The Leadership Deficit
We're Hiding Behind AI

I was in a room once when a CTO told his delivery team — people who had just survived a brutal eighteen-month program rescue, who had clawed back a failing portfolio through sheer discipline and trust in each other — that the company's future was in artificial intelligence. There were no words of recognition. No acknowledgement of what had just been built. Just a slide deck about the next transformation. Three months later, half that team was gone. The layoffs, naturally, were announced under the banner of strategic AI investment. What troubles me most is that this is not an isolated story. Speak to any senior program or transformation leader working inside a technology organization today, and you will hear a version of it. The specific company changes. The AI branding changes. The human cost does not. And I am no longer willing to stay quiet about what it actually represents.

I have spent over twelve years leading complex programs and transformations inside financial institutions, healthcare technology companies, SaaS businesses, and enterprise software organizations. I have watched from the inside as capable, motivated teams were hollowed out not by market forces, but by a failure of leadership — followed swiftly by a press release about "strategic investment in artificial intelligence." The playbook is now familiar. The emperor, I would argue, has no clothes.

The Numbers Don't Lie — But Leaders Use Them Selectively

Let us start with what the data actually says, because the data is damning — just not in the direction most executives would prefer.

In the United States, employee engagement fell to its lowest level in a decade in 2024 — only 31% of the workforce engaged, and 17% actively disengaged. These are 2014 numbers, in a world that has supposedly been transformed by technology. Engagement actually peaked in 2020, at 36%, before declining steadily through the very years companies were most aggressively deploying digital tools and AI initiatives. The post-COVID era, far from being a technological renaissance for workers, has been a slow erosion of the most basic human elements of work: clarity of purpose, the feeling that someone cares, the belief that development is possible.

Meanwhile, the AI spending machine has been running in the opposite direction. Global AI spending reached $1.5 trillion in 2025 and is forecast to hit $2.5 trillion in 2026. Companies across North America have been investing at a pace that staggers the imagination, cutting headcount to fund it, and promising their investors and boards that the returns are coming.

There is one problem. The returns, in many cases, are not coming.

The Great AI ROI Illusion

Gartner, one of the most respected voices in enterprise technology research, published findings in May 2026 that should have stopped every C-suite in its tracks. After surveying 350 global business executives, they found that workforce reduction rates were nearly identical among companies reporting high ROI from AI initiatives and those reporting modest or negative outcomes. In other words: laying off your people to invest in AI does not produce better returns. It produces the same returns as not laying them off — minus the people.

Gartner's analyst put it plainly: "Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced. Workforce reductions may create budget room, but they do not create return." What does create return? Investing more in skills, roles, and the operating models that allow humans to guide and scale technology.

This is not an argument against AI as a technology. Artificial intelligence, applied thoughtfully, can amplify human capability in extraordinary ways. The problem is not the tool. The problem is why and how leaders are reaching for it.

The Real Crisis: Five Years of Leadership Abdication

Cast your mind back to early 2020. Teams were forced, almost overnight, to work remotely. Managers had to lead without proximity, without the usual scaffolding of in-person culture, and with enormous personal pressure bearing down on everyone. And yet — engagement climbed. Purpose became visible. Many organizations discovered, to their surprise, that when you trust people with autonomy and treat them like adults, they deliver.

What happened next is the real story of the post-COVID era. As pandemic-era urgency faded, many leaders reverted. Hybrid arrangements became battlegrounds. Return-to-office mandates were issued without context or empathy. Mass hiring surges in 2021 and 2022 gave way to mass layoffs in 2023, 2024, and 2025 — often in the same companies, sometimes of the same people. The talent that had been recruited expensively was discarded efficiently.

It is fair to acknowledge that this period was not without genuine external turbulence. The global supply chain crisis of 2021–2023, Russia's invasion of Ukraine, escalating conflict in the Middle East, and persistent inflationary pressure created real headwinds for businesses operating globally. These were not invented pressures. But here is the critical point: they were headwinds for everyone, equally. The companies that maintained culture, retained talent, and continued investing in their people through that disruption did not merely survive — they emerged with stronger delivery capability, higher retention, and more institutional knowledge than those that cut first and asked questions later. Adversity does not excuse leadership abdication. It is precisely the condition in which leadership is most consequential. The macro environment was the test. How leaders responded to it was the result.

