For years now, executives at companies that are pouring hundreds of billions of dollars a year into developing various artificial intelligence tools have insisted that the technology will ultimately mean people will spend less of their time working.

An engineering director at Google said four years ago that AI would deliver a four-day work week by 2025.

Earlier this year, and just one year after that engineering director’s prediction, OpenAI took up the challenge, in a manner of speaking. It formally urged companies to start testing out a four-day work week (with no change in pay), claiming that AI will soon be able to speed up so much human labour that the corporate world should prepare itself.

However, a former OpenAI technical employee who left the company last year told the BBC the firm never actually trialled the four-day work week it suggested others should try while they were there.

Instead, the person described what was often a gruelling work culture marked by frequent “crisis meetings”, working on weekends, and “super cut-throat” performance reviews that would see colleagues suddenly let go.

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

Other companies have also pushed the idea that AI will effectively reduce the number of hours people need to work, for better or worse.

Anthropic has boasted that its popular coding tool and chatbot Claude is capable of working on its own for seven hours without a break, essentially a full corporate workday. Meta’s Mark Zuckerberg has said his company is in the middle of the year when “AI starts to dramatically change the way that we work” and that such tools let far fewer employees do more than they ever could have before.

While Meta has since laid off 1 in 10 of its employees, Anthropic’s chief executive Dario Amodei has warned that as AI tools inevitably become more productive, it could mean even broader job losses.

Despite these claims, workers inside these same tech companies, who are not only developing but using the very AI tools that will purportedly perform at least some of people’s work, say they are clocking in far more than the typical five-day, 40-hour work week.

US tech workers are typically well-compensated, and while other industries such as investment banking, law and medicine also often see people work long hours, a 14-hour workday was not always the norm in tech. For years, it was a more typical 9-5 office job.

But the former OpenAI employee said they would put in at least 70 hours a week, much more than they did in previous tech jobs. The person now works at a start-up also focused on AI, and said their work-life balance has improved, working closer to 50-60 hours a week, “outside of sprints”.

A “sprint” is term for a common period in technology companies in which people work long hours in the weeks leading up to a release of a new feature or product.

Inside AI companies and larger tech companies working furiously on AI projects, however, such sprints can be extreme.

At OpenAI and Anthropic, for instance, sprints can stretch on for many weeks and top 90 hours of work in a seven-day period, tech workers that the BBC spoke to for this story said.

Neither company responded to BBC requests for comment.

At Meta, workers said they have been abruptly pushed onto teams this year doing AI work being treated as urgent. They called it being “drafted”, according to one current and one former employee, because people were not given a choice.

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

They said although Meta recently began to walk back that strict take it or leave us approach, by then many workers had already been forced onto such work.

The hours on such teams at Meta are often long, with staff working into the night, on weekends, and feeling they are “on call” during the hours they are not working, according to descriptions of the work from the current and former employees.

There are no limits in the US on how many hours a person over the age of 16 can work. In the UK and Europe, for instance, laws limit a working week to 48 hours, including overtime.

Meta’s current AI projects include the creation of an AI tool that can be used for software engineering and other kinds of work, and building AI model infrastructure that can measure an AI model’s success in replicating various tasks, the employees added.

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

That work, the person added, seems “endless”.

A Meta spokesperson declined to comment.

Even tech workers who are not directly involved in the development of AI tools are facing longer hours due to the technology.

A former Google employee, Amin Shali, left the company in May due to the ways in which he claimed AI was negatively impacting his job, like having to often work all hours of the night because internal engineering functions had failed. This was happening more frequently as Google moved crucial resources like processing units and memory storage over to AI projects.

A Google spokesperson declined to comment.

Since leaving Google, Shali told the BBC that his sleep and overall health had improved. He said he’s realised that heavy reliance on AI tools in large tech companies “creates a bad culture with excess pressure on engineers”.

Some new research suggests that AI tools are making people’s workloads even more burdensome.

A study out of UC Berkeley followed hundreds of workers at a US tech company for eight months as they used AI. It found the employees “worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day”.

Neil Thompson, an innovation scholar at MIT, said that even at tech companies leading on AI development, it is unlikely that workers are being told to simply deploy the tools that are supposed to do some of their work and move on.

“It leads to a situation where even if there were real time savings, it would be sucked up by the changes, and implementing them, and making sure they worked,” Thompson said.

The UC Berkeley research found that the workload of tech employees was expanded in part because of the need to constantly check the output of AI tools.

In a situation where an employee had smoothed out processes for AI tools, people also tend to fill any time saved with more work, Thompson added, either because they want to or they feel they should do in order to prove their value to an employer.

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

As Shali observed: “AI is supposed to be doing so much for us now, so many more people should at least have better health and better sleep.”

Instead, it seems to be the opposite.