We examine how artificial intelligence (AI) impacts three core pillars of collaboration—performance enhancement, expertise integration, and social engagement—through a preregistered field experiment with 791 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 show that (1) AI significantly enhances performance: individuals with AI matched the performance of teams without AI, suggesting that AI can effectively replicate certain benefits of human collaboration. Moreover, (2) AI helps bridge functional silos: without AI, research and development professionals tended to suggest more technical solutions, whereas commercial professionals leaned toward commercially oriented proposals. Professionals using AI produced more balanced solutions, regardless of their professional background. (3) 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. Finally, decomposing the innovation process suggests that AI primarily enhances the quality of generated ideas, shifting the distribution of creative output upward, whereas human judgment retains value in evaluative selection. This finding highlights the multiple and complementary roles that human and AI partners can play in new product development tasks and creative problem solving. More generally, our results suggest that AI adoption in knowledge work affects not only performance but also how expertise and sociality appear within teams, offering insights into the impact of generative AI on collaborative work within organizations. Funding: Funding for this research was provided in part by Harvard Business School. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2025.20702 .
Dell’Acqua et al. (Fri,) studied this question.