A tense, week-long war of words between Donald Trump and Volodymyr Zelensky seems to have reached a happy denouement with the announcement of the US-Ukraine minerals deal. The Ukrainian President is expected to travel to Washington on Friday to sign the agreement.

A reconstruction fund for the country is to be established into which Ukraine will contribute 50% of its proceeds from the “future monetization” of minerals, hydrocarbons, and associated infrastructure. While the US will have a substantial (though as yet unconfirmed) stake in the jointly-owned and -managed fund, the initial demand of a $500 billion payout has notably been dropped.

Ukrainian officials have also successfully wrangled with their American counterparts over the inclusion of a vague reference to security guarantees. Though this falls short of any specific far-reaching American commitment, Kyiv intends the deal to be a “framework” for future discussions. Giving Washington a vested economic interest in its resources is no bad place to start when dealing with a transactional administration.

The EU might be kicking itself. After all, the bloc first signed a strategic partnership with Ukraine on raw materials back in July 2021, even if this was subsequently overtaken by events. (This didn’t stop it from allegedly pitching its own “win-win” minerals proposal on Monday.) But could it be that the open goal was really Europe’s to miss?

According to a senior Labour figure, the UK was involved in extensive negotiations for the whole of last year relating to our securing exclusive access to the precious metals, but adequate Government support was not forthcoming. In the end, Azerbaijan won the auction for Ukraine’s titanium mine. Naturally, Trump’s intervention has changed the dynamics, but the UK still remains extremely interested in negotiating with both the US and Ukraine on access.

There has, however, been much confusion about what assets Ukraine actually possesses. Despite the excited clamour around the supposed “trillions” on offer, Dr Robert Muggah (co-founder of Canadian geopolitical risk firm SecDev, which undertook the original study on Ukraine’s natural resource holdings in 2022) explained to me that this should be understood as the total hypothetical assessment of all that Ukraine has. The fact is that, for all the overwhelming media focus on minerals, the majority of the country’s natural wealth comprises hydrocarbons — resources that are already being exploited and of little strategic import from a geopolitical perspective.

When taking just rare earths and critical minerals together (erroneously conflated by too many people), Muggah said: “We’re likely talking about hundreds of billions by the time we get down to the overall amount that reasonably can be extracted over the next 15 to 25 years — and that’s assuming a high volume of investment and sufficient security guarantees for mining companies.” Certainly, any notion that Ukraine has “$500 billion worth of rare earth” is, as Bloomberg’s Javier Blas put it, a completely fantastical regurgitation of “conspiracy-theory claims found on the blogosphere”, propagated by the general lack of basic geological knowledge.

Fortunately, Britain need not concern itself with these rare earths or even critical minerals like lithium (which has suffered a price crash of more than 80% since its peak in 2022). Our key focus should instead be on gaining access to the two non-negotiable elements of any contemporary industrial strategy: graphite and titanium.

With Starmer due to pay homage to the King himself today, is this a chance for us to make our case? The Prime Minister showcased his more ruthless streak in slashing aid to boost defense spending and even signalled he is “ready and willing” to put UK troops on the ground to safeguard Ukraine (and, essentially, America’s investments there).

Given all this, access to a share of both the American and Ukrainian cups is, as my source insists, a “reasonable request”. But whether our scrappy attempt at the Art of the Deal is met with respect or derision by the master deal-maker himself is anyone’s guess.

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Sang-Hwa Lee is a foreign policy researcher and lead writer at Listening to the Other Side.

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China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

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Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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