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Development of a Task Model for Artificial Intelligence-Based Applications for Small and Medium-Sized Enterprises

  • The adoption of artificial intelligence (AI) technologies in manufacturing companies is challenging, particularly for SMEs that lack the necessary skills to develop and integrate AI-based applications (AI applications) into their existing IT system landscape. To address this challenge, the research project VoBAKI (IGF-Project No.: 22009 N) aims to enable SMEs to identify and close skill gaps related to AI application development and implementation using proper sourcing strategies. This paper presents the interim results from the second phase of the project, which involves identifying the tasks in the lifecycle of AI applications and determining the specific skills required for executing these tasks. The presented results provide a detailed lifecycle including the phases for the development and usage of AI applications, as well as the specific tasks that SMEs must consider when implementing an AI application. These results serve as the foundation for future research regarding the required skills to execute the presented tasks and provide a roadmap for SMEs to close skill gaps and successfully implement AI applications.

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Metadaten
Verfasserangaben:Florian Clemens, Fabian Willemsen, Susanne Mütze-Niewöhner, Günther SchuhORCiDGND
URL:https://link.springer.com/chapter/10.1007/978-3-031-43662-8_38
DOI:https://doi.org/10.1007/978-3-031-43662-8_38
ISBN:978-3-03143-661-1
ISBN:978-3-031-43662-8
ISSN:1868-4238
Titel des übergeordneten Werkes (Englisch):Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. IFIP WG 5.7 International Conference, APMS 2023, Trondheim, Norway, September 17–21, 2023, Proceedings, Part I
Schriftenreihe (Bandnummer):IFIP advances in information and communication technology (689)
Verlag:Springer
Ort:Cham [u. a.]
Herausgeber*in:Erlend Alfnes, Anita Romsdal, Jan Ola Strandhagen, Gregor von Cieminski, David Romero
Dokumentart:Konferenzveröffentlichung
Sprache:Englisch
Jahr der Fertigstellung:2023
Datum der Erstveröffentlichung:14.09.2023
Datum der Freischaltung:21.09.2023
Freies Schlagwort / Tag:rev
SME; artificial intelligence; artificial intelligence lifecycle; decision-maker; machine learning; manufacturing company
Erste Seite:528
Letzte Seite:542
FIR-Nummer:SV7773
Institut / Bereiche des FIR:FIR e. V. an der RWTH Aachen
Informationsmanagement
DDC-Klassifikation:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften