When Standard Is Not Enough: A Conceptualization of AI Systems' Customization and its Antecedents

Item Type Conference or Workshop Item (Paper)
Abstract The centrality of information systems (IS) customization to match companies' needs with software systems available in the market has been researched extensively. The distinctive characteristics of Artificial Intelligence (AI) systems compared to other types of IS suggest that customization needs a new conceptualization in this context. We draw on evidence from expert interviews to conceptualize customization of AI systems as composed of four layers: data, models, algorithms, infrastructures. We identify a continuum of levels of customization, from no to complete customization. Since companies customize AI systems in response to business needs, we develop a theoretical model with six antecedents of AI systems' customization choices. In so doing, we contribute to both AI management research, by introducing the IS customization perspective in the field, and IS customization literature, by introducing AI systems as a novel class of systems and enlarging the understanding of customization for a specific class of software systems.
Authors Diaferia, Lorenzo; Blohm, Ivo; Leonardo Maria, De Rossi & Salviotti, Gianluca
Language English
Subjects information management
HSG Classification contribution to scientific community
HSG Profile Area SoM - Business Innovation
Date 9 December 2022
Event Title International Conference on Information Systems (ICIS)
Event Location Copenhagen, Denmark
Event Dates 09-12 Dec 2022
Depositing User Prof. Dr. Ivo Blohm
Date Deposited 18 Oct 2022 07:27
Last Modified 18 Oct 2022 07:27
URI: https://www.alexandria.unisg.ch/publications/267608

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Diaferia, Lorenzo; Blohm, Ivo; Leonardo Maria, De Rossi & Salviotti, Gianluca: When Standard Is Not Enough: A Conceptualization of AI Systems' Customization and its Antecedents. 2022. - International Conference on Information Systems (ICIS). - Copenhagen, Denmark.

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https://www.alexandria.unisg.ch/id/eprint/267608
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