Artificial intelligence is rapidly shaping decisions in business, government, and society. With this growing influence comes the urgent need for strong governance and risk management practices to ensure AI systems are trustworthy, safe, and aligned with human values. This chapter explores the foundations of AI governance, outlining the principles of accountability, transparency, fairness, and human oversight that guide responsible use. It examines key frameworks—including the NIST AI Risk Management Framework and emerging ISO standards—showing how they can help organizations manage risk across the AI lifecycle, from design and development to deployment and monitoring. The discussion highlights both the opportunities and the challenges of adopting these practices in real-world contexts, where competing pressures of innovation, regulation, and ethics often collide. Beyond frameworks, the chapter considers the ethical and societal implications of AI, including issues of bias, privacy, and trust. Case studies illustrate how organizations succeed—or fail—when governance is weak, while international perspectives reveal the growing push for harmonized rules, such as the EU AI Act. By blending principles, practices, and lessons learned, this chapter offers policymakers, practitioners, and researchers practical guidance for building AI systems that are not only effective but also worthy of public trust.