Unicorns and Horses

Mark Zuckerberg is spending his evenings on the phone with AI researchers. Not his recruiters. Zuck himself. The Meta CEO is personally calling top machine learning scientists, selling them on Meta's vision for artificial general intelligence, offering compensation packages that would make investment bankers blush.

When I read this news last week, I thought about a conversation I'd had days earlier with a CEO who'd just blown $2 million trying to copy Zuckerberg's playbook. Six months ago, caught up in the AI gold rush, he hired a team of AI engineers. Signing bonuses, relocation packages, the works. His board loved it. "We're building AI capabilities," he told investors.

Last week, over coffee, I asked him about the ROI.

He stirred his latte for a long moment. "We have some interesting prototypes."

Translation: Zero revenue impact. Two million dollars for some interesting prototypes.

Here's the thing: while this CEO was hunting unicorns, his biggest competitor was training horses. They asked me to train their sales team. We took their existing sales team, average age 42, average tech sophistication somewhere between "what's a browser tab?" and "I think I downloaded the internet once," and spent two weeks teaching them to use ChatGPT. Just ChatGPT. Nothing fancy.

The result? Deal velocity increased by a third. Sales cycles shortened from 45 to 31 days. Annual revenue impact: $4.7 million. From a tool that costs $20 per month per user.

This is the great irony of the AI revolution. Everyone's so busy trying to build the next ChatGPT that they're forgetting to use the current one.

I've been thinking about this paradox a lot lately. Over the past year, I've stood in front of thousands of employees at companies like Chase, Toyota, and Mastercard, watching the same drama unfold. It always starts with fear. "AI will replace us." "It's too complicated." "It doesn't understand our business." The resistance is palpable. You can feel it in the room like humidity.

But then something shifts. Usually it happens when I show an accountant how AI can turn her from a number cruncher into a strategic advisor. Or when a sales rep realizes AI can analyze every lost deal from the past five years and tell him exactly why he's losing. One guy told me, "It's like having X-ray vision into my pipeline."

The transformation isn't technological. It's psychological.

A marketing director at a major retailer put it perfectly: "AI didn't change what we do. It changed what we're capable of doing." Her team went from producing one major campaign per quarter to one per month. Same people. Same budget. Different mindset.

This is what CEOs miss when they read about Zuckerberg's recruiting calls. Meta isn't hunting AI engineers because it's trendy. They're hunting them because Meta is building the infrastructure, the platforms and models everyone else will use. They're drilling for oil. The rest of us just need to learn how to drive.

The companies winning with AI right now aren't the ones with the best technology. They're the ones with the best adoption. They measure success not by how many AI engineers they've hired or how many models they've trained, but by a simpler metric: What percentage of their team used AI to do their job better today?

Every industry has its Kodak moment coming. But this time, the threat isn't a new technology replacing an old one. It's companies using the same technology better than you. Your competitor isn't building a better AI. They're building a better AI-enabled workforce.

I saw this play out dramatically recently. Two insurance companies, same size, same market. One hired a Chief AI Officer and a team of data scientists. The other trained their claims adjusters to use AI for document analysis. Guess which one is now processing claims 73% faster?

The path forward isn't complicated, but it requires letting go of the platform delusion, this idea that every company needs to be Meta or Google. Unless you're literally building the next generation of AI infrastructure, you don't need unicorns. You need faster horses.

You need leaders who can walk into a room full of skeptics and show them that AI isn't here to replace them. It's here to make them irreplaceable. You need managers who measure success not by prototypes built but by people transformed. You need a culture that treats AI like electricity: not something you generate, but something you plug into.

The CEO with the $2 million prototype team called me last week. He's changing strategy. Instead of trying to compete with Meta for AI engineers, he's investing in his people. Training, inspiration, adoption. He's stopped hunting unicorns and started betting on faster horses.

Smart move. Because in the end, the companies that win won't be the ones with the best AI. They'll be the ones with the best AI adoption. And that's not a technology problem. It's a human one.

The question isn't whether AI will transform your industry. It's whether you'll be the one doing the transforming or the one being transformed. And that choice? That's one no algorithm can make for you.