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A 3 phases model towards an industrialization of (generative) artificial intelligence developed for corporate environments

dc.contributor.authorPrzewloka, Martin
dc.contributor.editorMarkus Böhm, Jürgen Wunderlich
dc.date.accessioned2024-10-01T10:15:42Z
dc.date.available2024-10-01T10:15:42Z
dc.date.issued2024
dc.description.abstractCompanies face major challenges when it comes to developing a strategic approach related to artificial intelligence (AI). The massive wave of generative models that has just started is another indication that technology adaptation is associated with very large uncertainties. As a result, a large number of undirected activities in corporates occur in which so-called use cases, prototypes and minimum viable products are implemented. A targeted and strategic approach is hardly recognizable. The aim of the work carried out here was to develop a practical model that meets all parameters: moving forward quickly, learning from mistakes, developing unique selling points and thus competitive advantages ultimately resulting in an AI strategy. This is exactly what can be achieved in 3 steps, the efficiency phase, the competitive advantage phase and the transformation phase, all of which build on one another sequentially. The model presented here also makes a significant contribution to the development and adaptation of a responsible AI.en
dc.identifier.doi10.18420/AKWI2024-018
dc.identifier.isbn978-3-88579-801-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44657
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofAKWI Jahrestagung 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-357
dc.subjectdigital transformation
dc.subjectgenerative AI
dc.subjectcompetitive advantages
dc.subjecttechnology-push
dc.subjectclinical trials
dc.subjectclinical studies
dc.subjectkey performance indicators
dc.subjectchange management
dc.subjectresponsible AI
dc.subjectefficiency
dc.titleA 3 phases model towards an industrialization of (generative) artificial intelligence developed for corporate environmentsen
dc.typeText/Conference Paper
gi.citation.endPage205
gi.citation.publisherPlaceBonn
gi.citation.startPage201
gi.conference.date09.-10.09.2024
gi.conference.locationHAW-Landshut
gi.conference.sessiontitlePoster Presentations

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