How generative AI can affect employees

In four studies that involved more than 3,500 participants, the researchers explored outcomes of  human collaboration with generative AI on common work tasks.

In the studies, participants completed real-world professional tasks, like writing Facebook posts, brainstorming ideas, and drafting emails, both with and without generative AI. They then assessed both task performance and participants' psychological experiences, including their sense of control, intrinsic motivation, and levels of boredom.

The researchers found that generative AI enhanced both the quality and efficiency of the participants' tasks. For example, performance reviews written with generative AI were significantly longer, more analytical, and conveyed a more helpful tone compared to reviews written without AI.

Similarly, emails drafted with generative AI typically contained warmer, more personable language that included more expressions of encouragement, empathy, and social connection compared to those written without AI.

However, the researchers also found that despite the performance benefits, participants who collaborated with generative AI on one task and then moved on to a different task unaided by AI reported a decline in intrinsic motivation and an increase in boredom. Across the four studies, the researchers found that intrinsic motivation dropped by an average of 11% and boredom increased by an average of 20% in these instances. By comparison, those who worked without AI assistance maintained a fairly consistent psychological state.

These findings suggest that while utilizing generative AI tools can feel productive and empowering at first, it can also leave employees feeling less engaged when they shift to tasks unaided by AI.

Why the phenomenon occurs

According to the researchers, collaborating with generative AI can bypass the most cognitively demanding parts of a task, which are often what makes work stimulating and personally fulfilling.

For example, writing a performance review requires critical thinking and tailored feedback, but when generative AI writes most of this content, the process becomes less engaging, and people can feel disconnected from the task. As a result, when individuals return to work unaided by AI, they become bored and less motivated.

While generative AI can help organizations achieve short-term performance goals, overusing it could have long-term consequences for workers' psychological well-being, the authors write. If employees are consistently relying on AI for creative or cognitively challenging tasks, they risk losing the aspects of work that drive engagement, growth, and satisfaction.

What companies can do in response

According to the authors, the solution to the problem discovered in their research isn't abandoning generative AI, but instead redesigning tasks and workflows to preserve employees' intrinsic motivation while still leveraging AI's strengths.

The authors recommend five strategies:

1. Blend the contributions of humans and AI.

Instead of allowing generative AI to complete entire tasks, integrate AI outputs as a starting point while still encouraging human creativity.

For example, generative AI could draft an outline for a performance review, but the manager should elaborate on the initial content with their personalized insights. Or AI could generate initial ideas for a project while team members expand, refine, and build on them.

2. Design solo tasks that are engaging.

To help counterbalance the psychological costs of AI collaboration, follow up any AI-assisted tasks with work that provide autonomy and a sense of a creative challenge, the authors write.

For example, after drafting emails supported by AI, the authors recommend assigning a task that allows workers to be in control of designing a new project. These tasks will allow employees to exercise their skills, creativity, and decision-making without needing AI.

3. Be transparent with AI collaboration.

The authors write that their study found workers can feel disengaged when they believe AI has taken control. Clearly communicating how AI is assisting and not replacing their contributions can help workers maintain a sense of ownership and fulfillment in their tasks.

4. Rotate between different tasks.

Organizations can sustain both productivity and engagement by structuring workflows to alternate between independent tasks and those assisted with AI, the authors Liu and Wu write. Instead of clustering similar tasks together, managers can sequence the day to start with the cognitively demanding solo work and shift to AI-supported tasks later.

5. Train employees to use AI mindfully.

To avoid being over-dependent on AI, organizations can provide training to build employees' ability to utilize generative AI thoughtfully and effectively, the authors write.

This could include running workshops on prompt writing, engaging in critical evaluations of AI-generated content, or introducing scenario-based exercises that highlight when human judgment should take over. Workers can learn how AI can complement their work and what part their own skills must play, which can help foster autonomy, creativity, and long-term skill development.

"Human-gen AI collaboration has immense potential to boost productivity and performance, but organizations must be mindful of its psychological consequences," the authors write. "By thoughtfully designing workflows that integrate gen AI, businesses can unlock its benefits without compromising workers' motivation and engagement. After all, the future of work isn't just about what AI can do — it's about what humans and AI can achieve together."

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