At more than 50 years of age, Artificial Intelligence cannot be called a new technology. However, recent advances in AI have made the field widely available and applicable to the extent that it has become a major driver for technology-based innovations. This article investigates the characteristics underlying AI technology that are most relevant for innovation management. It addresses challenges and potential showstoppers such as data requirements, explainability and ethical questions. These que…
Read moreAt more than 50 years of age, Artificial Intelligence cannot be called a new technology. However, recent advances in AI have made the field widely available and applicable to the extent that it has become a major driver for technology-based innovations. This article investigates the characteristics underlying AI technology that are most relevant for innovation management. It addresses challenges and potential showstoppers such as data requirements, explainability and ethical questions. These questions require a strategic approach to managing AI innovation, i.e. a long-term perspective and a careful consideration of the epistemic flow of information from the problem domain to the application. We propose an epistemic framework for the AI innovation process that helps in understanding and improving key dynamic capabilities for strategic AI innovation management.
