Paper Number
1566
Paper Type
Short Paper
Abstract
Generative Artificial Intelligence (GAI) generated widespread enthusiasm for its formidable capabilities in natural language processing and content generation. Yet, we know very little about how it is used in practice. Through an exploratory single case study in a multinational corporation, this paper investigates how developers - typical frontline knowledge like data scientists, machine learning experts, and software engineers - used and precepted GAI. We explore how and to what extent their work and learning approaches were impacted, presenting preliminary findings of the knowledge work areas impacted by GAI usage. To that end, we discuss implications for knowledge workers and organizations alike.
Recommended Citation
Jiang, Mingyuan; Karanasios, Stan; and Breidbach, Christoph, "Generative AI in the Wild: An Exploratory Case Study of Knowledge Workers" (2024). ECIS 2024 Proceedings. 7.
https://aisel.aisnet.org/ecis2024/track04_impactai/track04_impactai/7
Generative AI in the Wild: An Exploratory Case Study of Knowledge Workers
Generative Artificial Intelligence (GAI) generated widespread enthusiasm for its formidable capabilities in natural language processing and content generation. Yet, we know very little about how it is used in practice. Through an exploratory single case study in a multinational corporation, this paper investigates how developers - typical frontline knowledge like data scientists, machine learning experts, and software engineers - used and precepted GAI. We explore how and to what extent their work and learning approaches were impacted, presenting preliminary findings of the knowledge work areas impacted by GAI usage. To that end, we discuss implications for knowledge workers and organizations alike.
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