Companies that use it for recombination see better results than those that use it for incremental improvements and radical innovation efforts.
July 25, 2024
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Companies need new ways to innovate quickly, cheaply, and productively. Many, quite reasonably, wonder how deploying AI might help. To investigate, we researched how companies are using AI for innovation and found that tools are just tools — success depends on how organizations use these new tools now at their disposal. To investigate what kinds of innovation AI worked with, the authors performed two studies: first, a survey of 331 firms for practices on process improvement and new technology development, and second, an archival analysis of patent data on new technology development for a broader sample of more than 2,000 publicly traded firms. The results of these studies suggest that firms that have historically focused on specific types of innovation — process innovation and innovation by diverse recombination, in which companies combine a wide variety of technology elements in new ways — may benefit most from using advanced data capabilities of machine learning and AI. Firms that use AI analytics to generate wide recombinations are 3 to 7% more productive than firms that do not. Furthermore, when a firm’s existing knowledge is spread throughout the firm, advanced AI capabilities can further boost firm innovation by about three more new patents a year. Conversely, using AI is less helpful for incremental innovation and making small improvements to existing products, and is almost no help at all for radical innovation.
At some point, just about every company must deal with a hard truth: products get old. It isn’t so much that there’s a precise expiration date, after which your offerings are suddenly dated. But often, leaders have a moment when they recognize that a product line is getting long in the tooth and realize it’s time for a refresh — even if it’s still thriving and popular. With the substantial development timelines of many modern complex products, failing to innovate to counter the subtle creep of obsolescence can turn a leader into a laggard.
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Lynn Wu is an associate professor at the Wharton School. She teaches and researches use and impact of emerging technologies on business.
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Sam Ransbotham is a Professor of Business Analytics at the Boston College Carroll School of Management. He co-hosts the “Me, Myself, and AI” podcast.
