Another dip in the stock market today has fuelled fears that the US is entering bear market territory. As the deadline for Trump’s new wave of tariffs draws closer, the Nasdaq index, the home of American technology stocks and the Magnificent 7, has dropped 16 percentage points since Christmas — four points from what is officially classified as a bear market. No wonder, then, that investors are moving their money into safe haven assets like gold, which has risen to about $3,120 an ounce.

Although Trump’s looming tariffs have no doubt contributed to this decline, the rot in Western markets runs much deeper. Many of the major companies on the Nasdaq have their own problems that are not related to tariffs. Tesla, for example, has been missing its revenue targets for months due to stiff competition from Chinese EV manufacturers. Nvidia, meanwhile, is still reeling from the release of DeepSeek’s latest AI model earlier this month.

The Trump tariffs have given an overarching narrative to explain these unrelated issues, which has fuelled a sense of pessimism that typically precedes a general bear market. The tariffs certainly correlate with the general downturn, but they are logically distinct from the dynamics that are actually driving poor future earnings at some of the Magnificent 7 companies.

Over in Europe, the picture is more mixed. While it is true that European markets are outperforming America, that does not mean that the continent has suddenly regained its international competitiveness. Rather, investors are betting that the plans for enormous borrowing being floated by various European leaders to militarise the continent’s economy will provide a short-term boost. Longer term, the picture for Europe is arguably worse than America’s. Concerns over European deficit spending have contributed to inflation worries, and bond market movements suggest mixed expectations on future interest rates.

The tariffs themselves, however, are largely a distraction. Trump is using them to put political pressure on allies and adversaries alike. It is by no means clear that he will even implement them. If he does, the tariffs will likely be offset by the relative movement of exchange rates.

The Trump administration has tried to play down the financial turmoil in the markets, but officials fail to understand how fragile the American economy is right now. Thanks to Joe Biden’s Inflation Reduction Act and the energy sanctions on Russia, the US economy is in a dire state. Take the example of mortgage delinquencies. With 6.1 million Americans now behind on their mortgages, this figure is could end up approaching levels not seen since the 2008 financial crisis. If the turmoil in the stock and bonds market spreads to the market for mortgage credit, there is every chance that the United States could see the bursting of a property bubble.

These are highly uncertain times, and as far as one looks into the future, all that can be seen is troubled water ahead. We do not know exactly what will happen next. But if stock markets continue to decline and the fear in these markets spreads to the bond market, there will be a rise in interest rates. Only then will we know if a recession is on the cards and, at worst, a borrowing crisis for the US government.

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Philip Pilkington is a macroeconomist and investment professional, and the author of The Reformation in Economics

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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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