A new study reports substantial increases in productivity and performance when employees worked with artificial intelligence, but what does that tell us about teamwork?
Teams working with GenAI produced the highest quality product innovation solutions.Co-authored by Aleksandra Siwek, Laura Kearney, and Michael Hogan,"The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise," a large-scale field study at Procter & Gamble.
This highly cited study reports substantial increases inand performance when employees worked with AI. In the broader context of teamwork and organisational science, it's valuable to take a closer look at the study to advance understanding of human-AIchallenges in a one-day virtual workshop. Solutions were compared across four experimental conditions: individual working without AI, individual working with AI, two-person team without AI, and two-person team with AI. The AI system was based on GPT-4 accessed through Microsoft Azure.were achieved by teams of two employees working with AI, followed by individuals working with AI and teams without AI. Usingas a productivity index, the most significant time savings were observed for individuals working with AI, followed by two-person teams working with AI.Better product innovation solutions combined both research and design and commercial knowledge. A key benefit was seen for participants working with AI. Without AI, participants produced solutions closely aligned with their area of professional expertise that are relevant for human-AI collaboration. The product innovation task used by Dell’Acqua and colleagues largely involves a series of Generate task functions—iterative creative ideation and deliberation—but also a series of Choose task functions, as individuals and teams converge on solutions. However, without a detailed task-process analysis, it is unclear how Generate, Choose, Execute, and Negotiate task functions are operative in the teamwork scenario. task requiring continuous coordination. In the Cybernetic Teammate study, it is unclear how GenAI might be working independently, and it is unclear how different team member inputs were coordinated.. While Dell’Acqua and colleagues focused on solution quality, it is unclear how the prompts given to humans and AIs aligned with the quality criteria used by experts to evaluate solutions., mutual performance monitoring, backup behaviour, adaptability, and team orientation. These behaviours are sustained and coordinated by mutual trust, closed-loop communication, and shared mental models. Although the Cybernetic Teammate study doesn't analyse these teamwork behaviours, future workplace studies can clarify how GenAI can function as a genuine teammate, including whether it can display these core behaviours.Notably, Dell'Acqua and colleagues interpret positive emotional outcomes as evidence of GenAI emulating teamwork's social aspect. However, their approach to analysis does not address trust and team orientation, which are central to effective teamwork.An important shortcoming of the Cybernetic Teammate and other studies focusing on performance and productivity effects is their limited analysis of team development dynamics. The team development model proposed byis useful here. This model highlights how human-AI teams can evolve through different developmental phases, where the focus shifts fromBy focusing on a one-day workshop, the study takes a snapshot at a single point. The primary focus appears to be task-role development—developing role clarity, capability awareness, and managing task allocation. However, the supporting process isn't fully specified.. These essential human functions cannot be delegated to AI systems. Critical leadership functions are not central to the Cybernetic Teammate study. Nevertheless, this study represents an important step toward developing comprehensive understanding of human-AI teamwork and designing, analysing, and evaluating organisational teamwork dynamics in this new era of GenAI. We have much to learn, and we need to proceed with careful, systematic analysis.Whatever your goals, it’s the struggle to get there that’s most rewarding. It’s almost as if life itself is inviting us to embrace difficulty—not as punishment but as a design feature. It's a robust system for growth.Self Tests are all about you. Are you outgoing or introverted? Are you a narcissist? Does perfectionism hold you back? Find out the answers to these questions and more with Psychology Today.
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