themselves were never trained. In the worst version, they hand their teams a few YouTube videos and say learn this. No standardization. No benchmarks. No shared definition of what good even looks like. Just a link and a hope.
It doesn't work. I see it over and over again.
Buying the tool is not adopting the tool. Handing it to your team is not a strategy. It's a gamble that you're going to lose.
I watch this play out constantly. The licenses get paid for, and then they sit there, untouched, because nobody told people what the tool is for, what it's not for, where the lines are, or why it's safe to try. The leader thinks the hard part is done. The hard part hasn't started.
Your people are not afraid of the tool
Here's what that careless rollout actually produces. Not productivity. Fear.
When you drop a powerful, unfamiliar tool on your team with no context and no guidance, your people don't hear opportunity. They hear threat. They wonder if the tool is there to replace them. They worry that using it makes them look like they're cutting corners, or like they can't do the job they were hired to do. So they quietly don't use it, and you're left wondering why the expensive thing you bought changed nothing.
And the fear runs deeper than losing a paycheck. Most people aren't really afraid of losing the job. They're afraid of losing the part of the work they're proud of, the thing they've spent years getting good at, the piece that makes them feel useful. When a tool shows up unannounced and seems to do that part instantly, it doesn't feel like help. It feels like erasure. Naming that, out loud, is leadership's job.
That fear is not an employee problem. It's a leadership problem, because it was created at the top, by the absence of anyone at the top taking it seriously.
This is why it has to start there. Top down. A human-first rollout isn't a soft idea. It's the plain recognition that the people who have to use this tool are the ones who decide whether it works. If they're scared, it fails. If they understand what it's for and trust that it's there to help them rather than replace them, it works. The technology was never the hard part. The people are the whole game.
What this means if you're the one in charge
If you're the person making this call for your organization, a few things change once you see it this way.
Strategy comes before tools. Decide what you're actually trying to do before you buy anything. Most of what's exciting in the industry has nothing to do with your situation, and a small piece of it could matter a great deal. You need to know which is which before you spend a dollar.
Learn it yourself first, before a single license reaches your staff. Not at an engineer's depth. At a leader's depth: enough to know what the tool is for, where it breaks, and what questions to ask. I train executive teams on AI before they deploy anything to their people, and I have never once seen that fail to produce a better result. This is my work, so weigh that as you read it. It's still the most reliable predictor I've found of whether a rollout lands or dies. Leadership that understands the thing can lead the thing. Leadership that doesn't is just forwarding a YouTube link.
Lead the rollout like it's about people, because it is. Tell your team what the tool is for. Tell them what it's not for. Tell them, out loud, that it's there to give them their time back, not to take their place. Then give them room to learn it without feeling watched.
The frontier will keep moving. The gap won't close on its own.
The people building AI are going to keep building. They're good at it, and we're all better off for it. The frontier will keep moving whether or not your organization is ready for it.
But the distance between what gets built in those rooms and what happens in yours is not going to close by itself. Someone has to stand in the middle, take the complicated thing, make it simple, and tell you the truth about what actually applies to you.
The technology is not the hard part. It never was.
The hard part is the human standing between the tool and the people it was built to serve. That part is yours.
