Mark Zuckerberg Replaced 10% of Staff With AI — Now Admits It Is Moving Too Slow

Mark Zuckerberg told Meta staff last week that the company's push to build AI agents is moving slower than expected, a striking admission after the tech giant cut roughly 10% of its workforce and redirected thousands of employees into artificial intelligence roles earlier this year.

Meta has spent the past several months aggressively reorganising around AI, betting that automated agents could handle workplace tasks, streamline operations and, eventually, reduce reliance on human labour.

In May, the company laid off about a tenth of its global staff and reassigned around 7,000 employees into new AI-focused teams, including units dedicated to agent development and optimisation. The shift was presented internally as urgent, even unavoidable, as rivals such as OpenAI, Google and Anthropic raced ahead.

Meta AI Agents Face Reality Check

Speaking at an internal town hall, Zuckerberg said progress over the past four months had not 'accelerated in the way' executives had hoped. He also conceded that the company's restructuring had not been as 'clean' as intended and that its new organisational model had yet to deliver results.

That matters because Meta has been selling a very specific vision of AI agents. These systems are not just chatbots. They are supposed to act, complete tasks, assist employees and automate workflows across everything from coding to customer support. In theory, they make companies leaner and faster. In practice, that promise is proving messy.

Inside Meta, some employees described being effectively 'drafted' into AI roles, with limited clarity on what their new jobs would involve. Others said transfers were not optional. The company's famously flexible culture, at least by Silicon Valley standards, has started to feel more directive. That shift has not gone unnoticed, or uncriticised.

There is also the awkward timing. Meta rolled out its Meta AI assistant across Facebook, Instagram, WhatsApp and Messenger in 2024, powered by its Llama models, positioning it as a free, built-in tool for billions of users. At the same time, Zuckerberg championed open-source AI as the industry's future, releasing increasingly powerful models such as Llama 3.1 405B. The message was clear. Meta intended to lead, not follow.

Yet building AI that works reliably inside a real workplace is a different beast entirely. It is one thing to generate text. It is another to navigate company systems, interpret context, maintain security and make decisions without constant human oversight. That gap, the one between demo and deployment, is where things get complicated.

Layoffs, Spending and Pressure Build

The stakes are not theoretical. Meta expects its 2026 capital expenditures to reach between $125 billion and $145 billion, according to company guidance, a figure that has already unsettled investors. At the same time, layoffs and internal reshuffling have put employees under pressure to justify the shift.

One flashpoint has been the use of mouse-tracking software, introduced as part of productivity monitoring and, some workers feared, AI training. At the same town hall, Meta CTO Andrew Bosworth said a review found no employee data had been used to train AI systems following a recent security concern. He added that any future rollout would be opt-in, after earlier indications that staff would not be able to refuse.

Even with those reassurances, the optics are tricky. Workers are being asked to help build systems that could reshape, or replace, parts of their own roles. It is a hard sell, even in a company used to rapid change.

There is also growing evidence that AI tools do not always deliver immediate productivity gains. Research cited in recent arXiv papers suggests that, in some controlled settings, developers using AI assistance actually took longer to complete tasks. One study found completion times increased by 19% in a 2025 trial, despite expectations of faster output. Another experiment linked to code review systems initially slowed reviewers by more than 5% before adjustments were made.

Those findings do not mean AI is ineffective. They do suggest that integrating it into complex workflows is far from straightforward. Software development, like many corporate functions, involves layers of judgement, maintenance and context that are difficult to automate cleanly. When AI gets it wrong, humans still have to step in, sometimes doing more work than before. That is the part that rarely makes it into keynote presentations.

Zuckerberg, for his part, is not backing away. He told staff he expects more tangible benefits from Meta's AI investments within three to six months. Company leadership continues to point to examples of small teams using AI to build products at a pace that would previously have required far larger groups. Meta CFO Susan Li has also acknowledged that the company does not yet know what the optimal size of an AI-driven workforce should be.

And that uncertainty hangs over everything. Meta is not experimenting on a small scale. It is reshaping a business used by billions, while spending at a level few companies can match.

If its AI agents are still struggling to deliver after layoffs, reassignment and massive investment, it raises a broader question about how quickly the rest of the industry can follow suit.

Some of this was always going to be uneven. The hype cycle made it sound simple, almost inevitable. Replace people, deploy agents, watch productivity spike. Reality, as it turns out, is a bit more stubborn. Maybe even a bit mad.

For employees watching the shift unfold, the message is less abstract. Companies may be reorganising around AI before the technology is fully ready to carry the load. And once those changes are made, there is no easy reset button.