Value creation and value capture in AI offerings : A process framework on business model development

Purpose – The purpose of this study is to explore how AI providers ensure value creation and value capture dimensions when developing AI offerings. This by illustrating activities that builds the dimensions and to increase the understanding on how value creation and value capture interplay. Method – To fulfill its purpose, this study adopted an inductive exploratory single case-study approach, conducted at a market leading telecom provider of AI related services. In total, 23 interviews were held with the case company, and the results were generated by applying a three step process of thematic analysis, where the framework’s phases and its underlying activities were identified. Findings – This study’s findings are presented in a process framework, explicitly illustrating key activities for the value creation and value capture dimensions. The framework further suggests AI providers to design AI offerings by going through three phases, i.e. identifying prerequisites for value creation, connecting value creation with value capture opportunities and designing the value offering. It is also found that AI providers must develop multiple business models, and operate them simultaneously, to operationalize AI successfully. Theoretical and practical implications – This study contributes to the theoretical understanding of AI by identifying activities building the value creation and value capture dimensions. In addition, the process framework can be used by practitioners when developing or refining business model architectures for AI offerings. Limitations and future research – This study is limited by its scope, and future research is recommended to perform extended studies where both providers and its customers are included. In addition, this study’s findings highlights the importance of developing and operating multiple business model to operationalize AI successfully. However, this also induces risks of business model cannibalization, which calls for more research.