Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
Customer support service employees are facing increased workload, while artificial intelligence (AI) appears to possess the potential to change the way we work. With the advent of modern types of generative AI, new opportunities to augment frontline service employees have emerged. However, little is known about how to integrate generative AI in customer support service organizations and purposefully change service employee work routines. Following a multi-method qualitative research, we performed a literature review, conducted workshops, and interviewed IT support agents, managers, and AI experts. Thereby, we examine AI augmentation for frontline service employees in the context of IT support to carve out where and how GenAI can be leveraged to develop a more efficient and higher-quality customer support. Our resulting framework reveals that especially adapting solutions and retaining knowledge is subject to a high degree of AI augmentation.
Recommended Citation
Reinhard, Philipp; Li, Mahei; Peters, Christoph; and Leimeister, Jan Marco, "Generative AI in Customer Support Services: A Framework for Augmenting the Routines of Frontline Service Employees" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 10.
https://aisel.aisnet.org/hicss-57/cl/ai_and_future_work/10
Generative AI in Customer Support Services: A Framework for Augmenting the Routines of Frontline Service Employees
Hilton Hawaiian Village, Honolulu, Hawaii
Customer support service employees are facing increased workload, while artificial intelligence (AI) appears to possess the potential to change the way we work. With the advent of modern types of generative AI, new opportunities to augment frontline service employees have emerged. However, little is known about how to integrate generative AI in customer support service organizations and purposefully change service employee work routines. Following a multi-method qualitative research, we performed a literature review, conducted workshops, and interviewed IT support agents, managers, and AI experts. Thereby, we examine AI augmentation for frontline service employees in the context of IT support to carve out where and how GenAI can be leveraged to develop a more efficient and higher-quality customer support. Our resulting framework reveals that especially adapting solutions and retaining knowledge is subject to a high degree of AI augmentation.
https://aisel.aisnet.org/hicss-57/cl/ai_and_future_work/10