Paper Number

2863

Paper Type

Complete

Abstract

Artificial intelligence (AI) technology is considered one of the most promising and widely used in numerous organizations. However, existing literature lacks knowledge about how AI will affect corporate innovation, especially the dark side and paradoxes of AI. Drawing on knowledge management theory, this study theorizes the “double-edged sword” effect of AI adoption on innovation and the contingent roles of top management team digital technology background (TMTdtb) and big data policy (BDP). Using data of Chinese listed companies from 2007 to 2022, we find that AI adoption has an inverted U-shaped effect on innovation performance. Both TMTdtb and BDP can flatten such an inverted U-shaped relationship. Our findings contribute to the debate on the AI-innovation relationship and respond to the initiatives to explore the dark side of AI. Meanwhile, the discoveries provide practical insights for managers and policymakers on how to avoid the negative effects of AI on innovation.

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Dec 15th, 12:00 AM

Artificial Intelligence Adoption and Innovation Performance: Curvilinear Impacts and Contingencies

Artificial intelligence (AI) technology is considered one of the most promising and widely used in numerous organizations. However, existing literature lacks knowledge about how AI will affect corporate innovation, especially the dark side and paradoxes of AI. Drawing on knowledge management theory, this study theorizes the “double-edged sword” effect of AI adoption on innovation and the contingent roles of top management team digital technology background (TMTdtb) and big data policy (BDP). Using data of Chinese listed companies from 2007 to 2022, we find that AI adoption has an inverted U-shaped effect on innovation performance. Both TMTdtb and BDP can flatten such an inverted U-shaped relationship. Our findings contribute to the debate on the AI-innovation relationship and respond to the initiatives to explore the dark side of AI. Meanwhile, the discoveries provide practical insights for managers and policymakers on how to avoid the negative effects of AI on innovation.

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