Successfully Mitigating AI Management Risks to Scale AI Globally

Authors

Thomas Hutzschenreuter
Tim Lämmermann
Alexander Sake
Helmuth Ludwig

Abstract

Many firms struggle to scale today’s generative and predictive AI systems effectively because their machine learning-based working mechanisms amplify general technology management challenges and create entirely new ones. Based on an in-depth case study of industrial AI pioneer Siemens AG, we describe how to successfully mitigate five critical technology management risks to scale AI globally, and provide recommendations for creating company-wide business impacts with machine learning-based AI systems.

Recommended Citation

Hutzschenreuter, Thomas; Lämmermann, Tim; Sake, Alexander; and Ludwig, Helmuth (2025) "Successfully Mitigating AI Management Risks to Scale AI Globally," MIS Quarterly Executive: Vol. 24: Iss. 3, Article 3.
Available at: https://aisel.aisnet.org/misqe/vol24/iss3/3