Paper Number
ICIS2025-1326
Paper Type
Short
Abstract
As generative AI becomes embedded in team workflows, understanding how collaboration modes shape outcomes is increasingly important. This study explores two approaches—shared-screen and individual-instance—through the lens of Adaptive Structuration Theory (AST), which emphasizes how teams adapt technology based on social and technical dynamics. Using a quasi-experimental design with six small teams, the study examines how these modes affect engagement, decision-making, communication, and knowledge sharing. Distributed teams favored individual-instance use, while co-located teams either remained in shared-screen mode or shifted adaptively. Results show that shared-screen collaboration supports real-time coordination but can limit individual contribution, whereas individual-instance use promotes idea diversity but requires more integration effort. Hybrid patterns emerged as flexible responses to task complexity. The findings offer insights into AI appropriation in group settings and practical guidance for designing adaptive AI-supported collaboration.
Recommended Citation
Sun, Jun; Islam, Md Rafiqul; and Wang, Ying, "Collaboration with Generative AI: Adaptive Structuration Across Shared and Individual Use Models" (2025). ICIS 2025 Proceedings. 11.
https://aisel.aisnet.org/icis2025/user_behav/user_behav/11
Collaboration with Generative AI: Adaptive Structuration Across Shared and Individual Use Models
As generative AI becomes embedded in team workflows, understanding how collaboration modes shape outcomes is increasingly important. This study explores two approaches—shared-screen and individual-instance—through the lens of Adaptive Structuration Theory (AST), which emphasizes how teams adapt technology based on social and technical dynamics. Using a quasi-experimental design with six small teams, the study examines how these modes affect engagement, decision-making, communication, and knowledge sharing. Distributed teams favored individual-instance use, while co-located teams either remained in shared-screen mode or shifted adaptively. Results show that shared-screen collaboration supports real-time coordination but can limit individual contribution, whereas individual-instance use promotes idea diversity but requires more integration effort. Hybrid patterns emerged as flexible responses to task complexity. The findings offer insights into AI appropriation in group settings and practical guidance for designing adaptive AI-supported collaboration.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
16-UserBehavior