Box CEO Aaron Levie diagnoses 'AI psychosis' among executives making workforce cuts

The Disconnect Between AI Authority and Job Knowledge

Box founder Aaron Levie articulated a sharp critique of executive decision-making in an episode of TechCrunch’s Equity podcast: the executives authorizing AI-driven workforce reductions are often the least equipped to assess whether those cuts make business sense. According to TechCrunch, Levie termed this phenomenon “AI psychosis”—a condition in which organizational leaders, captivated by AI’s promise, eliminate roles without understanding the actual work those roles perform. This diagnosis arrives as the tech industry enters 2026 with layoff momentum that already approaches the full-year total from 2025, suggesting the cycle of AI-motivated cuts is accelerating rather than stabilizing.

Workforce Reductions and the AI Agent Wave

ClickUp’s recent decision to eliminate 22% of its headcount specifically to deploy AI agents exemplifies Levie’s concern. According to TechCrunch, the company is betting that automated agents can absorb work that previously required human staff. The podcast discussion framed this not merely as headcount reduction, but as a fundamental reshaping of hiring patterns—companies are not simply firing and stalling; they are hiring differently, favoring AI infrastructure roles over traditional positions. TechCrunch reports that 2026 tech layoffs are already nearly matching all of 2025, indicating that the AI-replacement narrative has become broadly persuasive to decision-makers, whether or not those decisions rest on deep operational understanding.

User Skepticism and Market Response

Counterbalancing the AI-optimism narrative, TechCrunch notes that DuckDuckGo’s search engine is gaining users specifically because it omits AI-generated summaries, offering “just links.” This shift suggests that end-user skepticism about AI’s value proposition exists in tension with executive enthusiasm—a dynamic the Equity podcast framed as a moment when both the AI-pilled and AI-skeptical are “right at the same time.” Users want their existing tools to work without forced AI integration, yet the C-suite continues to architect business models around AI displacement.

Why This Matters

Levie’s diagnosis touches on a structural problem: information asymmetry between decision-makers and job performers. If executives ordering layoffs lack visibility into the actual complexity of the roles being eliminated, they may overestimate AI’s capacity to absorb that work, leading to short-term cost savings that erode operational resilience. The fact that 2026 is tracking to exceed 2025’s full-year layoffs suggests this gap in understanding is not self-correcting—it is accelerating. Teams making hiring and retention decisions should anticipate continued pressure to justify human roles in AI-automation terms, and may need to document job complexity in ways executives can evaluate independently of vendor claims about agent capability.