The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective

Dominik K. Kanbach (), Louisa Heiduk (), Georg Blueher (), Maximilian Schreiter () and Alexander Lahmann ()
Additional contact information
Dominik K. Kanbach: HHL Leipzig Graduate School of Management
Louisa Heiduk: HHL Leipzig Graduate School of Management
Georg Blueher: HHL Leipzig Graduate School of Management
Maximilian Schreiter: HHL Leipzig Graduate School of Management
Alexander Lahmann: HHL Leipzig Graduate School of Management

Review of Managerial Science, 2024, vol. 18, issue 4, No 9, 1189-1220

Abstract: Abstract The introduction of ChatGPT in November 2022 by OpenAI has stimulated substantial discourse on the implementation of artificial intelligence (AI) in various domains such as academia, business, and society at large. Although AI has been utilized in numerous areas for several years, the emergence of generative AI (GAI) applications such as ChatGPT, Jasper, or DALL-E are considered a breakthrough for the acceleration of AI technology due to their ease of use, intuitive interface, and performance. With GAI, it is possible to create a variety of content such as texts, images, audio, code, and even videos. This creates a variety of implications for businesses requiring a deeper examination, including an influence on business model innovation (BMI). Therefore, this study provides a BMI perspective on GAI with two primary contributions: (1) The development of six comprehensive propositions outlining the impact of GAI on businesses, and (2) the discussion of three industry examples, specifically software engineering, healthcare, and financial services. This study employs a qualitative content analysis using a scoping review methodology, drawing from a wide-ranging sample of 513 data points. These include academic publications, company reports, and public information such as press releases, news articles, interviews, and podcasts. The study thus contributes to the growing academic discourse in management research concerning AI's potential impact and offers practical insights into how to utilize this technology to develop new or improve existing business models.

Keywords: Artificial intelligence; Generative AI; ChatGPT; Business model innovation; Large language models (search for similar items in EconPapers)
JEL-codes: M10 M13 M15 M19 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11846-023-00696-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:rvmgts:v:18:y:2024:i:4:d:10.1007_s11846-023-00696-z

Ordering information: This journal article can be ordered from
http://www.springer.com/business/journal/11846

DOI: 10.1007/s11846-023-00696-z

Access Statistics for this article

Review of Managerial Science is currently edited by R. Ewert and W. Kürsten

More articles in Review of Managerial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().