These are not technology problems. Role clarity. Feeling cared for. Encouragement of development. These are management problems. They are culture problems. They are leadership problems. And no algorithm, however sophisticated, has yet been built to replace a manager who genuinely sees their people.

The Gallup data makes something else clear: manager disengagement is now driving employee disengagement. Managers themselves are only 27% engaged globally — and their disengagement cascades directly through their teams, since managers account for roughly 70% of the variance in team engagement. We have a system in which disengaged leaders are producing disengaged teams, and the official corporate response is to invest in AI rather than in the humans doing the leading.

Hiding in Plain Sight: AI as a Cover Story

There is something particularly troubling about the pattern that has emerged. When Cisco announced it was cutting nearly 4,000 employees in 2024, the company explicitly tied the layoffs to increased spending on AI infrastructure. When UPS eliminated 48,000 jobs in late 2025, it called it automation-enabled efficiency. Intel, Microsoft, Meta, Workday — the list goes on. Company after company, in sector after sector, has used the language of technological transformation to explain away decisions that have far more to do with cost optimization, short-term earnings management, and a fundamental unwillingness to invest in the harder, slower work of building great organizations.

The uncomfortable truth is that AI has become the perfect cover story for bad leadership decisions. It is forward-looking, so it distracts from present failures. It is technical, so it intimidates non-specialists. It is genuinely powerful in some applications, which lends legitimacy to its invocation even when the specific application is dubious. And it moves the conversation away from the questions that matter most: Did we hire the right people? Did we develop them? Did we create conditions in which they could do their best work? Did we hold ourselves, as leaders, to the same standard we held everyone else?

What Great Leadership Actually Looks Like

I want to be precise here, because the argument I am making is not a Luddite one. It is not that AI should be ignored, or that technology does not matter, or that companies should resist innovation. The argument is about sequence, emphasis, and honesty.

The organizations that will actually win over the next decade — not just in market cap, but in the quality and durability of what they build — will be the ones that invest first in leadership capacity and culture, and then deploy technology to amplify what those leaders and cultures produce. This is not sentiment. Gartner's own research finds that employees who are proficient in AI across multiple use cases are twice as likely to be highly productive, 2.3 times more likely to deliver high-quality work, and 3.2 times more likely to drive effective process improvements. The enabler of that proficiency is not the software. It is leaders who create the psychological safety and development infrastructure that allows people to experiment, learn, and grow.

Great working cultures share recognizable traits. Leaders communicate the "why" before the "what." People have clarity about what is expected of them and feel that their contribution is seen. Development is treated as a leadership responsibility, not an HR function. Bold ideas are rewarded, not just efficient execution of existing ones. Failure is interrogated honestly, not disguised by a restructuring announcement. These are not expensive things to do. They require investment of attention, honesty, and ego. They are the things that technology cannot replace — and that, in my experience, make the largest difference between organizations that consistently deliver and those that do not.

A Different Call to Action for 2026

Gartner forecasts that by 2027, 50% of enterprises without a people-centric AI strategy will lose their top AI talent. That word is worth sitting with: people-centric. Even the technology analysts have arrived at this conclusion. The machines are only as good as the humans directing them. And the humans directing them are only as effective as the culture, clarity, and leadership they operate within.

The leaders I have most respected over twelve years — the ones whose teams consistently delivered, whose people stayed and grew and did their best work — were not the ones with the most sophisticated tech stacks. They were the ones who created conditions in which people felt seen, understood what they were building and why, and were trusted to make bold decisions without fear of being made an example of. That is not a description of a software implementation. It is a description of a culture. And cultures are built by leaders, one decision, one conversation, one moment of honesty at a time.

So if you are a CTO deciding where your next dollar of investment goes, a VP of Engineering watching your best people disengage in real time, or a CEO standing before a board that wants AI returns by next quarter — this is worth sitting with: the team from that room I described at the beginning, some of them I still speak to. They are talented, experienced, and deeply disillusioned. Not with technology. With the leaders who used it as a reason not to lead. That disillusionment is the most expensive thing in corporate North America right now — and no AI budget, however large, will buy it back.