The New York Times’s jeremiad last week about AI’s impact on entry-level jobs — particularly in tech — merely underscores trends that have been clear for well over a year. Silicon Valley firms have been slashing jobs despite record profits, and since 2022 California has actually shed positions in the information sector. An astonishing 82% of millennials fear AI will drive down their compensation. They have every reason to be concerned.

This trend could create a political storm of massive proportions. In recent decades the Democratic Party has been able to compensate for its ebbing support among blue-collar workers by winning over college-trained professionals. Almost all college-educated professionals — excluding those in the military and airline pilots — lean overwhelmingly Democratic. College degrees, particularly graduate ones, are among the strongest indicators of a Leftist tilt, yet are becoming ever less salient in terms of garnering higher salaries.

This base is under increased assault, as universities are forced to confront declining enrolments and ever less public approval. At the same time, the supply of entry-level graduate jobs at major firms such as Salesforce, Meta, Amazon and Lyft are dwindling due to the introduction of AI. Google, most notably, has recently laid off 12,000 workers — a number that is expected to grow to 30,000.

The damage may be even greater at the grassroots level. Within months of AI’s emergence, freelance work in software declined markedly, along with pay. In a survey earlier this month, two-thirds of business leaders suggested that ChatGPT will lead to large layoffs of white-collar workers over the next five years. Already, new AI programmes are allowing software firms to do without lower-level programmers, particularly new hires.

To be sure, Americans without college degrees are not immune to the effects of AI. But in the near term, it’s college professors, administrators, lawyers, accountants, and psychologists — largely Democratic-leaning professionals — who are increasingly in the crosshairs. Even Hollywood, a traditional Democratic stronghold, faces mounting threats: as entertainment becomes more digitised, layoffs have accelerated, and studios find it far easier to shift production to lower-cost regions such as Eastern Europe.

Who wins here? It will be those professions that use AI to build things, such as drones, spaceships and robots. These firms are not as heavily concentrated in places like Silicon Valley, which has largely embraced software, social media and consumer services, leaving its once proud industrial heritage behind.

This is a huge opportunity for Texas in particular, since the state has always been oriented towards tangible engineering. Texas may have missed the social media boom, but its industrial legacy has left it well placed to dominate the “deep tech” builder space. This field often requires reliable and affordable energy — something not easy to get in states such as California or New York.

Beyond elite AI engineers, the other likely winners may be those in physical, hands-on jobs — mechanics or oil rig workers — that are much harder to automate. AI pioneer Rony Abovitz told me that the big winner in the coming years will be the “sophisticated, technically capable blue-collar worker”. Young people might be better off ignoring Joe Biden’s famous advice to “learn to code” and instead consider trade schools which teach practical, in-demand skills.

So, what can the Democrats do? For one thing, they might embrace a new welfarism designed to prop up the once-ascendant educated classes. Already, talk of a guaranteed income has gained support from oligarchs including Mark Zuckerberg, Elon Musk, former Uber boss Travis Kalanick, and AI guru Sam Altman. The old meme of the welfare mom could be replaced by the demand to sustain the unemployed coder, screenwriter, paralegal or accountant.

If Democrats choose this path, they risk entrenching a new kind of dependency — one rooted not in poverty, but in the disillusionment of a class stripped of its economic purpose.

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Joel Kotkin is a Presidential Fellow in Urban Futures at Chapman University and a Senior Research Fellow at the Civitas Institute, the University of Texas at Austin.

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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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