Toward a Better Understanding of AI Innovations

Autor: Yu-Kai Lin, Likoebe M. Maruping
Rok vydání: 2020
Předmět:
Zdroj: SSRN Electronic Journal.
ISSN: 1556-5068
Popis: Artificial intelligence (AI) has emerged to be a salient driver for digital innovations. However, there is very limited research into how firms should manage their AI innovations. To fill this gap, we examine the comparative radicalness and process-orientation between AI and non-AI innovations. Prior research suggests that such attributes of innovations require firms to adopt very specific organizing principles. That is, the ways in which firms approach radical innovations will differ from those used in incremental innovations, and the organizing logic for new product innovations will also depart from that for new process innovation. We conduct an inductive exploratory study using a large U.S. patent data set and a multi-method research design. Results from our analysis reveal that AI innovations are significantly less radical and more process-oriented than their similar non-AI counterparts. Theoretical and managerial implications of our findings are discussed.
Databáze: OpenAIRE