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The Politics of Global AI Governance — Global Security Review

Posted on October 13, 2026 by PG Newser

The Politics of Global AI Governance — Global Security Review– globalsecurityreview.com
News Source
EXCERPT:

 The growing gap between rapid advances in artificial intelligence (AI) and inadequate verification mechanisms has created several challenges for the technology. In this context, global AI governance has become a central topic of discussion in the tech world. However, the discourse around AI focuses primarily on how the technology will be regulated. The central problem of global AI governance is no longer whether AI should be regulated, but whether states possess the power to regulate the actors and infrastructures on which they increasingly depend.  

The international system has begun responding swiftly to evolving AI dynamics. Notably, the UN Global Digital Compact has established a framework for digital cooperation. The General Assembly has created the Independent International Scientific Panel on Artificial Intelligence, along with a Dialogue on AI Governance. In parallel, the European Union (EU) has moved towards an enforceable risk-based regulation through the AI Act. Likewise, the Council of Europe has also launched the first internationally binding treaty on AI. These initiatives are a step in the right direction. However, they lack a coherent global regime or direction, which impacts their effectiveness.  

As the latest initiatives show, the U.S. relies on targeted export controls on advanced chips, voluntary frameworks, and a pro-innovation approach that preserves U.S. dominance. China, on the other hand, favors a state-driven approach, built around controls on generative AI. The EU, by contrast, prioritizes enforceable rules for high-risk and general-purpose AI, along with strong fundamental rights protection. The emerging AI order is therefore not one model, but several operating simultaneously. This fragmentation is not accidental. It reflects competing power struggles among national interests. In such an environment, the search for a global AI governance appears misguided.  

Future AI governance is likely to mirror a hybrid model of international finance or trade regimes. Against this backdrop, private companies remain incredibly powerful, given their monopoly over data, models, computing power, and expertise, which are concentrated in a handful of private companies. This trend creates a governance paradox. Governments aim to regulate the private sector while remaining excessively dependent on it, creating a capacity challenge.  

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