If you are pushing for productivity through AI, it may be costing you more than you think. Artificial intelligence was meant to make work easier and, in many ways, it has. From automating routine tasks to accelerating research and customer service, AI tools have opened doors to new levels of efficiency. Yet alongside these gains, a quieter, more insidious consequence has emerged, one that organizations can no longer afford to ignore: AI-induced burnout.

Microsoft’s 2023 Work Trends Report anticipated that AI and automation would lighten workloads and reduce burnout. Early signs were hopeful: a global survey by UiPath in 2023 showed that 58% of workers believed automation could improve job fulfillment. However, just one year later, many organizations are beginning to see cracks in that optimism. As businesses rapidly integrate AI into daily workflows, pressure on employees to learn, adapt, and deliver faster has intensified. In fact, 65% of business leaders admit they struggle to keep employees motivated to embrace new technology, and 50% report declining enthusiasm for AI adoption, according to a 2023 Ernst & Young study. Instead of empowering teams, the flood of new tools and expectations may be overwhelming them.

The disconnect between leadership vision and employee experience is striking. In a survey of 2,500 knowledge workers across the US, UK, Canada, and Australia, Upwork found that while 96% of executives expect AI to boost company productivity, a significant 77% of employees report that AI tools have increased their workload. Even more telling: 47% of employees using AI say they don’t know how to achieve the productivity gains expected of them.

This widening gap between AI’s promise and workers’ reality is fueling a new form of digital fatigue. A separate survey by Resume Now of 1,150 American workers revealed that 61% believe using AI at work increases their risk of burnout, a number that climbs to 87% among workers under 25. Additionally, 43% reported that AI negatively impacts their work-life balance, blurring the boundaries between manageable output and escalating expectations. The underlying logic seems to be: if AI speeds up work, then employees can do more and so companies will demand more. As journalist Charlie Warzel notes, “The easier our labor becomes, the more of it we can do, and the more we’ll be expected to do.” In this sense, AI becomes an “accelerator button,” one that companies may push without restraint.

But speed and output are not the only variables in play. Burnout, as defined by the World Health Organization, is the result of chronic workplace stress that has not been successfully managed and today’s AI-driven environment is introducing several new triggers.

Job insecurity is one of them. In a SurveyMonkey Workforce Survey, 24% of workers expressed concern that AI might take their jobs, with those fears especially high among younger, lower-income, and minority groups. This kind of uncertainty has real psychological consequences.

Another growing issue is role clarity. As AI reshapes tasks and expectations, many employees are left questioning what success looks like: Should they deliver work faster? Be more strategic? Do more with less? Gallup research identifies lack of role clarity as one of the top five causes of burnout and in the era of generative AI, that lack of clarity is only deepening.

Social isolation is another byproduct. While tools like AI chatbots offer always-on support, they can reduce the need for human interaction, leading to feelings of disconnection from teams or projects. A study by Simon Fraser University found that loneliness and lack of social support are major contributors to burnout, particularly in highly digitized work environments.

AI’s impact, ultimately, depends on how it’s implemented and managed. It can be a powerful motivator when introduced thoughtfully, with training, clarity, and support. But when used as a blunt-force productivity tool without regard for human experience, it can become a serious liability.

What’s needed now is a fundamental reset in how we define and pursue productivity. Employers must recognize that burnout is not just a personal health issue, it is an organizational risk. Without clear expectations, comprehensive training, and systems of support, even the most advanced AI tools can become sources of chronic stress and disengagement.

And when burnout sets in, the costs are significant: decreased productivity, increased turnover, absenteeism, and rising healthcare claims. According to Gallup in 2022, absenteeism linked to poor mental health costs the U.S. economy $47.6 billion annually.

As AI becomes more embedded in the way we work, employers must monitor its human impact as closely as they track its performance metrics. Because in the race toward greater efficiency, the most successful organizations will be those that remember: people drive the outcomes.