Meta Once Planned to Cut 60% of Staff Using AI: Why Zuckerberg Changed His Mind

Meta's Internal Leak: The Radical Plan to Cut 60% of the Workforce Using AI

According to an in-depth investigative report from Reuters, Meta's leadership had quietly been developing a radical organizational restructuring plan: using AI tools to reduce headcount by as much as 60%. This wasn't a gradual cost optimization — it was a fundamental reimagining of what an engineering organization could look like. The logic was straightforward: if generative AI could handle a significant share of coding, testing, and documentation, there was no longer a compelling reason to maintain a massive engineering workforce.

The sheer scale of the plan is striking. A 60% reduction isn't a marginal headcount adjustment — it's a wholesale reshuffling of the entire team structure. For a tech giant with tens of thousands of engineers, cuts of that magnitude would fundamentally alter how products are built, how decisions are made, and the underlying logic of the company's culture.

Why Zuckerberg Changed His Mind at the Last Moment

Perhaps the most revealing twist in the report is this: Mark Zuckerberg ultimately backed down. The aggressive layoff plan was never executed at the intended 60% scale. But the problem is — the very act of drawing up the plan had already caused irreversible damage.

When employees learn that leadership seriously considered replacing more than half their colleagues with AI, the crack in trust is already there. Even if the plan is shelved, the anxiety of "we could be replaced by an algorithm at any moment" has already spread through the organization. It's a classic case of Schrödinger's layoff — the blade hanging overhead changes people's mindset whether it falls or not.

The Gap Between AI Maturity and Management Expectations

Zuckerberg's hesitation also reflects a grounded reality: current AI tools simply aren't mature enough to support such aggressive substitution. Generative coding assistants do add real value for individual productivity, but truly replacing entire engineering teams requires capabilities in system architecture, cross-team collaboration, and complex business understanding that AI still clearly lacks. There is a significant gap between management's idealized expectations and where AI technology actually stands today.

Declining Morale Inside Meta and the Spread of a "Mercenary Culture"

The report uses a pointed phrase to describe the current atmosphere inside Meta: the culture is becoming "mercenary." This framing deserves careful attention.

A mercenary culture is one where employees no longer see themselves as co-builders of the company's mission, but as pure transactional participants — working for you today, moving on for a higher offer tomorrow. When employees sense that the company is perpetually ready to replace them with AI or a cheaper alternative, their rational response is to reciprocate in kind: disengage emotionally, do the minimum required, and keep one foot out the door.

For tech companies whose lifeblood is innovation, this cultural shift can be fatal. Truly breakthrough products tend to emerge from teams where members are willing to think beyond their KPIs, take risks, and collaborate with genuine commitment. Once that atmosphere is replaced by mercenary calculation, the soil for innovation quickly hardens.

The Vicious Cycle of Talent Attrition

Low morale doesn't just create an emotional problem — it generates real, measurable risks around productivity and talent retention. When uncertainty pervades an organization, the best engineers are typically the first to leave, precisely because they have the most options. Those who remain may be those with fewer alternatives, which further dilutes the team's overall capability. Meta may be caught in a paradox: the more aggressively it pursues AI-driven cost savings, the more likely it is to lose the very people who create the most value.

Three Key Warnings for Enterprise Management in the AI Era

Meta's experience offers the entire industry a valuable cautionary tale, exposing several cognitive traps that business leaders are prone to falling into during the AI wave.

The first is overconfidence in AI capabilities. Jumping from "AI can boost productivity" directly to "AI can replace 60% of our people" is a dangerous linear extrapolation. Between productivity tooling and wholesale human replacement lies a complex organizational reality.

The second is underestimating the destructive power of communication and signals. Even if a plan is never executed, once internal discussions leak or are perceived by employees, the damage to trust has already occurred. In a climate where AI-driven job anxiety is already widespread, any signal about "replacing people with AI" will be amplified.

The third is undervaluing the fragility of company culture. Culture is an asset accumulated over years, but it can collapse quickly in response to a single misguided strategic signal. The cost of rebuilding trust almost always far exceeds whatever labor costs were being sought in the first place.

Conclusion: Balancing the Pursuit of Efficiency with Organizational Trust

Meta's unfinished gamble is a reminder that AI transformation is not a simple cost-cutting equation. Technology can change how work gets done, but how to maintain organizational cohesion and creative energy while pursuing efficiency remains a question every leader must answer with care. As AI becomes a regular presence at the decision-making table, what may be truly scarce isn't computing power — it's genuine understanding and respect for people.