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Paper Number
1848
Paper Type
Completed
Description
AI as a Service (AIaaS) is a promising path to leverage AI capabilities from the cloud. However, there is no one-size-fits-all service, but heterogenous service options since interdependent AIaaS characteristics require trade-offs. We lack knowledge on these trade-offs and how they result from conflicting characteristics. Therefore, we interviewed 39 AIaaS providers, customers, and consultants to provide rich descriptions of interdependent characteristics and uncover resulting trade-offs and their consequences. This study contributes to a better understanding of the inner functioning and interplay of AIaaS characteristics and discusses how this complex nature of service offerings impacts providers’ design and customers’ selection decisions.
Recommended Citation
Brecker, Kathrin; Lins, Sebastian; Trenz, Manuel; and Sunyaev, Ali, "Artificial Intelligence as a Service: Trade-Offs Impacting Service Design and Selection" (2023). ICIS 2023 Proceedings. 5.
https://aisel.aisnet.org/icis2023/itadopt/itadopt/5
Artificial Intelligence as a Service: Trade-Offs Impacting Service Design and Selection
AI as a Service (AIaaS) is a promising path to leverage AI capabilities from the cloud. However, there is no one-size-fits-all service, but heterogenous service options since interdependent AIaaS characteristics require trade-offs. We lack knowledge on these trade-offs and how they result from conflicting characteristics. Therefore, we interviewed 39 AIaaS providers, customers, and consultants to provide rich descriptions of interdependent characteristics and uncover resulting trade-offs and their consequences. This study contributes to a better understanding of the inner functioning and interplay of AIaaS characteristics and discusses how this complex nature of service offerings impacts providers’ design and customers’ selection decisions.
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