Value alignment in artificial intelligence (AI) involves designing, developing, and governing AI systems that are aligned with human values while avoiding harmful or unintended consequences. This chapter explores the theoretical foundations, historical development, and contemporary approaches to AI value alignment, highlighting the interplay between design, technical, and regulatory perspectives. It provides an overview of established value theories and frameworks and highlights the connection with contemporary guidelines for responsible AI. It also examines technical (how to inscribe values in AI) and normative (what values to inscribe in AI) challenges, related to the inherent diversity of values across cultures and stakeholders, the difficulty of operationalizing abstract values into concrete AI behaviors, and the limitations of existing alignment techniques. The chapter provides an overview of implementation approaches falling under three overarching categories: design-based, technical, and regulatory. The chapter concludes with insights into current trends and research opportunities, emphasizing the need for continuous refinement of alignment methodologies. This requires interdisciplinary collaboration between researchers, industry practitioners, and policymakers to design and develop effective, innovative, and value-aligned AI systems.