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In a landscape dominated by the fervent promise of artificial intelligence (AI) revolutionising work, a stark contrast emerges within Silicon Valley. Despite proclamations from tech titans that AI will lead to reduced working hours, many employees are reporting grueling schedules, with some logging as much as 90 hours a week. The narrative surrounding AI’s potential to free up time for creativity and personal pursuits is increasingly at odds with the reality faced by workers entrenched in the very systems designed to enhance productivity.
A Shift in Promises
For years, executives at tech giants have touted AI’s transformative power, suggesting that the technology will eventually allow employees to enjoy shorter workweeks. A notable prediction came from a Google engineering director four years ago, who claimed that a four-day workweek could be a reality by 2025. This sentiment was echoed by OpenAI in early 2023, which encouraged firms to trial a four-day workweek, asserting that AI would soon streamline human labour to such an extent that companies should prepare for this shift.
However, insider accounts paint a different picture. A former OpenAI employee disclosed to the BBC that the company never implemented the four-day workweek it proposed, instead fostering a high-pressure environment rife with weekend work and intense performance reviews. The culture was described as “super cut-throat,” where employees often felt compelled to work through their weekends to keep pace.
Reality of Work Hours in Tech
While the tech industry is known for offering generous compensation packages, the nature of work has shifted dramatically. Workers are increasingly finding themselves clocking in far more hours than the traditional 40-hour week. A former OpenAI staff member noted that they often worked upwards of 70 hours weekly, a significant increase compared to their previous roles in the sector. Although they now enjoy a slightly more balanced schedule at a startup, the reality for many within AI-focused firms remains one of relentless sprints—defined periods where employees are expected to exert extreme effort leading up to product launches.
Reports from both OpenAI and Anthropic indicate that these sprints can stretch for weeks, demanding upwards of 90 hours of work in just seven days. The workload does not just stem from project deadlines; it is exacerbated by the rapid pace of development and the constant need to monitor AI outputs, which compounds the pressure on engineers.
The ‘Drafting’ Phenomenon at Meta
At Meta, employees are often “drafted” into urgent AI projects with little choice in the matter, as described by both current and former staff. This practice has led to extended hours, with team members frequently working late into the night and during weekends, feeling perpetually “on call.” Despite a recent softening of this approach, the impact on employee morale and work-life balance has already taken its toll.
The scenario is not confined to teams directly working on AI tools. Former Google employee Amin Shali highlighted how the demand for AI has altered the landscape across the board, leading to longer hours and heightened stress levels. He noted that reliance on AI tools frequently resulted in late-night troubleshooting sessions as the company shifted essential resources towards AI initiatives.
Workload vs. Work-Life Balance
Emerging research from UC Berkeley further complicates the narrative around AI’s promise of efficiency. A study spanning eight months revealed that employees, while incorporating AI into their workflows, experienced heightened workloads. The speed of work increased, and many found themselves extending their hours as they attempted to adapt to the new tools. Neil Thompson, an innovation scholar from MIT, remarked that rather than merely deploying AI tools to cut down on tasks, workers often end up with an expanded set of responsibilities, effectively nullifying any potential time savings.
The research indicates a troubling trend: even if AI were to reduce certain tasks by 20%, the emergence of new responsibilities often fills that gap, leaving workers with the same or even greater demands on their time. As Shali observed, the expectation is that AI should enhance well-being and work-life balance. Yet, the reality remains that many are experiencing the opposite.
Why it Matters
The disparity between the promise of AI and the reality faced by tech workers raises critical questions about the future of work in the industry. As organisations rush to adopt AI technologies, the onus falls on them to ensure that the pursuit of innovation does not come at the expense of employee well-being. With the potential for increased productivity comes the risk of burnout, making it imperative for companies to foster a culture that truly values work-life balance. The narrative of AI as a liberator of time may very well depend on a fundamental shift in how tech firms manage their most valuable asset: their people.