More than 30 economies backed a global AI Opportunity Declaration during the second PAX Silica Summit hosted by the U.S. [1].

This agreement signals a coordinated international effort to balance rapid technological advancement with economic sovereignty. By aligning policies across dozens of nations, the summit seeks to prevent a fragmented global AI landscape while ensuring that economic growth remains inclusive.

The summit focused on promoting responsible AI development and innovation sovereignty [5]. As part of this effort, more than 30 economies endorsed the AI Opportunity Declaration to foster international cooperation [1]. Additionally, more than 30 governments committed to implementing pro-growth AI policies to stimulate economic expansion [2].

To facilitate these goals, the U.S. announced the creation of PaxPass. This initiative is designed to streamline the movement of critical AI goods across borders, reducing bureaucratic friction for essential hardware, and software components [4].

Education and training also featured prominently in the summit's agenda. Participants announced the establishment of the Foundry School, a partnership with Stanford University intended to cultivate the next generation of AI experts and innovators [3].

To ensure the sustainability of these programs, the U.S. pledged $50 million in financial support to back the summit's initiatives [5]. This funding is intended to bridge the gap between high-level policy declarations and the practical implementation of AI infrastructure and training.

“More than 30 economies backed a global AI Opportunity Declaration”

The PAX Silica Summit represents a strategic move by the U.S. to lead the creation of a standardized global framework for AI trade and development. By combining financial incentives, educational partnerships with institutions like Stanford, and logistics solutions like PaxPass, the U.S. is attempting to secure a coalition of allies that prioritizes open, pro-growth AI policies over more restrictive or isolated national models.