Study shows AI tools adding to workload, burnout, not productivity

The study found that 77% of employees said AI tools had added to their workload.

(Credit: TippaPatt)

Advocates of artificial intelligence often argue that the technology will help workers, taking over the most laborious office tasks and freeing employees to spend more time on harder, more stimulating work. A new study from The Upwork Research Institute, however, shows that AI has so far largely failed to improve worker wellbeing and productivity. On the contrary, AI is increasing workloads, diminishing productivity and possibly contributing to burnout.

According to the study, there are wide disparities between executive hopes for AI tools and the experiences of employees using the tools on the ground. Ninety-six percent of C-Suite leaders said they had high expectations for AI increasing productivity, yet 77% of employees said those same tools had added to their workload. What’s more, 47% of employees using AI reported not knowing how to achieve the expected productivity gains.

It is possible that AI is leading to higher rates of burnout and employee turnover. Seventy-one percent of full time employee respondents reported being burned out, and 65% said they were struggling with their employers’ productivity demands. Incredibly, 1 in 3 employees said they were likely to quit their jobs in the next six months.

The results of the study beg the question whether the new AI tools, or their applications, are innately counterproductive, or if we’re just witnessing a hard, but temporary learning curve. Thirty-nine percent of employees reported spending more time reviewing or moderating AI-generated content, while 23% said they were investing more time learning how to use AI.

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Kelly Monahan, managing director of The Upwork Research Institute, believes in the potential of AI but thinks workplaces must change to accommodate the technology, “Our research shows that introducing new technologies into outdated work models and systems is failing to unlock the full expected productivity value of AI. While it’s certainly possible for AI to simultaneously boost productivity and improve employee wellbeing, this outcome will require a fundamental shift in how we organize talent and work.”

Monahan continued, offering specific steps businesses can take, and warning of the consequences of inaction, “This includes leveraging alternative talent pools that are AI-ready, co-creating measures of productivity with their workforces, and developing a deep understanding of and proficiency in implementing a skills-based approach to hiring and talent development. Only then will leaders be able to avoid the risk of losing critical workers and advance their innovation agenda.”