Innovation Analytics: Leveraging Artificial Intelligence in the Innovation Process

Abstract

Artificial Intelligence (AI) is about imbuing machines with a kind of intelligence that would otherwise mainly be attributable to humans. Extant literature suggests that, while AI may not yet be ready to completely take over the more creative tasks within the innovation process, our experience of using AI in the field suggests that it may be able to significantly support innovation managers nonetheless. In this article, we broadly refer to the derivation of computer-enabled, data-driven insights, models and visualizations within the innovation process as innovation analytics. We argue that AI can play a key role in the innovation process by driving multiple aspects of innovation analytics. We consider the fuzzy front end of the innovation process as a “double diamond” that spans exploration and selection of concepts in the problem and solution space, and outline the aspects of innovation analytics where AI can play an important role. We then present four different case studies of AI in action – one for each part of the innovation process – based on our previous work in the field. The cases demonstrate how AI-enabled innovation analytics can yield richer insights in a more cost effective manner. Finally, we conclude with implications for innovation managers, highlighting the benefits and limitations of using AI in innovation.