Employee intention and resistance to AI policies: perceived injustice, moral outrage, and social influence from an activity theory perspective

Abstract

This study investigates employees’ responses to artificial intelligence (AI) policies through the lens of Activity Theory (AT), a framework widely used in human–computer interaction (HCI) research. Using data from 547 South Korean professionals, this study examines how perceived injustice, moral outrage, and social influence affect economic acceptance and social identification, which subsequently influence intention to use and resistance to change, providing insights into the human-centred aspects of AI implementation. Structural equation modelling reveals that perceived injustice negatively affects economic acceptance while positively influencing social identification. Moral outrage shows no significant effect on economic acceptance but positively impacts social identification. Social influence strongly predicts both outcome variables. Economic acceptance increases intention to use and decreases resistance, while social identification paradoxically increases both. Furthermore, policy trust significantly moderates these relationships. This study extends human–computer interaction and technology acceptance research by identifying contradictions within organisational activity systems that shape user responses to AI policies, providing insights for developing human-centred implementation strategies that address both economic and social dimensions of the user experience with AI technologies.

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