For our Global AI Watch post today, we’re highlighting a compelling new article from OECD.AI, written by Charles Martinet and Yohann Ralle that challenges the notion that countries must choose between dependence on US- or China-led AI systems, or fall behind entirely.

“Conventional wisdom presents mid-sized economies with two options for accessing advanced AI: rely on American or Chinese systems, or fall behind. Neither choice preserves the technological sovereignty that countries increasingly see as essential. But there is a third path we explore in detail in a recent memo.”

The authors argue that this “dependency dilemma” is neither inevitable nor sustainable—and that collective action offers a credible alternative:

“Collectively, nations outside the US–China duopoly possess substantial computing infrastructure, a majority of the world’s top researchers, and the growing political will to create a third path. The question is whether they can come together to make it work.”

The piece emphasizes that multinational cooperation does not require sacrificing control over data or national priorities:

“With federated learning, the data never leaves national boundaries. This architecture enables pooling compute capacity and developing shared AI capabilities without centralising sensitive information.”

Read more on the OECD blog.