Paper Number
1840
Abstract
Research has primarily focused on process models for AI-use-case-adoption, but neglected the usecases themselves. In this research, an ontological artifact is developed as the basis for an AI-use-casedescription-scheme. It allows practitioners and researchers to systematically describe such use-cases based on their level of abstraction and core characteristics. It enables them to classify, document and communicate these use-cases to support AI-adoption. We ground its development in diffusion of innovation theory and build upon research on AI-adoption. In particular, Rogers’ (2003) innovation decision process is utilised as a framework that explains adoption decisions by organisations. A Design Science Research approach is chosen that integrates the ontology development process by Noy and McGuinness (2001). In this research-in-progress, we conduct one ex ante and one ex post evaluation and plan for a second ex post evaluation that ensure the relevance and rigor of the artifact design. Keywords: artificial intelligence, innovation, adoption, use-case, ontology
Recommended Citation
Kirschbaum, Julius; Posselt, Tim; and Roth, Angela, "USE-CASE-BASED INNOVATION FOR ARTIFICIAL INTELLIGENCE – AN ONTOLOGICAL APPROACH" (2022). ECIS 2022 Research-in-Progress Papers. 64.
https://aisel.aisnet.org/ecis2022_rip/64
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.