Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
As Generative Artificial Intelligence (AI) is encroaching further on our work and social environments, we examine the increasingly common situation where teams of white-collar workers include both humans and AI. We explore three key themes via a comprehensive (n=122) systematic literature review: key success factors, use cases for human-AI teams, and challenges faced when implementing human-AI teams. The key success factors identified discuss the need for clear roles and responsibilities by playing to human and AI strengths, skill development and system transparency. Use cases can be grouped into problem-solving, decision-making, routine tasks, and personal assistants. Finally, the identified challenges relate to system trustworthiness, biases, time and effort to adopt, AI using data, and job insecurity. We conclude by identifying avenues for future research based on the gaps identified throughout this review.
Recommended Citation
Latto, Chloe; Richter, Alexander; and Tate, Mary, "Human-AI Teams' Impact on Organizations - A Review" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 7.
https://aisel.aisnet.org/hicss-58/cl/ai_and_future_work/7
Human-AI Teams' Impact on Organizations - A Review
Hilton Waikoloa Village, Hawaii
As Generative Artificial Intelligence (AI) is encroaching further on our work and social environments, we examine the increasingly common situation where teams of white-collar workers include both humans and AI. We explore three key themes via a comprehensive (n=122) systematic literature review: key success factors, use cases for human-AI teams, and challenges faced when implementing human-AI teams. The key success factors identified discuss the need for clear roles and responsibilities by playing to human and AI strengths, skill development and system transparency. Use cases can be grouped into problem-solving, decision-making, routine tasks, and personal assistants. Finally, the identified challenges relate to system trustworthiness, biases, time and effort to adopt, AI using data, and job insecurity. We conclude by identifying avenues for future research based on the gaps identified throughout this review.
https://aisel.aisnet.org/hicss-58/cl/ai_and_future_work/7