Artificial intelligence and innovation management: Charting the evolving landscape

Abstract

The excitement surrounding Artificial Intelligence (AI) is palpable. It is rapidly gaining prevalence in academia, business, and personal use. In particular, the emergence of generative AI, exemplified by large language models such as ChatGPT, has been marked by substantial media attention, discourse, and hype. Like most, if not all, aspects of business, innovation processes have been impacted. However, little is known about the degree of impact or the benefits that might be gained. To cut through the hype and understand the use of AI in innovation processes in businesses today, a large-scale survey amongst innovation managers in the USA was conducted, followed by interviews. The findings indicate that the use of AI in innovation processes is high and widespread, with AI being used for more than half of the surveyed firms' innovation projects. Furthermore, AI is used more in the development stage of the innovation process than in the idea or commercialization stages, which counters much of the existing discourse, which focuses on the idea stage. We uncover interesting differences by comparing the use and impact of generative AI with that of more traditional AI. Among these is a significant difference in expected benefits in making employees’ jobs more fulfilling — managers believe generative AI is more likely to confer this benefit than traditional AI. This paper offers two valuable contributions. First, it enriches the evolving dialogue at the intersection of AI and innovation management by offering much-needed empirical evidence about practical applications. Second, it provides timely managerial implications by examining relationships between the use of AI and innovation performance and understanding the benefits that AI can confer in the innovation process.