Unpacking generative AI adoption in the workplace: the roles of algorithmic ethics and intellectual humility

Abstract

Purpose As organizations increasingly integrate generative artificial intelligence (AI) into workplace processes, understanding the factors influencing its adoption is important for effective information systems management. This study aims to investigate how algorithmic ethics influences the perceived information quality of generative AI, ultimately driving its adoption in work environments. Additionally, it examines how intellectual humility moderates in this process. Design/methodology/approach A mixed-methods approach was employed, combining a 2-wave survey of 438 generative AI users with in-depth interviews of 30 employees using AI tools for work-related tasks. Findings The two-wave survey findings indicate that perceived explainability and fairness at Time 1 are positively associated with perceived information quality at Time 2, whereas perceived transparency and accountability do not exhibit a direct effect. Perceived information quality, in turn, is positively related to AI use for work-related tasks at Time 2. Additionally, intellectual humility negatively moderates the relationship between perceived accountability and information quality. The interviews further contextualize these findings, offering nuanced explanations for the observed patterns. Originality/value This study contributes to information management research by advancing knowledge on the role of algorithmic ethics in AI-driven decision-making and offering managerial implications for organizations seeking to enhance the responsible use of generative AI in workplace environments.

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