Labour is now flirting with the idea of a wealth tax. Reports over the weekend suggest that the Cabinet is considering a windfall tax on the richest people in Britain. It is a seductive idea for the Left; one of the few ways a government can raise funds for public services without harming average workers. Yet it is proving a tricky proposition for Keir Starmer as he tries to maintain his rickety electoral coalition.

The Government’s approach to a wealth tax has lacked the enthusiasm that many Labour supporters have demanded. This is understandable. The advice from the Treasury about the levy, which charges a percentage of wealth over a certain level, will be pretty clear: it is extremely difficult to implement, and unlikely to raise much revenue. A wealth tax raises all sorts of practical issues, from questions about how business interests are valued to the risk of capital flight. In countries where it has been introduced, it has largely been confined to real estate and has raised far less money than predicted. The French version raised about £1.7 billion — barely anything in terms of government spending.

Populists on the Left are less burdened by these realities. Many are either convinced that a wealth tax can raise vast amounts of money with few ill effects; others simply don’t care. For them, the issue goes beyond fiscal practicality. It is about signaling and messaging — showing that you want to soak the rich, and that you don’t care if they take their money to other jurisdictions. The Labour Party, burdened with having to try to make this work, can’t afford to be as gung-ho.

Starmer and Chancellor Rachel Reeves are stuck with a harder reality. From a Treasury point of view, the best way to raise money is broad-based tax increases, aimed at median and higher earners. These generate the biggest sums and are easiest to implement. They are also politically very difficult. People want more spending but don’t want to pay for it themselves. Ideas like a wealth tax, which avoid this dilemma, have obvious popularity.

Labour’s challengers on the Left know this, too. As they seek to take votes away from the struggling Government, a wealth tax is an eye-catching idea that will win them attention and support. A number of Left-wing campaign groups have pushed the policy for a while. The Greens have embraced the idea, as have many Left-leaning independents. If a new Corbynite party does come together, it is likely to echo these calls. Labour’s weakness on this could open the door for a party on the Left to do what Reform UK is going to do to the Tories: namely, pressure manifesto changes, steal votes, and deprive the larger party of a majority.

Yet a wealth tax is likely to fail on its merits. When it does, tax rises will be needed elsewhere to stave off further cuts. Doing so risks taxing ordinary workers and losing the working-class vote en masse.

In the last few years of power, the Conservatives struggled to find simple solutions that would alleviate the country’s worst problems and win the trust of voters. When it comes to a prospective wealth tax, Labour faces the same problem. Even if Starmer makes concessions to the idea, it won’t solve the party’s broader issues — both fiscal and electoral.

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John Oxley is a corporate strategist and political commentator. His Substack is Joxley Writes.

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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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