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Is your super helpful generative AI partner secretly making your job boring?

DATE POSTED:May 14, 2025
Is your super helpful generative AI partner secretly making your job boring?

Recent research shows that when people team up with generative artificial intelligence (GenAI) to complete tasks, they do better at the task right away. Yet, this short-term boost comes with a hidden cost: once people go back to working on their own, they often feel less motivated and more bored. Below, we explain these findings in clear terms and offer practical ideas for balancing AI support and personal engagement.

  • Immediate performance gains: Collaborating with AI helps people produce higher-quality work right away.
  • Motivation drop: After switching back to solo work, people report feeling less driven by interest or enjoyment.
  • Increased boredom: Tasks that follow AI-assisted work feel more tedious, reducing engagement.
Why people turn to AI partners

Generative AI tools like ChatGPT can generate text, ideas, or even code at impressive speed and quality. In professional settings—whether writing emails, brainstorming product improvements, or crafting reports—these systems act like an extra teammate who never gets tired.

Researchers wanted to know two things:

  • Does working with AI make people perform better on following tasks done alone?
  • How does the switch from AI help to independent work affect people’s feelings about the tasks?
How the studies worked

Four online experiments involved over 3,500 participants. Each person completed two tasks in a row. In some cases, they did both tasks by themselves (Solo-Solo). In others, they did the first task with AI support and then the second task alone (Collab-Solo). A final experiment also looked at switching from solo work to AI support (Solo-Collab) and doing both tasks with AI (Collab-Collab).

After each task, participants rated how much control they felt, how motivated they were, and how bored they felt. Independent judges also scored the quality of their work.

What the research revealed

  • Immediate performance boost: Participants who used AI produced more engaging posts, longer reports, and more socially warm emails compared to those who worked alone. These results were consistent across different tasks and measures.
  • No lasting spillover effect: Contrary to expectations, AI assistance did not make people perform better on the next task when done solo. In some cases, their work was slightly worse than those who never used AI.
  • Shift in psychological experience: Switching from AI collaboration to solo work led to:
  • Higher sense of control: People felt more in charge once AI was removed.
  • Lower intrinsic motivation: Interest and enjoyment dropped significantly.
  • Greater boredom: Tasks felt duller after the AI-assisted activity.
  • Order matters: Moving from solo to AI also reduced control and motivation, though in different ways.

AI finally solves biology’s hardest puzzle

Why motivation and boredom change

Self-Determination Theory suggests that people need autonomy, competence, and relatedness to stay motivated. When AI does much of the creative work, people may feel less competent or autonomous. Then, when they return to doing everything by themselves, the contrast makes tasks feel harder to enjoy. Tasks become more routine, triggering boredom.

To make the most of AI help without losing motivation, consider these strategies:

  • Balance AI and solo tasks: Alternate between AI-assisted and independent work in a way that maintains challenge and novelty.
  • Set clear roles: Use AI for repetitive or data-heavy parts and keep the creative or decision-making steps for yourself.
  • Build in autonomy: Personalize prompts or edit AI outputs so you remain in control of the final product.
  • Vary task types: Mix analytical tasks with brainstorming or hands-on activities to reduce monotony.

Generative AI offers clear benefits for immediate task performance. Yet, to keep long-term motivation and engagement high, it is essential to thoughtfully integrate AI assistance into workflows.

Featured image credit