The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
Harvard Business School Strategy Unit Working Paper No. 25-043
Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 25-043
56 Pages Posted: 21 Mar 2025 Last revised: 1 Apr 2025
There are 2 versions of this paper
The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
The Cybernetic Teammate: A Field Experiment on Generative Ai Reshaping Teamwork and Expertise
Date Written: March 28, 2025
Abstract
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 commerciallyoriented proposals. Professionals using AI produced balanced solutions, regardless of their professional background. Finally, AI’s language-based interface prompted more positive selfreported 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.
Keywords: Artificial intelligence, Teamwork, Human-machine interaction, Productivity, Skills, Innovation, Field experiment
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