AI burnout: The hidden cost of rapid technology adoption

NEW JERSEY, UNITED STATES — As companies rush to adopt artificial intelligence (AI) and generative AI technologies, a new concern is emerging: employee burnout. 

While AI promises increased efficiency and productivity, the fast pace of its implementation is straining resources and overwhelming workers, leading to stress and exhaustion.

Employee concerns and AI anxiety

A recent survey conducted by Resume Now in March 2024 revealed that 63% of U.S. workers express fears about AI use, while 61% are concerned it will increase burnout. 

Nearly 90% of young workers fear AI-related burnout, and about half of the women surveyed believe AI will negatively impact work-life balance.

“Workers hear that and naturally worry that their workload will skyrocket, right along with productivity expectations,” Heather O’Neill, career expert at Resume Now, explained. 

“But fears about being overworked aren’t the only things that can cause AI-related burnout. Worries about what it will take to keep pace in this new work landscape are also nerve-wracking.”

Resource constraints and workload pressure

“We’re not getting additional resources to evaluate AI for its potential benefit,” Bob Huber, chief security officer at Tenable told CNBC.

“The resources have to come from elsewhere, whether that’s via reprioritization of people’s time or placing other projects on the back burner.”

This situation can lead to employees being double or triple-tasked, straining already limited resources. While some AI use cases require minimal effort, Huber noted that “the majority of use cases require dedicated resources to build, design and evaluate.”

Preventing AI-related burnout

To mitigate the risk of burnout, Huber and O’Neill shared several steps companies can take:

• Gradual Implementation: Huber recommends introducing AI initiatives gradually, avoiding “moonshots” that require significant resources.
• Clear Communication: O’Neill emphasizes the importance of clear messaging about AI use, including how it will be integrated and its timeline for adoption.
• Employee Feedback: HR departments should be open to employee feedback about how AI can help them work more efficiently and address any concerns.
• Realistic Expectations: Leadership should prioritize work for people and set realistic expectations to ensure teams understand business goals.
• Reassurance and Training: Companies should remind workers that AI is intended to help with repetitive tasks, allowing them to focus on higher-level projects.