In the UK, there is perhaps no more concrete symbol of state failure than Thames Water. In the privatized British water system, Thames Water is the country’s largest supplier. It provides water to around 16 million people, in and around London. Despite this, and a literally captive market, the firm has found itself in financial difficulties and in need of rescue.

One option to do this has just vanished. Initially, KKR, the private equity group, had said that it would put £4 billion into Thames Water, and deliver a plan to turn the firm around. But this week, it pulled out of the deal.

Now another option will have to be found. The Government would prefer that Thames Water and its £20 billion debt pile become the responsibility of the firm’s creditors, who would take the company over and try to turn it around. But it is also possible that the firm could be put in a so-called special administration regime, or SAR. This would basically entail the Government, for a time, nationalizing the firm.

Thames Water is the most egregious example of the Kafkaesque mix of public and private that has arisen in so many areas of British public services and the economy as a whole. Companies were privatized. But in many instances, like rail travel and especially water, this happened in sectors where competitive markets are very difficult to achieve. So, there was strict regulation to ensure decent services and avoid price-gouging.

But these have become hard to bear financially. The result is a system where you have companies that are de jure privatized but almost quasi-state backed. Thames Water might not be run by the government. But if there is no other option, it will be. It is almost the definition of too-big-to-fail.

The costliest instance of too-big-to-fail for the British Government, of course, was its banking system. That blew up in the UK’s face almost two decades ago, during the global financial crisis. Since then, there has been little progress in finding an economic model away from firms that are nominally private, but implicitly rely on the state’s backing if things go wrong.

Trying to rationalize this mess would be a political project that the center-left Labour party, if nobody else, could actually pull off. Indeed, it would be a politically popular moral mission. Railway nationalization, and planning reform, are already tentative steps in a system that would do away with ersatz privatization, and let the actually-existing private sector do what it has to. But there is no bigger vision for this so far.

Turning the economy, and public services, around is the only thing that will save the government’s flagging popularity. Trying to be a toned down version of populist upstarts Reform UK won’t win anyone over. Neither will cutting deals with US President Donald Trump that only partially mitigate the damage in sectors that barely exist in the UK, like the exemption from new 50% steel and aluminum tariffs. As things stand, Thames Water looks set to become merely another albatross around Keir Starmer’s neck.

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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