Ethical Artificial Intelligence Governance for Organizational Sustainability
Keywords:
Artificial Intelligence, Work Ethics, Automation, AI Governance, Organizational SustainabilityAbstract
The rapid development of Artificial Intelligence (AI) and automation has significantly transformed the modern workplace by creating opportunities to improve organizational efficiency while simultaneously raising ethical challenges, including algorithmic bias, data privacy, transparency, and accountability in decision-making processes. These developments require organizations to establish AI governance frameworks that not only promote technological innovation but also uphold ethical principles and organizational sustainability. This study aims to analyze the development of research on work ethics in the era of AI and automation, identify the major ethical challenges associated with AI implementation, and formulate organizational strategies for responsible AI governance. A Systematic Literature Review (SLR) was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to examine scientific articles indexed in the Scopus database published between 2020 and 2026. The findings indicate that AI implementation has reshaped workforce competency requirements, strengthened human–AI collaboration, and generated five major ethical issues: algorithmic bias, transparency, data privacy, accountability, and job security. To address these challenges, organizations should establish ethical AI governance through clear organizational policies, continuous digital competency development, the promotion of an ethical organizational culture, and transparent monitoring mechanisms. This study proposes a conceptual synthesis integrating work ethics, ethical AI governance, and organizational sustainability, providing theoretical insights and practical recommendations for organizations implementing responsible and sustainable AI technologies.
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