ETHICS AND GOVERNANCE IN AI MANAGEMENT

Abstract

Purpose: The publication aims to analyse ethics and governance in artificial intelligence (AI) management within organisations. It examines how ethical principles and governance mechanisms facilitate the responsible use of AI, taking into account both legal obligations and social expectations. Need for the study: The study addresses the growing significance of AI in various sectors and the challenges it presents to society, the economy, and individual rights. Methodology: An interdisciplinary approach is used, combining a literature review, legal analysis, and case studies. The study integrates legal, ethical, and technological perspectives to provide a comprehensive view of AI governance. Findings: Three governance models are examined: regulatory, self-regulatory, and hybrid. The regulatory model offers legal certainty but limited adaptability. The self-regulatory model allows innovation and flexibility but may lack consistency in ethical norms. The hybrid model, which combines both approaches, is the most effective, striking a balance between structure and flexibility, and sharing responsibility. Practical Implications: The article discusses the implementation of effective oversight mechanisms tailored to industry-specific needs and technological maturity. It emphasizes the need for a dynamic regulatory framework that adapts to technological advancements, while promoting self-regulation and private sector accountability. A balanced governance model—combining formal legal controls with voluntary industry standards—is essential for promoting safety, transparency, and ethical compliance in AI use.

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