Six weeks after the election, surviving Conservative MP Neil O’Brien produced his own analysis of the result, highlighting the emergence of new dynamics in British politics. Unfortunately for the Conservatives, there may not be a comforting narrative for them to rely on. O’Brien has identified that now there are few three-way marginals, but instead two distinct groups of battlegrounds: around 300 seats where the Tories face Labour, and over 80 where Lib Dems and the Conservatives face off. Brought together, as he puts it, Labour and Lib Dems are forming an anti-Tory coalition.

The diagnosis is pretty accurate. The overriding narrative of the election was that it was about getting the Tories out. The problem for the party is that if 2029 becomes about keeping them out, this coalition could hold with brutal effectiveness. That, in turn, could make the next election harder than the recent one for the Conservatives.

Recent evidence suggests that winning back power is already difficult. In 2001, the Conservatives gained just one seat back from Labour. In both 1983 and 2015, the Labour Party went backwards after its first defeat. The Tories may hope that a more volatile politics helps them flip last month’s result in one term, but that very much goes against the precedent of previous majorities.

The solidification of an anti-Conservative coalition would make things much harder for the party. At present, Labour can focus on defending seats, while the Lib Dems might hope to pick off a few of the seats where they came close this time. If voters remain motivated against the Tories, this looks like a simple task. For one thing, voting tactically is easier if you have an incumbent MP to rally behind or where someone lost narrowly last time. In somewhere like Shropshire South, for example, it would only take 2000 Labour-Lib switches to flip the seat away from the Tories.

Some of the other trends of 2024 should also worry the Tories. Turnout was down, and many on the Left backed the Greens or independent candidates. Labour won a huge majority with nearly a million fewer votes than when they lost in 2019. This was partly fueled by complacency about how the result would turn out, giving voters a sense it was ‘safe’ to go elsewhere. If these voters fear a Tory return, they might be more motivated to get to the polling station and back Labour.

Underneath all this sits a huge structural problem for the Conservatives. Their vote is now heavily skewed towards the old, making it vulnerable to a more natural form of attrition. Statistics suggest that around a million Tory voters will pass away between now and the next poll, and at present, they are not being replaced among younger cohorts. The Tories have to win back a huge amount of people who deserted them this July just to stay still.

Five years is still a long time, and making firm predictions is a foolhardy business. There is every chance that the Labour government could struggle, or some unexpected event or crisis could derail it. Yet this summer’s electoral map sets the Conservatives a real challenge.

They have to win back a swathe of seats, but they also face an electoral landscape that was crafted to boot them out of power. If that solidifies around keeping them out, the distribution of votes means that it could become stronger than it is already, making the next election more of a challenge than the last one. The 2024 election was the worst election result the Tories have ever had, but that doesn’t mean the next one can’t be worse.

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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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