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Technostress: Orgs Give Employees AI, then Demand More Work

• By David Ramel
• 06/03/2025

Your new AI assistant might help you work faster -- but don't expect to go home earlier. A recent academic study shows that as companies adopt AI tools, they're not just streamlining workflows -- they're piling on new demands. Researchers found that "AI technostress" is driving burnout and disrupting personal lives, even as organizations hail productivity gains.

The study explores AI's dual impact on employees' work and life well-being, finding that while it can increase productivity, it can also cause negative effects, such as the demand to always do more.

While AI tools are marketed as time-savers and productivity boosters, the reality for many workers is more complex. In a new study in the International Journal of Information Management" published at ScienceDirect, researchers found that AI often introduces new pressures rather than alleviating them. "Technostress associated with AI is likely to manifest as demands and urgency on employees, affecting their work and life," the authors wrote, pointing to phenomena like cognitive overload, blurred boundaries, and increased pace. These findings suggest that, far from relieving employees, AI may be fueling a quiet expectation to do more with less.

As does much other recent research, the study explores the double-edged sword of enterprise AI, which provides both benefits and challenges, by examining how AI at work affects employees' work and life domains. Highlights include:

• Generative AI and AI efficacy increase productivity.
• AI efficacy increases engagement and improves job satisfaction.
• AI technostress induces exhaustion and leads to work -- family conflict and low job satisfaction but benefits productivity.
• Generative AI mitigates the negative effects of technostress.

The paper isn't alone in investigating potential negative effects of enterprise AI, as a May 25 article in The New York Times reported stresses reported by Amazon coders given AI tools and then asked to do more. The article's subhead reads "Pushed to use artificial intelligence, software developers at the e-commerce giant say they must work faster and have less time to think. Others welcome the shift."

The article quoted Dr. Lawrence Katz, a labor economist at Harvard University, as saying: "Things look like a speed-up for knowledge worker. There is a sense that the employer can pile on more stuff."

Careers firm Upwork visited the issue in its own study last year, noting in a news release that: "While business leaders are investing heavily in AI, the study shows that most organizations are currently failing to unlock the full productivity value of the technology. Despite 96% of C-suite leaders expressing high expectations that AI will enhance productivity, 77% of employees using AI say these tools have added to their workload, and nearly half (47%) of employees using AI report they do not know how to achieve the expected productivity gains."

The executive summary of the study, which is titled "From Burnout to Balance: AI-Enhanced Work Models," reads:

• Research by The Upwork Research Institute reveals that 71% of full-time employees are burned out and 65% report struggling with employer demands on their productivity. Meanwhile, 81% of global C-suite leaders acknowledge they have increased demands on workers in the past year.¹
• Leaders have high hopes that generative AI will help boost productivity, as 96% of C-suite leaders say they expect the use of AI tools to increase their company's overall productivity levels. Already, 39% of companies in our study are mandating the use of AI tools, with an additional 46% encouraging their use.
• However, this new technology has not yet fully delivered on this productivity promise: Nearly half (47%) of employees using AI say they have no idea how to achieve the productivity gains their employers expect, and 77% say these tools have actually decreased their productivity and added to their workload.
• By introducing new technology into outdated models and systems, organizations are failing to unlock the full productivity value of generative AI across their workforce. Business leaders need to shift how they organize talent and work by balancing traditional and nontraditional approaches. This includes leveraging alternative talent pools, co-creating measures of productivity with their people, and becoming fluent in the language of skills rather than job descriptions.

Researchers at Aarhus University also examined "technostress" in their analysis of Responsible AI (RAI) in the workplace. "While [RAI] can enhance productivity and innovation, it can also lead to stress and exhaustion if not managed properly," they wrote in a May 12 article titled "AI is helpful -- but can also cause technostress." Their findings emphasize that the effects of AI are highly contextual -- shaped not just by the technology itself, but by how it's introduced and integrated. "Investigating challenge and hindrance stressors is crucial," said researcher Ana Alina Tudoran, "as it helps identify the factors that promote well-being and those that may cause strain."

Notably, another AI capability, monitoring employees in the office or working remotely to ensure they aren't slacking off and are diligently trying to meet their new demands, is often mentioned along with work output stresses. For example, the above study published in the International Journal of Information Management flagged the rise of algorithmic management -- the use of AI systems to monitor and guide employee behavior. Citing related research, the authors noted that "high levels of algorithmic control reduce service quality and referral behaviors," highlighting the risk that AI oversight may create more pressure than support.

Using AI to monitor employee performance was also examined in a July 2024 Cornell University study titled "More complaints, worse performance when AI monitors work," which found that such surveillance not only increased stress and resistance but actively harmed productivity. "The AI surveillance caused them to perform worse in multiple studies," said Emily Zitek, associate professor at Cornell's ILR School and co-author of the research.

With almost all of the above research just being published recently, it's clear the double-edged sword of AI is under more scrutiny as it takes hold in the workplace. If these trends continue unchecked, experts warn that the promise of AI could backfire -- not just in terms of employee wellness, but in actual productivity. Burnout, high turnover, and disengagement could undermine the efficiency gains AI is supposed to provide. Organizations that adopt AI without restructuring job roles or investing in human-centered policies may find themselves accelerating into a future that leaves workers -- and their business goals -- behind.