Paper Number
1921
Paper Type
Short
Abstract
The diffusion of public Generative Artificial Intelligence (GenAI) tools such as ChatGPT has prompted many firms to (re-) consider how to integrate GenAI technology into their daily operations. We are studying a prominent German automotive manufacturer that started developing an inhouse generative conversational AI tool as an assistant for the daily tasks of all their employees. At his point, we have completed 31 interviews with development team members and pilot testers. Through inductive data analysis, we identified three relevant clusters of aspects – challenges, success factors, and potential benefits of GenAI development, which each span institutional, social, and technical dimensions. Once completed, our study will contribute new empirical and theoretical insights about GenAI development in large firms.
Recommended Citation
Grashoff, Imke; Mayer, Thomas; and Recker, Jan, "Challenges, Success Factors, and Potential Benefits of GenAI Development: Insights from an Ongoing Case Study at a German Automotive Manufacturer" (2024). ICIS 2024 Proceedings. 20.
https://aisel.aisnet.org/icis2024/aiinbus/aiinbus/20
Challenges, Success Factors, and Potential Benefits of GenAI Development: Insights from an Ongoing Case Study at a German Automotive Manufacturer
The diffusion of public Generative Artificial Intelligence (GenAI) tools such as ChatGPT has prompted many firms to (re-) consider how to integrate GenAI technology into their daily operations. We are studying a prominent German automotive manufacturer that started developing an inhouse generative conversational AI tool as an assistant for the daily tasks of all their employees. At his point, we have completed 31 interviews with development team members and pilot testers. Through inductive data analysis, we identified three relevant clusters of aspects – challenges, success factors, and potential benefits of GenAI development, which each span institutional, social, and technical dimensions. Once completed, our study will contribute new empirical and theoretical insights about GenAI development in large firms.
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