In sub-Saharan Africa (especially in Nigeria, Kenya, and South Africa), AI-driven financial services and predictive policing are reshaping key sectors, and the rapid development of the technology presents both transformative opportunities and regulatory challenges. While AI fosters financial inclusion and enhances decision-making processes, concerns regarding privacy, algorithmic bias, and governance persist. As AI continues to expand across industries and borders, the question is no longer whether AI should be regulated but rather how, by whom, and to what extent. This short chapter explores the imperative of AI regulation, examining the conceptual justifications for regulatory interventions, the challenges of applying existing legal frameworks to AI, and the competing models for effective governance. Drawing on regulatory theories, including Lawrence Lessig’s “Big Four” modalities of regulation (law, norms, markets, and code), the work highlights how the unique characteristics of AI complicate traditional regulatory approaches. The chapter analyzes different regulatory models, including top-down (government-led), bottom-up (industry self-regulation), and hybrid co-regulation approaches, as well as their applicability to AI governance. It also explores sectoral versus horizontal regulatory strategies and the complexities of regulating AI within deterritorialized, transnational contexts. The African regulatory landscape is examined, highlighting resource constraints, public distrust in institutions, and the tendency of some governments to impose broad, restrictive measures rather than tailored, technology-specific policies. Ultimately, the chapter argues for a flexible yet robust regulatory framework that balances innovation with accountability. It advocates for an interdisciplinary, multi-stakeholder approach that integrates legal, communitarian, and technological considerations to ensure the responsible development and deployment of AI while maintaining fundamental rights and societal values.