According to reports yesterday, NHS trusts around the UK may have to make up to 100,000 job cuts in order to meet the target of slashing their “corporate cost” by 50%. Health Secretary Wes Streeting is once again swinging his reformist axe in order to boost efficiency in the service, with NHS leaders requesting that the Treasury cover the costs.

While pushes for efficiency are welcome given the bloat that weighs down the NHS and the rising deficits in hospital trusts, these job cuts are not cause for celebration. The potential scale of these redundancies points to Streeting pushing for too much too quickly, with the NHS Confederation suggesting the cuts could entail anywhere between 40,000 to 150,000 employees. The Confederation’s chief executive, Matthew Taylor, has therefore called for a redundancy fund, similar to that announced in the Spring Statement, for Civil Service and NHS England workers.

The NHS has clear inefficiency problems; but trusts are currently hemorrhaging money, leaving them financially anemic and potentially unable to cover the costs of making such redundancies. The Nuffield Trust reported in February that NHS trusts overspent by around £1.2 billion last year, twice the previous year’s total. These cuts could potentially cost almost £2 billion alone, with several trust leaders reportedly budgeting around £12 million each to cover for the redundancy payments and associated costs.

With this in mind, the call for a redundancy fund is a sensible one, given the likely short-term cost of making such drastic cuts. If the payouts are entirely put into the trusts themselves, it will leave them worse off over the next few years before any benefit can be felt.

Likewise, rather than boosting efficiency, Streeting risks leaving the NHS short-staffed in order to make the necessary reforms. As the chief executives of the King’s Fund and the Nuffield Trust pointed out yesterday in the Guardian, many of these workers are specialists in driving efficiency and keeping wards adequately staffed.

It seems that this government has not learned from the failures of the Tories, who similarly made over 10,000 redundancies over the course of their 2013 reforms. Then, thousands of those laid off were re-employed afterwards, having left the NHS short on staff able to carry out the administrative roles required. It would be counterintuitive to make these cuts — and the required redundancy payments — only to re-hire staff at great cost. Labour may have the foresight to anticipate the potential fallout, but the record of successive Tory governments is hardly a source of hope.

The NHS finds itself at a crossroads. While immediate reform is needed, Streeting can’t risk rash decision-making for the ideological change he wants, given the frailty of the service as it approaches its 80th birthday in 2028. The pressure being put on NHS trusts to meet these figures also serves as a flashback to the control-freakery of the New Labour era, which focused on target-based care at the expense of quality. NHS leaders were broadly glad to see the back of that approach; few will want to see its return under this new government.

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Dr Ammad Butt is a freelance writer and doctor working in the UK.

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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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