Toward a Better Understanding of AI Innovations

22 Pages Posted: 18 Nov 2020

See all articles by Yu-Kai Lin

Yu-Kai Lin

Georgia State University - J. Mack Robinson College of Business

Likoebe M. Maruping

Georgia State University

Date Written: October 1, 2020

Abstract

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.

Keywords: artificial intelligence, radicalness, process-orientation, patents, multi-method design

Suggested Citation

Lin, Yu-Kai and Maruping, Likoebe M., Toward a Better Understanding of AI Innovations (October 1, 2020). Available at SSRN: https://ssrn.com/abstract=3703021 or http://dx.doi.org/10.2139/ssrn.3703021

Yu-Kai Lin (Contact Author)

Georgia State University - J. Mack Robinson College of Business ( email )

P.O. Box 4050
Atlanta, GA 30303-3083
United States

HOME PAGE: http://robinson.gsu.edu/profile/yu-kai-lin/

Likoebe M. Maruping

Georgia State University ( email )

35 Broad Street
Atlanta, GA 30303-3083
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
13
Abstract Views
70
PlumX Metrics