The Rise of "AI Psychosis"
A growing chorus of voices in the tech industry is sounding the alarm on what Box founder Aaron Levie is calling "AI psychosis" — a phenomenon where company leaders become so captivated by the promise of artificial intelligence that they make sweeping workforce decisions without truly understanding the work being replaced.
The concept cuts to a central tension in the current AI boom: the executives deciding that AI agents can handle a job are often the least qualified to assess what that job actually involves day to day. The result, critics argue, is a wave of layoffs driven more by boardroom enthusiasm than operational reality.
ClickUp's Drastic Cut
The most striking recent example is ClickUp, the project management software company, which announced it was cutting 22% of its workforce to make room for AI agents. The move sent shockwaves through the tech world — not just because of the scale of the cuts, but because of the explicit reasoning behind them.
ClickUp's leadership framed the layoffs as a forward-looking investment in automation. But former employees and industry observers pushed back, arguing that the tasks being handed to AI systems are far more nuanced than leadership acknowledged. Customer support, content operations, and internal coordination — the roles most commonly targeted — involve layers of judgment and relationship management that current AI tools struggle to replicate reliably.
2026: A Year of Accelerating Cuts
ClickUp's move is part of a broader and accelerating pattern. Tech layoffs in 2026 are already approaching the full-year totals from 2025, and the pace shows no sign of slowing. Where earlier rounds of cuts were often framed around macroeconomic headwinds, this cycle is being driven by something different: a strategic bet that leaner teams augmented by AI will outcompete larger, traditionally staffed organizations.
The logic is seductive. AI tools are genuinely improving. Costs are falling. For a CFO staring at a headcount budget, the math looks compelling on a slide deck. The problem, as Levie and others are pointing out, is that the slide deck doesn't capture what actually happens when institutional knowledge walks out the door.
The Human Cost of Premature Automation
Researchers and organizational psychologists have long documented the hidden value in experienced workforces — the informal networks, the tacit knowledge, the judgment calls that never get written down in a process document. AI systems, however sophisticated, are trained on what can be codified. They struggle with the rest.
For workers across the tech sector — including the many Canadians employed by multinational tech firms — the current climate is deeply unsettling. Roles that seemed stable a year ago are now being evaluated through an AI lens, often by people several management layers removed from the actual work.
A Reality Check for the AI Boom
None of this means AI isn't transforming work — it clearly is. But the gap between what AI can do in a demo and what it can reliably do in production, at scale, without supervision, remains significant. Companies discovering that gap after the layoffs have already happened face a painful rebuild.
For now, Levie's warning about AI psychosis resonates in a moment when the pressure to act boldly on AI is immense, and the consequences of moving too fast are just beginning to become clear.
Source: TechCrunch
