How Siemens Democratized Artificial Intelligence
Publication Date
3-1-2023
Abstract
The steep rise of artificial intelligence (AI) has spawned new value promises for industry, academia and society. Estimates suggest that in 2030, AI could contribute between $13 trillion 3 and $15.7 trillion 4 to global GDP. The common assumption underlying such estimates is that firms are and will widely adopt AI technologies 5 to transform products and services, processes and even entire business models to create value. The reality, however, portrays a different picture: organizations struggle to progress AI pilots and prototypes successfully into productive use and scalable market offerings. One of the main reasons for the lack of progress is the difficulty of making modern-day AI technologies (e.g., machine learning and deep learning 6) broadly accessible to organizational members in a way that enables them to explore and realize valuable AI applications. 1 Hind Benbya is the accepting senior editor for this article. 2 We would like to thank Siemens for their excellent collaboration during our research. We would also like to thank the two anonymous reviewers and, especially, Senior Editor Hind Benbya for her specific advice that helped to improve this article. We would like to thank Walter Brenner for his feedback on an earlier version of this manuscript.
Document Type
Article
Disciplines
Finance
DOI
10.2139/ssrn.4928166
Source
SMU Cox: Finance (Topic)
Language
English
