The Captive Market You Created

Sanctions were supposed to kneecap China’s tech ambitions. Instead, they’ve become the most effective market development program Beijing never had to pay for. When the US restricted access to American AI models and semiconductor technology, it didn’t eliminate demand, it simply guaranteed that demand would flow to the only viable alternative.

The pattern is brutally consistent across sanctioned nations. Belarus, Cuba, and Russia had no choice but to pivot. But the UAE and Singapore are different animals entirely. These aren’t pariah states scraping by, they’re wealthy, technologically sophisticated economies actively choosing Chinese models over American ones. Microsoft attributes this to heavy Chinese state subsidies undercutting US pricing, but that’s only half the story.

The “Good Enough” Revolution That’s Actually Great

The conventional wisdom in Silicon Valley holds that Chinese models are cheaper imitations, functional but inferior. The data tells a different story. One developer with a paid Gemini Pro subscription admitted using DeepSeek daily, citing it as their preferred tool despite having access to what many consider the current gold standard. This isn’t a compromise, it’s a preference.

Chinese developers have embraced what one observer called the “less compute power for 80% of the benefit” approach. It’s pragmatic engineering that prioritizes accessibility over bleeding-edge performance. Open weights plus low cost creates a powerful network effect: more developers build on the platform, more tools emerge, and suddenly the “good enough” model becomes the ecosystem standard.

The irony? American AI companies are repeating the same mistake that nearly cost Microsoft the global operating system market in the 1990s. Back then, Redmond tacitly allowed pirated Windows to spread worldwide, creating a dependency that later converted to legitimate revenue. China watched that playbook and improved it, intentionally subsidizing AI model deployment to capture entire national markets, with no plans to ever flip the monetization switch back on.

The Subsidy Engine and the Scale Game

Make no mistake: this is state-directed industrial warfare, just not the kind Washington expected. Chinese subsidies aren’t simply making models cheaper, they’re making them ubiquitous. When a government absorbs the compute costs and distributes models as public infrastructure, it removes the entire procurement decision from corporate IT departments and hands it to policymakers.

The implications ripple outward. Zhipu, one of China’s “AI tigers”, just went public in Hong Kong after raising $558 million. It’s explicitly backed by Beijing and positioned as a direct competitor to OpenAI. This isn’t a scrappy startup, it’s a national champion executing a geopolitical strategy.

Meanwhile, Chinese LLMs are finding their way into global consumer products. AISpeech’s technology powers robotic sweepers from Dreame and multilingual systems for Haier and Hisense, brands that have already broken the monopoly of Western audio-visual equipment. The AI is following the same path: embedded, invisible, and impossible to dislodge once it becomes the default.

The Counterargument That Misses the Point

The knee-jerk response from US policymakers is predictable: Should we really be subsidizing AI for the entire world? It’s a fair question with a dangerously naive premise.

This isn’t about charity. It’s about who writes the rules of the road. When Chinese models become the foundation for a country’s digital infrastructure, that nation inherits Chinese data governance norms, Chinese censorship capabilities, and Chinese technical standards. The AI doesn’t just process text, it exports an entire political and technological framework.

More immediately, losing the global developer market means ceding the future. The developers building on DeepSeek today are tomorrow’s startup founders, enterprise architects, and technology ministers. They’ll hire from ecosystems they know, purchase tools that integrate with their stack, and write regulations that favor their incumbent platforms.

The argument that American companies can’t compete on price because they’re already operating at a loss misses the strategic calculus entirely. China is playing a longer game: absorb losses now to own the market later. It’s the same playbook that conquered solar panel manufacturing, electric vehicle production, and 5G infrastructure.

When 80% Becomes 100%

The most dangerous moment for US AI leadership hasn’t arrived yet, but it’s visible on the horizon. Chinese models currently compete on cost and accessibility while trailing slightly on raw capability. But China’s grid development is accelerating at a pace the US and Europe can’t match. Once they can “throw much more power at the problem”, that performance gap will narrow or vanish.

We’re watching the classic technology disruption pattern in real time: the incumbent (US AI) focuses on high-margin enterprise customers and premium performance, while the disruptor (Chinese AI) captures the mass market with “good enough” solutions. By the time the incumbent notices the threat, the disruptor has achieved scale, improved quality, and locked in network effects.

The numbers from Singapore and UAE prove this isn’t limited to poor nations making desperate choices. It’s rational actors selecting superior value propositions. When a model costs 90% less, runs on local infrastructure, and delivers results that satisfy 95% of use cases, the question isn’t why adopt it, the question is why wouldn’t you?

The Fragmentation No One Wanted

The tragedy is that this fragmentation serves no one’s long-term interests. A bifurcated AI world, American models in the West, Chinese models everywhere else, creates incompatible systems, duplicated effort, and a race to the bottom on safety standards. It makes global scientific collaboration harder and turns AI into another theater of Cold War-style competition.

But intentions don’t matter, outcomes do. Every additional percentage point of market share that flows to Chinese models makes reunification more difficult. The developers who master DeepSeek’s quirks today won’t spontaneously switch to GPT-5 tomorrow, no matter how impressive the benchmarks. They’ll have codebases, documentation, training materials, and institutional knowledge tied to the Chinese ecosystem.

What Happens Next

The US faces an uncomfortable choice. It can continue down the current path, restricting exports, maintaining premium pricing, and watching Chinese models colonize the global south and beyond. Or it can compete aggressively on accessibility, potentially sacrificing short-term margins for long-term strategic position.

Neither option is attractive, but only one acknowledges reality. The sanctions regime that was supposed to contain China’s AI development has instead created the perfect conditions for its global expansion. Washington cut off the world from American AI, Beijing offered them an alternative. The market responded exactly as economics would predict.

The question isn’t whether Chinese models are good enough. The question is whether America is willing to fight for a market it seems increasingly content to surrender, one subsidized model at a time.