Aaron Levie Accuses CEOs of AI Psychosis Behind Wave of Layoffs

Box founder Aaron Levie has voiced sharp criticism of the wave of mass layoffs sweeping the tech industry, driven by AI-driven optimization. He called this phenomenon 'AI psychosis,' suggesting that executives making layoff decisions often lack a clear understanding of what their employees actually do.

What Is AI Psychosis According to Levie

Levie is referring to a fundamental disconnect between those making decisions about AI automation and those who actually understand how an organization works. When CEOs and investors read marketing materials about the capabilities of modern AI agents, they often fall into the trap of excessive optimism. They overestimate automation's ability to replace entire positions and functions without understanding the real complexity of the work, its dependencies, and hidden value. The result of this 'psychosis' is hasty decisions about mass layoffs that companies try to justify by claiming improved efficiency. Yet these decisions often turn out to be a strategic mistake.

Real Numbers on Layoffs

Examples already exist. ClickUp recently announced a 22% workforce reduction, betting on AI agents. On a broader scale, the technology industry is already approaching in early 2026 the number of layoffs that were recorded throughout all of 2025.

• ClickUp cut 22% of employees betting on AI agents
• Tech layoffs in 2026 are already comparable to the entire year of 2025
• The wave has affected both young startups and established companies
• Many promise 'retraining,' but rarely actually provide it

Why This Is a Strategic Mistake

'The people who decide to replace your job with AI are usually the least capable of understanding what you actually do,' Levie notes.

The problem runs deeper than mere optimism. Positions that require deep knowledge of the company's context, its history, clients, and work nuances are often eliminated. Yes, AI can handle routine tasks and standard responses. But AI cannot fully replace complex decision-making, negotiations, relationship management, and mentoring. The result: companies lose critical expertise and institutional memory. Within a year or two, when problems surface, the remaining team struggles to solve them.

What This Means

The wave of AI-driven layoffs shows that the industry has entered a phase of excessive optimism similar to the dot-com boom. Before cutting staff, companies need to more honestly assess which tasks AI can solve reliably and autonomously, and which ones require humans in the decision-making chain.