Governing the Algorithm, Sustaining the Environment: How Authentic Leadership Validates Corporate Responsible AI to Foster Moral Ownership and Green Innovation

초록

The integration of artificial intelligence (AI) generates a structural tension within the twin transition, wherein the organizational pursuit of algorithmic efficiency systematically constrains the discretionary ecological dedication of employees. Grounded in uncertainty management theory (UMT), this study investigates how perceived corporate responsible artificial intelligence (CRAI) addresses this paradox by converting macroscopic ethical governance into micro-level environmental action. Utilizing a four-wave time-lagged research design with 401 employees in South Korea, we empirically tested a moderated sequential mediation model. The results demonstrate that CRAI functions as a cognitive heuristic that attenuates AI-induced job insecurity (AIJI) by providing procedural proxy control. This attenuation validates the respected status value of employees and generates active moral ownership, which subsequently drives high-cost green innovative behavior (GIB). Furthermore, the institutional ethical declaration operates as an autonomous normative signal that facilitates ecological innovation independently of the sequential psychological pathway. Finally, the systemic benefits of this macroscopic governance are structurally contingent upon the relational validation provided by authentic leadership. This research advances the organizational behavior literature by elucidating the identity-based mechanism of uncertainty reduction and establishing the structural complementarity between macro-level technological ethics and micro-level human leadership.

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