Ergebnisse

@inproceedings{Kirschbaum2022,

title = {Use-Case-based Innovation for Artificial Intelligence - An ontological Approach},

author = {Julius Kirschbaum and Tim Posselt and Angela Roth},

url = {https://www.researchgate.net/publication/361667326_Use-case-based_innovation_for_artificial_intelligence_-_An_ontological_approach},

year  = {2022},

date = {2022-06-21},

urldate = {2022-06-21},

booktitle = {ECIS 2022 Proceedings},

publisher = {AIS Electronic Library (AISeL)},

abstract = {Research has primarily focused on process models for AI-use-case-adoption, but neglected the use-cases themselves. In this research, an ontological artifact is developed as the basis for an AI-use-case-description-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 = {Adoption, Artificial Intelligence, IIP-Ecosphere, Innovation, Künstliche Intelligenz, Ontology, Use Case},

pubstate = {published},

tppubtype = {inproceedings}

}