Paper Type

ERF

Abstract

Generative AI tools are increasingly used in software development. While evidence suggests potential gains in speed and productivity, generative AI also introduces evaluation uncertainty through hallucinations, prompt sensitivity, and non-determinism. At the team level, these properties can reshape interaction patterns and shift the balance of coordination mechanisms used to integrate interdependent work. Drawing on coordination theory and Adaptive Structuration Theory, we develop a model in which AI augmentation shapes horizontal and vertical coordination, with implications for team performance. The model proposes that consensus on AI appropriation moderates these relationships by shaping shared norms for appropriate use, verification, disclosure, and integration of AI-assisted work. This paper contributes a coordination-centered perspective on when AI augmentation improves versus disrupts team performance and offers guidance for future research and practice.

Paper Number

1789

Comments

SIG OSRA

Download

Share

COinS
 
Aug 15th, 12:00 AM

The Impacts of AI Augmentation and Consensus on AI Appropriation in Software Development Teams

Generative AI tools are increasingly used in software development. While evidence suggests potential gains in speed and productivity, generative AI also introduces evaluation uncertainty through hallucinations, prompt sensitivity, and non-determinism. At the team level, these properties can reshape interaction patterns and shift the balance of coordination mechanisms used to integrate interdependent work. Drawing on coordination theory and Adaptive Structuration Theory, we develop a model in which AI augmentation shapes horizontal and vertical coordination, with implications for team performance. The model proposes that consensus on AI appropriation moderates these relationships by shaping shared norms for appropriate use, verification, disclosure, and integration of AI-assisted work. This paper contributes a coordination-centered perspective on when AI augmentation improves versus disrupts team performance and offers guidance for future research and practice.

When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.