AI Psychosis Phenomenon Emerges as Tech Executives Come Under Scrutiny

Mass layoffs in the tech industry continue, with AI frequently cited as the primary reason by company executives. However, behind these major decisions, a growing question is whether CEOs truly understand AI’s capabilities or are trapped in what is now termed ‘AI psychosis’—where company leaders overestimate AI’s potential without grasping its limits and risks. According to experts, CEOs are particularly vulnerable to AI psychosis as they are not directly involved in day-to-day technical work. They experiment with AI, create prototypes, then hastily conclude the technology can replace most of the workforce. Yet these are the very people who do not need to debug code, hunt for bugs, or ensure systems are free of critical errors before deployment. This unfounded confidence has real-world consequences. According to TechCrunch, in the first five months of 2026 alone, the tech industry laid off 115,430 employees across 152 companies—nearly matching the total of 124,636 layoffs throughout 2025. Most companies cite AI as the main reason for these cuts. A stark example is ClickUp CEO Zeb Evans, who publicly announced a 22% workforce reduction after deploying around 3,000 internal AI agents. Evans claimed the decision was not about cost efficiency but to build what he calls a ‘100x organisation’—where humans merely oversee and review AI-generated work. However, scientific data does not support such optimism. A meta-analysis published in UC Berkeley’s California Management Review found no strong link between AI adoption and overall productivity gains. MIT research also found AI agents are yet to match human quality across many tasks. Researchers estimate AI will only handle most text-based tasks with 80-95% success rates by 2029—at minimal quality standards. Truly surpassing human capabilities will take several more years. Harvard Business Review research adds a more complex layer: as everyone uses AI to produce more output, bottlenecks shift to executives who must approve all results. Without proper management, this could lead to organisational chaos.