Meta CEO Mark Zuckerberg led a failed internal effort to replace thousands of employees with artificial intelligence to create an "AI native" workforce [1].
The initiative represents a significant attempt by one of the world's largest tech companies to automate professional roles at scale. Had the plan succeeded, it would have fundamentally altered the employment landscape for software engineers and corporate staff.
Known internally as Project Organization Transformation, or Project OT, the strategy sought to increase efficiency and reduce costs by automating daily tasks [1]. The plan envisioned a future where AI handled the bulk of the daily work performed by thousands of human employees [1]. Under this model, Meta intended to slash team sizes by as much as 60% across two waves of reductions [1].
While the broader vision for Project OT collapsed, the company still moved forward with some staff reductions. In May 2026, Meta fired 10% of its workforce [3]. This layoff occurred just hours before the more aggressive phases of the AI-replacement plan were scheduled to begin [3].
Reports indicate that the scope of the replacement varied across internal discussions. Some accounts suggest the plan focused specifically on replacing some coders with AI [2], while other reports describe a wider effort to automate the daily work of thousands of employees across various functions [1].
Despite the collapse of Project OT, the company continues to integrate AI into its operational workflows. The failure of the project suggests that the technical or organizational hurdles of replacing large swaths of human personnel were greater than Zuckerberg initially anticipated [1].
“Meta intended to slash team sizes by as much as 60% across two waves of reductions.”
The failure of Project Organization Transformation highlights the gap between the theoretical capability of generative AI and its practical application in complex corporate environments. While AI can automate specific tasks, Meta's inability to execute a 60% staff reduction suggests that human oversight and institutional knowledge remain critical for maintaining operations at a global scale.
