Workers at OpenAI, Anthropic, and Meta say AI is making their jobs harder, not easier

The big picture: AI tools are being sold as a way to make work faster and easier. But employees at some of the companies building those tools say the opposite is happening inside their own workplaces. Current and former workers at OpenAI, Anthropic, Meta, and Google told the BBC that developing AI often involves long hours, weekend shifts, and constant pressure to meet product deadlines.

At OpenAI and Anthropic, some employees said major development pushes can last for weeks and involve more than 90 hours of work per week.

One former OpenAI technical employee said they worked at least 70 hours most weeks before leaving the company last year. They now work at another AI startup and said their schedule is closer to 50 to 60 hours a week, except during intense release periods known as sprints.

“You go in on Saturday or Sunday just to catch up or make sure things aren’t broken,” the person said.

That experience does not line up with the public message from many AI leaders. Google predicted several years ago that AI could help make a four-day workweek possible. Earlier this year, OpenAI encouraged companies to experiment with four-day schedules without cutting pay, saying AI would soon accelerate much of the work people do.

The former OpenAI employee said the company did not try a four-day workweek while they were there. Instead, they described regular “crisis meetings,” weekend work and “super cut-throat” performance reviews that could lead to sudden layoffs. OpenAI and Anthropic did not respond to the BBC’s requests for comment.

The workload is partly a result of the pace of the AI race. Companies are trying to improve models, build more computing infrastructure, and add AI features to products at the same time. That creates pressure on engineers, researchers and product teams to move quickly and fix problems as they arise.

Anthropic has said its Claude tool can work independently for seven hours on some tasks. Meta CEO Mark Zuckerberg has said AI will allow smaller teams to do more work. Yet employees say these systems are not reducing the amount of work expected from them. In many cases, they are simply being asked to produce more.

Meta workers described being moved onto AI teams with little warning. A current employee and a former employee told the BBC that workers called the process being “drafted.” The former employee said people often had little meaningful choice about joining an AI project.

“They just move you over,” the former employee said. “You can’t say no – or if you do, you have to quit.”

Those teams are working on AI systems for software engineering and other tasks, along with infrastructure that measures how well models can perform work typically done by people. The former employee said the work had no clear endpoint.

“You’re literally working in teams of people trying to replicate humans doing jobs,” the person said.

Meta has reportedly softened its reassignment approach, but workers said many employees had already been placed on AI projects. They described late nights, weekend work, and a feeling that they remained on call even when they were not actively working. A Meta spokesperson declined to comment.

The strain is not limited to people directly building AI models. Amin Shali, a former Google employee, said he left the company in May after seeing internal engineering systems fail more often. He said Google had shifted key resources, including processing units and memory storage, to AI projects, leaving other teams dealing with disruptions.

Shali said the problems often required engineers to work through the night. Since leaving Google, he said his sleep and health have improved. He said heavy use of AI tools at large companies “creates a bad culture with excess pressure on engineers.” A Google spokesperson declined to comment.

Research from UC Berkeley suggests that AI can increase workloads even when it makes individual tasks faster. The study followed hundreds of workers at a US tech company for eight months and found that employees using AI worked at a faster pace, handled more tasks and worked later into the day. They also had to spend time checking AI-generated output.

Neil Thompson, an innovation scholar at MIT, said companies are unlikely to give workers more free time when AI creates efficiency gains. Instead, those gains often lead to new tasks, more oversight, and higher expectations.

“People assume that 20% less work means four-day weeks,” Thompson said. “But new work emerges.”