The first proper Shadow Cabinet assembled by a Tory leader in a decade and a half looks to be driven more by continuity than renewal. Early announcements have shown Kemi Badenoch handing the major positions to her vanquished rivals. So far, three of the five candidates who stood against her have been handed jobs, while James Cleverley ruled himself out. Plugging the Shadow Cabinet with influential members of the last few governments is a good way of securing Badenoch’s position, but perhaps avoids confronting some of the bigger issues in the party.

Mel Stride, the surprise entrant into the leadership race, has been made Shadow Chancellor, pointing to a continuation of Sunak-era economic policy. Putting runner-up Robert Jenrick into the Justice role suggests an endorsement of his attacks on Keir Starmer, with more attention focused on “two-tier” allegations and the release of prisoners. More controversial, however, might be the return of Priti Patel, who oversaw the significant rise in immigration which many Tory voters (and insiders) blame for the catastrophic scale of defeat.

For a shadow leader, there is little that can go right and a lot that can go wrong. Now there will be few set pieces to make a mark against the Government until the spring, when another Budget and the local elections loom. With the drama of a leadership contest gone, the Tory Party will start to feel just how far from power it now is and may start to get tetchy. This could be compounded in the spring by a poor performance in local elections, which Reform UK appears to be targeting hard.

Badenoch’s political survival relies on calming these jitters. She needs her backbenchers pulling together, and her potential rivals placated. A vanquished rival who already has a network in place can be dangerous if they feel slighted. Jenrick, who mounted an effective campaign to win, has everything in place to do so again, while someone on the Left of the party may see another opportunity if Badenoch falters.

It feels highly unlikely that this will be the shadow team that fights the next election or tries to form a government after it. Over the next few years, a new vanguard of Tory talent will start to emerge — figures such as Claire Coutinho who apprenticed under Sunak, or some of the 2024 intake with political pedigree such as former Spad Katie Lam. The junior figures in the shadow operation may soon come to be more important than those who occupy the top jobs now. The question will remain, though, whether that will be too late for the party to get itself into shape for the next election.

The political imperatives around simply surviving to the next election will have steered the Shadow Cabinet picks. That’s understandable — the Tory impulse for regicide can’t be overstated. For a party that needs a deep consideration of where it went wrong, however, picking from the old guard might just be embedding the same mistakes. These early appointments feel like a holding pattern, not a deep renewal. For a party which needs fresh ideas and energy to have a hope of winning back power, that may be a mistake.

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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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