Focus on meaningful core work with AI

Citation: Hoffmann, M., Boysel, S., Nagle, F., Peng, S., & Xu, K. (2024). Generative AI and the Nature of Work (SSRN Scholarly Paper No. 5007084). Social Science Research Network.

While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI?

Note: It’s worth pointing out that these researchers refer to software developers as ‘knowledge workers’, a phrase that can also be applied to academics.

Summary

This study describes how access to GitHub Copilot, a generative AI coding tool, changes the work patterns of software developers. The researchers found that when developers had access to AI assistance, they:

1. Increased their core coding work
2. Decreased their project management activities
3. Shifted toward more autonomous (vs collaborative) work
4. Engaged in more exploratory (vs routine) activities
5. Showed stronger effects among less experienced developers

The findings suggest AI tools can help professionals focus more on their primary creative work while reducing administrative burden. In other words, AI tools can help knowledge workers reallocate their time and energy.

Implications for academics

Like software developers, academics often find themselves pulled away from their core scholarly work (research, writing, deep thinking) by administrative and management tasks. The paper suggests that appropriate AI tools could help academics:

• Return focus to their primary intellectual work
• Reduce time spent on administrative tasks
• Work more autonomously when beneficial
• Explore new research directions more readily
• Level the playing field for less experienced scholars

Practical takeaways

• Strategic AI integration. Consider adopting AI tools for administrative and routine tasks that pull you away from core scholarly work. For example, use AI for email drafting, meeting summaries, or initial literature review organisation, freeing up more time for deep thinking and writing.
• Autonomous work blocks. Create dedicated time blocks for autonomous, AI-assisted work. Just as developers in the study became more productive with independent work sessions, academics might benefit from focused periods using AI tools for initial drafting, outlining, or research planning, before moving to collaborative phases.
• Exploratory research practice. Use AI tools to support more exploratory research approaches. The study showed that AI enabled more experimentation; academics could use AI tools to explore new research directions, test initial ideas, or make novel connections across disciplines with lower time investment and risk.

This research suggests that strategic use of AI could help reduce the feeling of being overwhelmed by enabling more focus on meaningful core work while streamlining administrative tasks.