Paper Number
2158
Paper Type
Complete Research Paper
Abstract
Incumbent firms feel pressured to incorporate artificial intelligence (AI) in their business model (BM) to innovate and stay competitive. While transforming the BM with digital technologies is challenging, AI adds complexity through its countless applications and incomprehensible nature. Unraveling this complexity, we develop a taxonomy to describe and analyze how AI impacts incumbent BMs. The taxonomy builds on extant literature and the analysis of 46 empirical cases. Our findings reveal AI’s roles in enhancing and transforming offerings, key operations, and financial logic. In addition, the taxonomy highlights different ways incumbents provide AI capabilities and data as key resources for the resulting BM. Despite the hype around AI, we critically reflect that most of AI’s impact corresponds to well-known digital BM concepts (e.g., personalization). However, AI technology‘s progress might intensify the effectiveness of those BMs and spur novel opportunities within the known digital BM space.
Recommended Citation
Weber, Michael; Knabl, Oliver Benjamin; Böttcher, Timo Phillip; Hein, Andreas; and Krcmar, Helmut, "The AI Transformation? Unpacking the Impact of AI on Incumbent Business Models" (2024). ECIS 2024 Proceedings. 11.
https://aisel.aisnet.org/ecis2024/track12_digtrans/track12_digtrans/11
The AI Transformation? Unpacking the Impact of AI on Incumbent Business Models
Incumbent firms feel pressured to incorporate artificial intelligence (AI) in their business model (BM) to innovate and stay competitive. While transforming the BM with digital technologies is challenging, AI adds complexity through its countless applications and incomprehensible nature. Unraveling this complexity, we develop a taxonomy to describe and analyze how AI impacts incumbent BMs. The taxonomy builds on extant literature and the analysis of 46 empirical cases. Our findings reveal AI’s roles in enhancing and transforming offerings, key operations, and financial logic. In addition, the taxonomy highlights different ways incumbents provide AI capabilities and data as key resources for the resulting BM. Despite the hype around AI, we critically reflect that most of AI’s impact corresponds to well-known digital BM concepts (e.g., personalization). However, AI technology‘s progress might intensify the effectiveness of those BMs and spur novel opportunities within the known digital BM space.
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