There is a certain wildness in the tech industry these days that both mimics previous eras of large changes, like cloud computing (runaway costs in the early days), and is like nothing we have ever seen before (record revenues accompanied by mass layoffs). One possible explanation: Tech executives, especially CEOs, are collectively suffering from delusions of AI grandeur. And at least one tech CEO has said as much out loud: Box founder Aaron Levie.

Levie, the longtime CEO of the cloud content management company Box, recently took to X (formerly Twitter) to coin the term "AI psychosis." In a post that quickly went viral, he wrote: "CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI." According to Levie, CEOs "play with AI," develop a prototype, or generate a contract, and then make the leap to believing agents can do the work. But these top-level executives are not the people who have to review code, discover bugs, and identify calls to hallucinated libraries before software is deployed. They are not responsible for training AI models on a company’s idiosyncratic contract terms, nor do they have to spend days combing through contracts to find sneaky terms. In other words, Levie’s theory posits that CEOs do not really understand processes well enough to know what really can and cannot be automated. But that lack of knowledge does not stop them from acting on their beliefs.

The AI Layoff Wave

The consequences of this AI psychosis are already visible. In just the first five months of 2026, the tech industry has had nearly as many layoffs as in all of 2025: 115,430 people have been fired from 152 tech companies so far in 2026, compared to 124,636 people let go by 275 companies in 2025, according to industry layoff tracker Layoffs.fyi. The bulk of companies have pointed to AI as a reason for cutting these jobs. Many argue that the biggest tech companies are AI washing, or crediting AI productivity gains in the past or future, when other business decisions and metrics are really driving the cuts. Still, some of these stories are surprising. Zeb Evans, the CEO of project management and productivity software startup ClickUp, proudly declared on X that he had laid off almost a quarter of his employees — 22% — after rolling out about 3,000 AI agents to do internal work. Evans swore this was not done to reduce costs. Instead, he wants a workforce composed of people who run AI agents and spend their days quickly reviewing the agents’ work. He believes this will create a "100x org," as he calls it.

The Productivity Paradox

While AI can be a very useful tool, the data on AI and productivity does not support such assumptions. By miles. A meta-analysis of other research published in October in UC Berkeley’s California Management Review found "no robust relationship between AI adoption and aggregate productivity gain." Research published in March by the National Bureau of Economic Research did conclude that AI adoption improved productivity but noted "a productivity paradox, in which perceived productivity gains are larger than measured productivity gains." After creating thousands of agents to work on tasks, researchers at MIT concluded that agents just are not doing human-quality work yet in many cases. They predict at the current rate of LLM improvement, models will "be able to complete most text-related tasks with success rates of, on average, 80%–95% by 2029 at a minimally sufficient quality level." In other words, AI is on track to perform at base competence on most tasks in about three years. These researchers believe agents will need another few years to outperform humans.

The Bottleneck Shifts to Executives

Meanwhile, research published in the Harvard Business Review showed that when everyone is using AI to produce more stuff, the bottleneck simply shifts to executives. Their work awaits the people who must authorize all the stuff everyone is producing. If everyone is empowered to act, then from what OpenAI experienced last year, we can tell that things may get out of control. Are CEOs ready for that? If not, the most certain outcome of the ongoing CEO AI psychosis will simply be organizational chaos. Levie, despite his critique, is not an AI hater. Quite the opposite. He mostly posts AI positivity on X to his 2.7 million followers, writing blogs titled "Headless software is the future" on how software built for AI agents is the way forward. He also puts his money where his mouth is, backing AI startups as an active angel investor.

What CEOs Should Do Instead

So what are CEOs to do instead? Levie advises CEOs to use AI "a ton" to really see what it can and can’t do, "and come out the other side with an appreciation for both the upside and the real work." He emphasizes that the last mile of work — the debugging, the nuanced training, the contract review — is still essential. Without that hands-on experience, executives are vulnerable to overconfidence. The phenomenon is not entirely new. During the dot-com boom, CEOs similarly overestimated the power of the internet to automate business processes. During the cloud computing transition, many companies overspent on infrastructure before learning to manage costs. Now, with AI, the stakes are even higher because the technology is more opaque. Large language models can produce convincing text but also hallucinate facts, misinterpret context, and require careful human oversight. The MIT research suggests that even by 2029, AI will only reach "minimally sufficient quality" for most text tasks. That is hardly a replacement for experienced professionals.

In the meantime, layoffs continue to mount. Companies like Google, Microsoft, and Meta have cited AI efficiencies as reasons for restructuring. But critics argue that these moves are also driven by shareholder pressure to boost margins in a slow-growth environment. The term "AI washing" has gained traction, referring to companies that attribute layoffs to AI when the real reasons are financial engineering or competitive pressure. Yet the narrative that AI can replace human workers is powerful. It appeals to CEOs' desire for control and efficiency. Levie’s warning is timely because it comes from an insider who believes in AI but also understands its limitations. Box itself has integrated AI into its products, but Levie has not resorted to mass layoffs. Instead, Box has focused on upskilling employees and using AI to augment their work.

The Danger of Delusion

The danger of AI psychosis is not just that it leads to layoffs, but that it creates a false sense of progress. Companies may invest billions in AI tools that do not deliver the expected productivity gains, leading to wasted resources and missed opportunities. Moreover, the cultural impact of widespread layoffs can be devastating. Remaining employees become overworked, distrustful, and less innovative. The very creativity that drives tech forward can be stifled when people fear for their jobs. Levie’s call for CEOs to get their hands dirty with AI is a practical solution. By actually using the tools in day-to-day operations, executives can calibrate their expectations and make better strategic decisions. They might discover that AI is excellent for generating first drafts, summarizing documents, or automating routine customer queries, but terrible for tasks requiring deep domain expertise, ethical judgment, or emotional intelligence.

As the tech industry hurtles toward an AI-first future, the need for grounded leadership has never been greater. The CEOs who succeed will be those who embrace AI without losing sight of the messy, human work that still underpins most of the value creation. They will resist the temptation to declare victory too early and instead commit to a long, iterative process of integration. The alternative is the psychosis Levie describes—a collective delusion that may look impressive in boardroom presentations but ultimately leads to organizational chaos. The data is clear: AI is not yet a magic wand. It is a powerful tool that requires skilled human operators. CEOs would do well to remember that before they replace their workforce with agents that cannot yet perform at a human level.

Source: TechCrunch News