The Role of Ecosystems in the Development of Generative AI

In the context of global digitalization and rapid technological progress, the study of business ecosystems and their role in the development of generative artificial intelligence (GenAI) becomes particularly relevant. Despite the significant economic potential and interest of companies in the development and implementation of GenAI, the role of business ecosystems in this process remains under-researched. The key idea of this paper is to fill the existing research gap regarding the interaction between business ecosystems and generative AI. The paper analyses how ecosystems contribute to the adoption of generative AI applications and the development of foundation models. The generative AI value chain is chosen for the study, and of its six stages, two of its stages are analysed in detail: the adoption of business applications and the development of foundation models. The first stage analysis examined 118 use cases in 111 companies across 5 industries and found that ecosystems have 3-4 times more generative AI use cases per company; moreover, among ecosystems, technology ecosystems have ~4 times more use cases than non-technology ecosystems. These results can be attributed mainly to the fundamental propensity of ecosystems to innovate and partly to the economies of scale they gain from realising use cases across industries. The second stage analysis examined 60 of the most notable foundation generative AI models and determined whether their development companies are affiliated to ecosystems. The results of the study showed that 80% of the foundation model development companies are affiliated to ecosystems, and the most common affiliation formats are partnerships and infrastructure products/services provision. The study demonstrates that business ecosystems have significant potential for generative AI development due to their organisational and technological capabilities. The paper offers practical recommendations for companies seeking to utilise the potential of generative technologies to improve their competitiveness and innovative development.