The future of artificial intelligence (AI) is increasingly dominated by the **United States** and **China**, which together employ 70 percent of the world’s top machine learning researchers and command 90 percent of global computing power. This concentrated power allows them to attract the vast majority of AI investment—more than twice that of all other countries combined. Unlike past technological revolutions, nations that are not at the forefront of AI may find it far more difficult to catch up, potentially relegating many countries to a state of technological dependency.
This dependency poses significant challenges for what are often termed “AI middle powers,” including **France**, **India**, and the **United Kingdom**. These countries possess considerable resources but lack the scale, capital, and computing power to develop their own leading AI systems. Their reliance on Washington and Beijing for access to advanced AI technologies leaves them vulnerable to both the disruptive effects of AI, such as job displacement and increased cybercrime, and the strategic whims of these superpowers. They also find themselves ill-equipped to shape AI’s development or manage its consequences effectively.
To navigate this precarious landscape, middle powers must explore various strategies to maintain access to frontier AI capabilities while determining their own roles in an AI-driven world. Some may choose to align closely with either the United States or China, while others might attempt to leverage both to extract concessions. Additionally, a few may pursue an ambitious agenda aimed at achieving technological sovereignty. However, all these strategies will ultimately require a keen understanding of the changing dynamics of global AI.
Access and Infrastructure Challenges
Currently, most middle powers engage with AI through commercial products from foreign companies, a reliance that can be precarious. Unlike traditional goods, AI capabilities cannot be stockpiled; access requires constant connection to infrastructure controlled by a select few firms, primarily in the U.S. This could shift as China develops its own capabilities, but significant hurdles remain. AI capabilities demand increasing computational power, making it difficult for less-resourced nations to catch up.
Should either the United States or China decide to cut off a middle power’s access to AI systems, the immediate consequences might be limited, as many critical services do not yet depend on advanced AI. However, as AI becomes more integrated into essential services, the stakes will undoubtedly rise. The U.S. and China have previously used dependency as a leverage point in other contexts, and there is little reason to believe that they will refrain from doing so in the realm of AI.
Some middle powers are trying to mitigate these vulnerabilities by developing data centers capable of running foreign AI models domestically. Projects in the **European Union**, **South Korea**, and the **United Kingdom** aim to create sovereign computing resources. However, such endeavors are costly and may not be economically feasible for all nations. Even if successful, these data centers face the ongoing challenge of keeping pace with rapidly evolving AI models, which require regular updates and maintenance tied to U.S. supply chains.
Efforts to establish sovereignty over AI models themselves are also fraught with challenges. Countries like France and Canada are investing in local AI initiatives, yet these efforts have not yet matched the capabilities of their U.S. and Chinese counterparts. As long as these disparities exist, national security agencies and businesses are likely to continue favoring superior offerings from the leading powers.
Despite these hurdles, middle powers are not fated to remain in the periphery. By securing access to frontier AI capabilities and identifying strategic economic niches, they can carve out roles that ensure their relevance in this new landscape. Potential niches include upstream inputs like semiconductor manufacturing and advanced training data, as well as downstream applications in robotics and manufacturing.
However, middle powers will need to guard against the risk of selling off their strategic assets too hastily. For instance, controlling valuable training data could provide leverage if managed prudently, while the loss of such assets would diminish their future negotiating power. Many middle powers, such as **Germany** and **India**, stand to benefit from focusing on sectors where they excel, such as advanced manufacturing and pharmaceutical research.
As the global AI landscape evolves, the United States has a vested interest in shaping how middle powers position themselves. By promoting bilateral trade and export agreements, the U.S. could help these countries align their technological ambitions with its strategic interests. However, this will require the U.S. to offer terms that do not exploit these nations’ vulnerabilities. If successful, a cooperative approach could foster a beneficial division of labor, allowing middle powers to contribute valuable capabilities while also ensuring access to advanced AI systems.
Ultimately, the future of AI will hinge on the ability of middle powers to navigate a complex web of dependencies and opportunities. If they can effectively leverage their unique positions, they may not only avoid being left behind but also play a critical role in shaping a more balanced global AI landscape.
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