s artificial intelligence adoption continues to accelerate, AI governance at the global level has largely stalled. Years of multilateral negotiations and discussions have produced high–level principles but little agreement on enforceable rules. This trend was again evident at the recent AI Impact Summit hosted by India, which produced more voluntary, nonbinding commitments. Meanwhile, the gap continues to widen between rapid AI deployment and credible governance approaches.
For many emerging economies, uncertainty—not lack of ambition—is a central challenge. Governments and local firms face complex questions about where AI value will accrue, which investments to prioritize, and how regulation will advance—not obstruct—these goals. Moreover, national AI action plans highlight that governance at the AI ecosystem level includes a considerable array of opportunities, risks, and tradeoffs before even considering AI–specific regulations. Infrastructure, investment, data access, capacity, skills, and market conditions shape the true reality of governance on the ground.
Could regional approaches to AI governance be more conducive to competitiveness than either global multilateral frameworks or fragmented country–specific policy? Likely so. Regional bodies such as the Association of Southeast Asian Nations already appear to be better equipped at building trust, reducing regulatory uncertainty, lowering compliance costs, and aligning market incentives.
Regional AI governance can also be more easily shaped to largely focus on market creation and less on constraints. Backstopped by trade and investment councils, local businesses and their associations are well positioned to support high–level government strategy because they understand regional market dynamics, trade inefficiencies, and where to find win–win investments and partnerships. By creating larger and more predictable regulatory spaces, regional governance can advance interoperable rules and incentivize innovation tailored to regional consumers, languages, labor markets, and digital maturity.
For emerging market governments and small and medium-sized enterprises, such governance translates into clearer signals about opportunities and reduces uncertainty around strategic investment. Aligning AI governance at the regional level reflects the economic reality that AI innovation requires cooperation—the question is, with whom? Done well, regional AI governance can turn regulation from a barrier into a market enabler, giving resource–strapped governments and businesses a chance to attract investment and compete on fairer terms among their neighbors.
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A case for regional AI governance: Won’t you be my neighbor?
Photo by Catarina Kåsa via Pexels.
April 2, 2026
Regional AI governance can hurdle global gridlock, helping emerging economies align rules, reduce risk, and unlock innovation, writes Louisa Tomar.
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s artificial intelligence adoption continues to accelerate, AI governance at the global level has largely stalled. Years of multilateral negotiations and discussions have produced high–level principles but little agreement on enforceable rules. This trend was again evident at the recent AI Impact Summit hosted by India, which produced more voluntary, nonbinding commitments. Meanwhile, the gap continues to widen between rapid AI deployment and credible governance approaches.
For many emerging economies, uncertainty—not lack of ambition—is a central challenge. Governments and local firms face complex questions about where AI value will accrue, which investments to prioritize, and how regulation will advance—not obstruct—these goals. Moreover, national AI action plans highlight that governance at the AI ecosystem level includes a considerable array of opportunities, risks, and tradeoffs before even considering AI–specific regulations. Infrastructure, investment, data access, capacity, skills, and market conditions shape the true reality of governance on the ground.
Could regional approaches to AI governance be more conducive to competitiveness than either global multilateral frameworks or fragmented country–specific policy? Likely so. Regional bodies such as the Association of Southeast Asian Nations already appear to be better equipped at building trust, reducing regulatory uncertainty, lowering compliance costs, and aligning market incentives.
Regional AI governance can also be more easily shaped to largely focus on market creation and less on constraints. Backstopped by trade and investment councils, local businesses and their associations are well positioned to support high–level government strategy because they understand regional market dynamics, trade inefficiencies, and where to find win–win investments and partnerships. By creating larger and more predictable regulatory spaces, regional governance can advance interoperable rules and incentivize innovation tailored to regional consumers, languages, labor markets, and digital maturity.
For emerging market governments and small and medium-sized enterprises, such governance translates into clearer signals about opportunities and reduces uncertainty around strategic investment. Aligning AI governance at the regional level reflects the economic reality that AI innovation requires cooperation—the question is, with whom? Done well, regional AI governance can turn regulation from a barrier into a market enabler, giving resource–strapped governments and businesses a chance to attract investment and compete on fairer terms among their neighbors.
