Innovation management has attracted considerable attention from management scholars in all disciplines given the critical importance of innovation activities to all firms. While our knowledge of the innovation process has advanced, there is little debate that the tasks within the main stages of the process remain not only resourceintensive but also fraught with ambiguity. In the meantime, Artificial Intelligence (AI) has been rising as a powerful general-purpose technology that promises to lower uncertainty with more accurate predictions and to reduce the cost of laborious tasks. Here, we perform a critical review of the literature at the intersection of artificial intelligence and innovation management to present our thoughts on the ways AI can augment innovation managers in dealing with their tasks at each of the four stages of the process. We also present the articles in this special issue and explain their contribution to advancing our knowledge on how AI can act as an enabler for innovation.
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