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How fast can we scale AI?
And how many people can we replace when we do?
That’s the conversation happening in too many boardrooms today.
But it’s the wrong one.
For many leaders, the logic is simple: if we can automate more, we can grow leaner. If intelligent tools can do the work of five, why hire five? And we see it in the market—hiring freezes, leaner org charts. From a spreadsheet view, it makes perfect sense.
But if we follow that logic to its conclusion—if the goal is simply to do the same work with fewer people—we risk misunderstanding not just what AI is capable of, but what our organizations are really built on.
Because here’s the truth: in a world where everyone has access to the same AI tools, the technology itself doesn’t give you an edge. The question isn’t just what AI can do.
The question is: what makes you, you?
AI at Work Alone Is Not a Strategy
AI is rapidly becoming a commodity. The same models, APIs, and tools are available to your competitors, your partners—and in some cases, your customers. If all you do is use AI to replicate what you were already doing, you’ll find yourself in a race to the bottom.
Productivity gains are important—but they’re not your moat. What differentiates your organization is not how well your tools perform, but how well your people think, create, decide, and respond in ways no machine can. Culture, adaptability, insight—these aren’t soft elements. They’re your power. They’re the last durable advantage in a world where technology moves faster than business models.
Even innovation itself doesn’t come from the tools. It comes from people—often from the friction of experience, contradiction, emotion, and collaboration. Automate too much in pursuit of speed or scale, and you risk suffocating the very innovation you’re trying to unlock.
There’s also the matter of risk. As AI seeps into more decisions—from hiring to customer service to strategic planning—leaders will need to account for not just what’s efficient, but what’s responsible. Algorithms won’t catch ethical red flags, reputational risks, or cultural missteps. That falls to people. And to the companies that empower them to step in, question assumptions, and course-correct when needed.
And while AI may improve convenience, customers are increasingly sensitive to how a company operates—not just what it offers. In a trust economy, human-centered leadership becomes a brand asset—one that shows up in the product, the service, the tone, and the values behind both.
Why Humans at the Wheel Is a Business Imperative
That’s why we need a different framing—
not “how do we use fewer people,”
but “how do we rethink what work looks like with people?”
What are they here to do?
How should they lead?
And how do we help them evolve as technology accelerates around them?
“I’m starting to dislike the term ‘humans in the loop,’” said Kelly Jones, Chief People Officer at Cisco, in a recent conversation for The Future Of Less Work podcast. “I think it’s ‘humans at the wheel.’ It’s not just about working with the machines. It’s about directing them.”
This shift in mindset—from human in the loop to human at the wheel—is more than semantics. It’s strategic. Human in the loop implies oversight—a checkpoint for a system that runs itself. Human at the wheel implies agency. Leadership. Intention. The ability not just to approve what technology produces, but to shape what it’s used for in the first place.
And this matters at the highest levels. Not as a feel-good message about engagement—but as a core business strategy.
Bringing People Through the Wormhole
Of course, none of this happens by decree. You can’t just tell people to think more strategically while replacing the work they once did with an algorithm. You have to take them through the transition—not just operationally, but emotionally.
“How do we take our humans through this wormhole?” Jones asks. “Work is a very existential thing… So in a world where the tasks that you do, you used to get great personal value from, are no longer the tasks we need you to do—how do we take you through that change… to the higher stack of work that we actually need done?”
This isn’t a training problem. It’s a redefinition problem. And it won’t be solved by job descriptions, dashboards, or top-down messaging.
It will require leadership that sees people not as a cost, but as the differentiating factor in a world where everything else is replicable. It requires investing in redefinition, not just reskilling. Helping people understand how they contribute now—and why it still matters.
Because when people no longer feel essential to the outcome, they disengage. But when they see that they are still the driver of decisions, strategy, and purpose, they rise.
This is where the conversation needs to go. Not “how many jobs can we replace?” but “how do we evolve what work means?”
The companies that thrive in the age of AI won’t be the ones with the most automation. They’ll be the ones with the most alignment—between what technology can do, and what people are uniquely positioned to create.
The future of AI at work is not about replacing humans. It’s about realizing how much more human the work will need to be.