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Navigating Public Sentiment : Acceptance of Disruptive Innovations Created by Transformational Generative AI

Title data

Mayer, Valentin ; Guggenberger, Tobias:
Navigating Public Sentiment : Acceptance of Disruptive Innovations Created by Transformational Generative AI.
In: Proceedings of the 32nd European Conference on Information Systems (ECIS). - Paphos, Cyprus , 2024

Official URL: Volltext

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Abstract in another language

The advance of generative artificial intelligence (GenAI) is rapidly progressing and inundating markets with its outputs. Moreover, the creativity of these systems is increasing, potentially leading to the creation of disruptive innovations in the future. Previously, research has examined acceptance of Artificial Intelligence (AI) systems and disruptive innovations independently. We are combining two research areas to shift the focus from studying the acceptance of AI systems to examining the acceptance of GenAI generated disruptive innovations. Thus, we ask, what factors drive the acceptance of disruptive innovations created by GenAI? Therefore, we conducted 18 interviews with 19 AI experts and identified several factors that could enhance acceptance in this case. The perceived usefulness of disruptive innovations appears to be the key factor, which indicates internal validity with existing research. However, higher quality expectations and the desire for traceability and comparability of disruptive innovations suggest a distinction from human-created ones.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Generative artificial intelligence; acceptance; disruptive innovation; creativity
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Profile Fields
Profile Fields > Emerging Fields
Profile Fields > Emerging Fields > Innovation and Consumer Protection
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT
Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 12 Jun 2024 09:28
Last Modified: 12 Jun 2024 09:28
URI: https://eref.uni-bayreuth.de/id/eprint/89748