The global landscape of AI governance is rapidly evolving, with diverse approaches emerging within and across jurisdictions, such as Canada’s AI and Data Act, the United States’ Executive Order on Safe, Secure, and Trustworthy Development and Use of AI, the European Union’s AI Act, OECD’s AI Principles, the International Organization for Standardization’s AI Management System standard, among countless other efforts. However, this diversity of governance efforts presents significant challenges, like fragmentation between governance efforts, conflicting technical specification requirements, or regulatory races to the top or bottom (depending on economic and political circumstances).

To address these challenges, regulatory interoperability – the alignment and compatibility of AI regulations across different jurisdictions – is crucial. Implementing regulatory interoperability could streamline compliance processes, promote global norms in technical specifications requirements, and reduce barriers to international trade and collaboration. Learning from more established sectors that have faced similar challenges could provide valuable insights into successful interoperability strategies. A comprehensive implementation roadmap for AI regulatory interoperability should involve diverse stakeholders, including governments, industry leaders, and civil society organizations and take into consideration lessons learned from established sectors regulatory interoperability efforts to ensure a balanced and effective approach to global AI governance.