Abstract
Manufacturers often encounter challenges when implementing artificial intelligence (AI) in their manufacturing operations. Similar challenges with other digital transformation technologies have resulted in the emergence of innovation ecosystems. In this paper, we aim to demonstrate the emergence of AI innovation ecosystems and highlight the factors that influence their structure in manufacturing. To achieve this, we conducted a qualitative study of ten manufacturing case studies, analyzing different value propositions, activities, actors, and modules in AI ecosystems in the manufacturing sector. We first visualize the AI innovation ecosystems to showcase their structure and then discuss factors such as trustworthiness, scalability, simulation, and cloud that impact the ecosystem structure. Our study provides practitioners with a better understanding of the structure of AI ecosystems and their influencing factors. For researchers, we introduce influencing factors as a new part of the ecosystem-as-structure concept, which can lead to new research opportunities.
Recommended Citation
Scepanski, Erik; Schoemer, Daniel; Zillner, Sonja; and Laumer, Sven, "Navigating AI innovation ecosystems in manufacturing: Shaping factors and their implications" (2023). ACIS 2023 Proceedings. 54.
https://aisel.aisnet.org/acis2023/54