AI acts as a catalyst for platform innovation, reshaping industries, and the broader ecosystem. This study delves into AI governance, balancing the need for rapid technological advancement with the necessity for stringent oversight. Our analysis presents AI governance as a complex array of regulatory strategies that address the dynamics between governmental oversight and market forces, encompassing centralized and decentralized controls, and spanning from mandatory to voluntary, rigid to flexible systems. We advocate for a governance approach that simultaneously fosters innovation and manages risk, while also addressing the challenges of collective action. The research indicates that effective AI governance requires more than just adherence to laws; it involves management structures and procedures that ensure AI evolves responsibly within a framework that is both legally sound and operationally adaptable. Moreover, the array of governance tools highlights a fundamental issue: to govern AI efficiently, one must confront the intrinsic complexities of the technology and unveil the ‘black box’ of AI decision-making processes.