The AI Race: Why China Is Further Ahead Than You Think

TL;DR: The narrative that the US leads AI without serious competition is incomplete. China is ahead in research, patents, industrial adoption, and state investment volume. If your business strategy only watches Silicon Valley, you're leaving a multi-billion dollar market off your radar.

Why nobody talks about China in AI

When AI comes up in business conversations, 90% of the discussion revolves around OpenAI, Google, and the Silicon Valley giants. It's a collective blind spot worth examining.

There are three concrete reasons why China disappears from the radar:

1. Language barrier. Most Chinese AI research is published in Mandarin or through official state media. If you're not reading Chinese-language sources or following specialized publications, you simply don't see the progress.

2. Low transparency. The WTO recently flagged a "lack of overall transparency" in China's industrial programs. Chinese AI companies — state-owned or private — aren't required to disclose operational metrics or funding the same way their Western counterparts are.

3. Media bias. The tech media ecosystem is overwhelmingly American. AI coverage = coverage of American companies. It's a selection bias that distorts the global picture.

The result: a massive and accelerating Chinese AI ecosystem that most decision-makers in the West are systematically underestimating.

The numbers don't lie

Let's set aside speculation and look at the data. And the data is hard to ignore.

Investment and market size

Metric	China / Asia	US / Europe
Core AI market (2024)	~$126.7B (+24% YoY)	Private investment dominates (OpenAI raised $6.6B in one round)
2025 projection	Surpassing $170B	North America captures ~60% of global AI VC
Funding model	Massive state funds (60B RMB in 2025) + "AI Plus" program	Venture capital + big tech
AI companies	5,300+ enterprises	Diverse startup ecosystem, led by Silicon Valley

China isn't "trying to compete" with the West. It's already competing. And on several indicators, it's already ahead.

Research and patents: China dominates the volume

This is the point where a lot of executives would be surprised. According to Digital Science, China matched the combined AI research output of the US, UK, and EU in 2024, capturing over 40% of global citations.

On patents, the advantage is even clearer: China holds more than 60% of global AI patents, and in some categories, it outpaces the US by 10x.

~30,000 active AI researchers. That's not a startup lab. That's industrial-scale national investment.

Chinese models are closing the gap

Demis Hassabis, CEO of Google DeepMind, was blunt about it: China is "months" behind the most advanced US models.

The numbers back it up. Alibaba positioned its Qwen3-Max-Thinking model as comparable in performance to Claude Opus 4.5 and Gemini 3 Pro across 19 benchmarks. TrendForce documented these advances in February 2026.

Other names worth tracking: DeepSeek (the Chinese open-source model that shook the industry), Ernie Bot (Baidu), Doubao (ByteDance), and Kimi (Moonshot AI).

Where the West still has real advantage

Let's be straight. This isn't a game that's over in China's favor. The US maintains significant structural advantages:

Compute and chips. As RAND puts it: "Right now, compute is arguably the single biggest driver of AI progress." Control over Nvidia and GPU infrastructure remains the biggest technological moat the US has.
Total private investment. Private AI investment in the US vastly outpaces China. Silicon Valley's VC ecosystem remains the single largest accelerator for AI startups globally.
Frontier models. GPT-4, Gemini, Claude, and LLaMA still represent the cutting edge in general-purpose AI. China is closing the distance, but the distance exists.
Open ecosystem. Western academic collaboration, open-access publications, and the culture of sharing benchmarks generate a much faster iteration loop.

The real advantage isn't just in the models. It's in the infrastructure, the ecosystem, and the speed of private iteration.

Enterprise adoption: where China is surprisingly ahead

This is the point that should concern Western businesses the most — and it's barely discussed.

China: adoption at national scale

According to CPA Australia, around 72% of Chinese companies have used AI in some capacity in 2024. 48% plan to expand that usage in the coming months.

Manufacturing AI adoption went from ~19.9% in 2024 to 25.9% in 2025. China isn't "experimenting" with AI in its factories. It's already integrated into the production pipeline.

The national "AI Plus" program is pushing AI integration into healthcare, agriculture, transportation, and infrastructure — with a 2027 target for full adoption across key sectors.

The West: fragmented and lagging in many areas

The contrast is stark. In the EU, only ~13.5% of companies with 10+ employees used AI in 2024, according to OECD data. SMEs are particularly behind: the OECD median for AI adoption sits at just ~8.5%.

Nordic countries and South Korea are exceptions, surpassing 25%. But much of Europe is below 10%.

In the US, the largest tech and finance corporations are aggressively integrating AI. But there are no uniform official numbers that allow a direct comparison with China.

The enterprise adoption gap is real. The numbers prove it.

The conversation nobody wants to have: layoffs

The AI and employment discussion is where the differences between China and the West get the most interesting from a business strategy perspective.

The Chinese approach: proactive regulation

China is taking an approach that few expected. A recent labor ruling in Beijing established that companies cannot lay off employees solely because their tasks were automated. That's a clear line: AI transforms tasks, but it's not a legal justification for direct headcount elimination.

The Chinese government is promoting retraining and social protections for a planned transition. Social stability is a top priority for Beijing, and that translates into concrete policy.

The Western approach: "move fast and lay off"

The picture in the US is diametrically different. Between Q4 2025 and January 2026, approximately 245,000 layoffs hit the tech sector.

Amazon, Ford, JPMorgan, and others have openly stated they plan to cut administrative roles "because of AI." However, Harvard Business Review flagged something important: many of these layoffs are driven by AI's future potential, not its current performance.

And here's the data point that every CFO should pay attention to: according to Forrester, 55% of employers report regretting laying off workers because of AI. Half of those layoffs are expected to be "quietly rehired" — but offshore or at significantly lower salaries.

The business perspective

This isn't about who's morally right. It's about operational strategy. China is managing the transition in a way that preserves workforce stability while integrating AI. The West is running a much more volatile experiment, with uncertain outcomes and real reputational cost.

For any company planning its AI adoption strategy, both models offer valuable lessons.

Where to focus in 2026

If you're a decision-maker in tech — or any industry that depends on AI — here's where your attention should be:

Watch the Chinese models. DeepSeek, Qwen, Ernie, and their iterations aren't going anywhere. In some cases, they're already competitive. TIME's coverage on how China "caught up" is required reading.
Benchmark against the global standard, not just the Western one. If you're only comparing your AI adoption to European or American companies, you're mid-pack at best.
Treat regulation as competitive advantage. The EU AI Act is already in effect. Companies that build compliance from day one are better positioned than those who leave it for last.
Be careful with reactive layoffs. Forrester's numbers are clear: laying off on AI hype has a real cost. Build, don't just cut.
Energy is the next battleground. As Brookings points out, China has produced more energy than the US since 2010. And AI is extremely energy-intensive. This factor is going to matter more and more.

The bottom line

The AI race isn't the US versus the rest. It's a global ecosystem where China is playing a role that the West has been systematically underestimating.

China has more researchers, more patents, higher enterprise adoption, and a state investment strategy that's producing measurable results. The US has better frontier models, superior compute infrastructure, and a more dynamic private ecosystem.

Neither side has the race won. But if your AI strategy assumes the only competition comes from San Francisco, you need to recalibrate the map.

The real race isn't about who builds the best model today. It's about who deploys AI at scale, sustainably, and first.

Sources and references

Josh Crash Building scalable solutions, one commit at a time 🦅