In his first major international address, Vice President JD Vance made a forceful case against stringent AI regulations at the AI Action Summit in Paris, warning that excessive oversight could stifle innovation just as AI is transitioning from research to real-world deployment. He emphasized that AI’s commercial value is no longer in experimentation but in inference—where models make real-time decisions and drive business impact.
Vance criticized the European Union’s approach, singling out the General Data Protection Regulation (GDPR) and the Digital Services Act as barriers to AI growth due to high compliance costs and what he called “ideological bias.” Beyond the regulatory burden, these policies could slow AI’s ability to execute at scale, limiting its economic impact. The challenge is no longer about building AI engines—it’s about ensuring the infrastructure exists to power them in real-world applications. AI inference, the process where models translate intelligence into action, demands purpose-built infrastructure that eliminates performance and latency bottlenecks.
Positioning the United States as the leader in AI development, Vance argued that future AI dominance will be defined by execution, not experimentation. As enterprises integrate AI into business-critical operations, the ability to execute inference at scale will be what separates industry leaders from laggards. The U.S., with its innovation-friendly policies, aims to provide a foundation where AI-first enterprises can thrive without restrictive regulatory frameworks throttling deployment. 
While advocating for international collaboration, Vance warned against AI being used as a tool for authoritarian control, a statement widely interpreted as a critique of China’s technological policies. The ability to make AI-powered decisions instantly—rather than through slow, centralized processing—is key to maintaining AI’s role as a force for innovation rather than surveillance. This is why AI infrastructure must evolve to ensure real-time, decentralized inference that aligns with democratic values and enterprise agility.
Vance’s remarks carried immediate weight—following his speech, the European Commission withdrew an AI liability directive due to a lack of consensus, and both the U.S. and U.K. declined to sign a Paris summit declaration on AI regulations. Market confidence in AI execution was evident, with Intel’s stock seeing a significant boost. As businesses look beyond AI hype and focus on practical implementation, infrastructure that eliminates bottlenecks—especially in AI data mobility and compute optimization—will be critical to unlocking AI’s full economic potential.
Vance’s speech signals a clear U.S. shift toward a lighter regulatory approach, one that prioritizes AI execution over bureaucratic red tape. The next phase of AI’s evolution will be defined not by how powerful models can become in isolation, but by how efficiently they can be deployed in real-world environments.
