The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
Source: Dell'Acqua et al., NBER w33641 · 2025-04
We examine how artificial intelligence transforms the core pillars of collaboration—performance, expertise sharing, and social engagement—through a pre-registered field experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods company. Working on real product innovation challenges, professionals were randomly assigned to work either with or without AI, and either individually or with another professional in new product development teams. Our findings reveal that AI significantly enhances performance: individuals with AI matched the performance of teams without AI, demonstrating that AI can effectively replicate certain benefits of human collaboration. Moreover, AI breaks down functional silos. Without AI, R&D professionals tended to suggest more technical solutions, while Commercial professionals leaned towards commercially-oriented proposals. Professionals using AI produced balanced solutions, regardless of their professional background. Finally, AI’s language-based interface prompted more positive self-reported emotional responses among participants, suggesting it can fulfill part of the social and motivational role traditionally offered by human teammates. Our results suggest that AI adoption at scale in knowledge work reshapes not only performance but also how expertise and social connectivity manifest within teams, compelling organizations to rethink the very structure of collaborative work.
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Can AI research automation improve discovery pace without sacrificing quality? How does AI assistance affect professional skill development and retention? Does AI coding assistance improve productivity and code quality across experience levels? Does generative AI shift knowledge work away from collaborative tasks?- Does generative AI push knowledge workers toward different types of tasks?
- Does generative AI adoption shift work away from coordination tasks?
- Does AGI focus distract firms from developing task-creating AI innovations?
- Does AI shift knowledge work away from communication toward solo documentation tasks?
- Does AI adoption push knowledge work away from communication toward solo tool use?
- Can individuals using AI match the output of teams without AI?
- Does generative AI improve immediate task performance but not sustained independent work?
- How often do enterprise generative AI pilots produce measurable financial returns?
- When does generative AI reduce versus amplify existing skill differences?
- How do workers actually choose to use generative AI in practice?
- Does AI-assisted work reduce time spent on coordination and communication?
- Does benefit from AI partnership depend on the individual worker?
- What specific training approaches help managers integrate AI into team workflows?
- Are heavy AI users spending more time on solo work instead of collaboration?
- What evidence exists that collaborative AI systems actually improve team outcomes?
- Why did hybrid human-AI teams fail to improve on the best standalone model?
- When does AI collaboration actually improve team outcomes instead of burdening them?
- How much coordination must teams achieve before AI tools reshape workflow?