European leaders are still in disarray in the wake of Donald Trump’s Ukraine interventions. Last week, the US President called Volodymyr Zelensky a dictator and excluded Ukraine from peace negotiations with Russia in Saudi Arabia. On Monday evening, the US twice sided with Russia over resolutions at the United Nations to mark the third anniversary of the war.

Responding to Trump’s comments, the UK this week announced what it claims are the largest sanctions against Russia since 2022. Yet British imports from Russia only amounted to $467 million in 2023-24, around 0.15% of Russia’s $310 billion total exports. Prime Minister Keir Starmer yesterday pledged to increase UK defense spending to 2.5% of GDP by 2027, some of which would be funded by cuts to international aid. This is still far off the 3.5% recommended earlier this month by ex-chief of the general staff Lord Dannatt, and miles off Trump’s much-touted 5% for Nato members.

At this stage, most serious analysts have concluded that sanctions on Russia have failed. They have failed to seriously damage the Russian economy, and they have certainly failed to deter Russia from military action in Ukraine or shut down its military machine. “Today’s measures will target funds going into Putin’s war chest and propping up Russia’s kleptocratic system,” the press release accompanying the sanctions states. Increasingly, the rhetoric in these statements resembles less policy language and more propaganda.

But what can the UK actually do? Starmer has this month floated the idea of deploying the British military to Ukraine. But it has quickly become clear that the country does not have the military capacity to intervene in any concerted manner. Some have suggested that Europe alone might be able to prop up Ukraine now that America is following its own path, but even with the major European powers involved there are unlikely to be sufficient troops. Poland, which has a standing army that could conceivably support Ukraine at least for a few more months, has explicitly stated that it will not be sending its troops.

The reality is that Starmer and his European friends’ project in Ukraine has run out of road. The British Government is therefore reduced to announcing inconsequential sanctions packages accompanied by increasingly shrill messaging. It now appears that the conflict has cost these countries the security guarantees from the United States, under the Nato umbrella, that they have jealously guarded for so long.

European leaders are now horrified that the United States would pivot so quickly in its international alliances. But this is often what happens when a war is lost, and it is becoming increasingly clear that the main loser of the Ukraine war, apart from Ukraine itself, is Europe.

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Philip Pilkington is a macroeconomist and investment professional, and the author of The Reformation in Economics

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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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