AI is forcing every leader into a choice they can’t dodge: do you believe your people are fundamentally creative and motivated, or lazy and in need of control?
Most leaders won’t want to answer that honestly, but their AI strategy already has. The AI mandates. AI-blamed layoffs. So-called AI-enabled “bossware.” The truth is in the tools: many leaders prefer “synthetic” employees they can control, and will treat human beings much the same way until they can be replaced.
Sound hyperbolic? Just look at recent headlines. Klarna’s CEO famously bragged about AI replacing his staff after the company fired or lost 22% of its workforce a year earlier (this blew up in his face, of course). Duolingo effectively announced a hiring freeze with the introduction of AI. Elijah Clark, a CEO who advises other CEOs on AI, quipped to Gizmodo, “AI doesn’t go on strike. It doesn’t ask for a pay raise” as he expressed excitement about laying off employees in favor of AI. A 2024 review found that more than two-thirds, 68 percent, of U.S. workers report experiencing at least one form of electronic monitoring on the job. There are actual billboards running that say, “Stop hiring humans,” while a new survey found that 37% of employers would prefer hiring a robot or AI over a recent college graduate.
It isn’t just that AI is replacing workers (it is), it’s that AI is reinforcing our dimmest view of workers in the process.
Generation X
Douglas McGregor was a social psychologist and MIT Sloan professor who, in 1960, argued that leaders don’t just manage from goals and objectives; they manage from hidden assumptions about human nature. He called one cluster of assumptions Theory X: the belief that people dislike work, avoid responsibility, and need tight control and incentives to perform. The contrasting Theory Y assumed that, given the right conditions, people will seek responsibility, exercise self-direction, and bring far more creativity and judgment than most organizations ever tap. When leaders push AI in ways that amplify surveillance, shrink autonomy, or quietly replace judgment with automation, they aren’t just “modernizing,” they’re hard-coding Theory X into the operating system of work.
Here’s the thing about Theory X/Y: McGregor wasn’t arguing which was right, whether employees were fundamentally lazy or capable, but that managerial beliefs become self-fulfilling. How you think about your employees determines how they’ll act. Bossware, productivity scoring, keystroke tracking, sentiment analysis of employee chats, all of it sends the same signal: we assume you won’t do the right thing unless we’re watching. These tools teach people that initiative is risky, creativity is irrelevant, and trust is conditional. And once those assumptions are embedded in tools, dashboards, and performance reviews, they stop being a management preference and start being the default culture.
It doesn’t matter that not every CEO or leader sees employees this way, enough vocal Theory X proponents will shape the narrative for everyone else. Ultimately, the more that human beings are placed in head-to-head competition with AI, the more that the workforce will respond with fear, mistrust, loafing, and even cheating.
Y Not
A Theory Y AI tool starts from the premise that people want to do good work when the system around them makes that possible. Unfortunately, the market isn’t offering a lot of Theory Y AI right now. We need more tools here, more competition, more billboards blaring an alternative worldview.
Imagine a tool, for example, that spots duplicated efforts early. Or one that learns from and simplifies decision-making and governance over time. That helps teams compare options, highlights trade-offs, and develops their strategic thinking muscles. That could create shared situational awareness by showing how changes in one team affect others in real time. Instead of secret dashboards used to police performance, Y-style tools could give workers ownership of their data and use it for growth, not punishment. They could make invisible contributions visible—mentorship, relationship-building, problem-prevention—so the whole texture of teamwork gets its due. In short, they could expand autonomy with guardrails, rather than constrict it with algorithms.
Asking the Wrong Question
The real question isn’t how much productivity we can squeeze out by replacing people with AI or treating them like imperfect machines. It’s how much potential we’ve never tapped because the modern workplace was built on bureaucracy, compliance, and risk-avoidance. For decades, we’ve constrained the very things that make humans extraordinary—creativity, judgment, curiosity, connection, the spark that happens when people riff on each other’s ideas. Those capacities have never been fully measured, let alone optimized, because most organizations designed them out of daily work.
AI could help us reverse that. Not by automating humans out, but by clearing away the sludge that has buried human capability for a century: redundant approvals, performative documentation, meetings that exist because the calendar said so, processes created for a world that no longer exists. The opportunity isn’t a marginal gain from policing employees harder—it’s the exponential upside from finally unleashing the talent you hired in the first place. The leaders who will win the next decade aren’t the ones who solely bet on synthetic workers, but the ones who use AI to build the first truly human organizations—places where people can think, make, collaborate, and surprise you again.