ORCID

Document Type

Article

Abstract

Purpose – The rapid expansion of generative artificial intelligence (AI) is reshaping organizational processes and competitive dynamics across industries. Although scholarly interest in AI adoption is increasing, there remains a lack of research on how ethical leadership and technological sustainability affect organizational outcomes related to generative AI. This study investigates the role of virtue ethics in guiding the implementation of generative AI in HR-driven customer service contexts and examines how leadership perspectives influence the responsible and sustainable adoption of technology. Design/methodology/approach – This study draws on normative ethical theory and dynamic capability theory to develop a conceptual framework explaining how ethical leadership and organizational capabilities influence perceptions of generative AI performance. The research analyzes the mechanisms by which virtue-based ethical considerations and leadership-driven governance practices support the effective and responsible deployment of generative AI technologies. Data were collected from 335 respondents, and analysis was conducted using structural equation modelling. Findings – The study indicates that ethical leadership grounded in virtue ethics is essential for fostering responsible generative AI adoption by strengthening employee trust, enhancing internal reputation, and supporting sustainable technology integration. Additionally, dynamic organizational capabilities enable the alignment of ethical governance with technological implementation, thereby improving perceived generative AI performance in HR-supported customer service environments. Originality/value – This research advances the literature on generative AI adoption by integrating virtue ethics and dynamic capability perspectives to explain how ethical governance and leadership influence AI-enabled organizational outcomes. The study underscores the significance of strategic leadership, ethical oversight, and sustainable technology management in maximizing the value that generative AI generates within organizational contexts.

Publication Date

2026-06-17

Publication Title

Strategy and Leadership

ISSN

1087-8572

Deposit Date

2026-09-17

Keywords

Corporate reputation, Dynamic capability, Generative-AI performance, Implementation expectancy, Leadership, Strategy

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

First Page

1

Last Page

26

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