AI Arms Race: USA vs. China – Where Does the Mittelstand Stand?

Marktanalyse · 7. März 2026 · Manuel Krapf

The global AI arms race dominates headlines. But what does the battle between the USA and China mean for your company? An analysis for the Mittelstand.

Last week, I was sitting with a mechanical engineering company in East Westphalia. A traditional company, a global market leader in its niche, proud engineers. The managing director, a man who spends more time on the factory floor than in a leather armchair, slid a tablet PC across the table to me. On it: a news page showing brightly colored bar charts. Hundreds of billions of dollars. USA. China. Artificial Intelligence. He looked at me and asked with that wonderfully dry Westphalian manner: "Mr. Müller, is this just noise for the big players overseas, or do I need to worry that a Chinese robot will soon take away my sales?"

A damn good question. Because while Nvidia CEO Jensen Huang dismisses talk of AI's dangers as "illogical" and champagne corks pop in Silicon Valley, here in Germany, there's a mix of fascination and sheer panic. The sums are indeed astronomical: the USA alone is pumping over 100 billion dollars in private capital into AI in 2024, and the state has pledged almost half a trillion dollars since 2013. China counters with state-orchestrated programs and investments that make Europe's efforts look like a confirmand's pocket money. And us? We in Europe, especially the German Mittelstand, are asking ourselves: Are we just spectators in this tech space race – as the experts at Lombard Odier call it – or can we somehow play along? Honestly: the cart is being put before the horse here. Everyone talks about the technology, but no one talks about what it means for the business model of a Hidden Champion in Baden-Württemberg. Time to change that.

The Criteria: What We Really Need to Measure AI Superpowers Against

Before we dive into the numbers, let's pause for a moment. Judging a competition solely by the amount of money involved is too simplistic. It's like judging the quality of a wine only by its price tag. To understand what this global conflict means for a manufacturing company in the DACH region, we need to dig deeper. I propose we evaluate the three contenders – USA, China, and Europe – based on criteria that are relevant to practical application.

My evaluation criteria for the global AI arms race:

• Capital & Financial Strength: Who has the money – and who is spending it? We look at private venture capital and government funding.
• Strategic Focus: Is it about the next social media app or automating a production line? The application focus is crucial.
• Speed & Scalability: Who is fast in implementation and can broadly disseminate innovations?
• Talent & Research: Where are the brightest minds and where do the fundamental ideas originate?
• Regulatory Environment & Ecosystem: Is the state a hindrance or an enabler? And is there a network that smaller companies can also benefit from?
• Relevance for the Mittelstand: This is the crucial question. What of all this ultimately reaches a medium-sized supplier in practice?

Candidate 1: USA – The Cowboy with Deep Pockets

One must grudgingly admit: when it comes to spending money, no one can beat the Americans. A whopping 109 billion dollars in private AI investments in 2024 alone. That's a figure you have to let sink in. Added to that are cumulative government pledges of 471 billion dollars since 2013. This is not a drizzle; it's a hurricane of capital. This money primarily flows into the development of so-called Frontier Models – the very large, fundamental AI models from Google, OpenAI, Anthropic, and co. It's a gold rush, driven by the hope of the next technological Big Bang that will revolutionize entire industries.

The strength of the USA is this unbridled, almost reckless dynamism of the free market. There's no hesitation here; investments are made. The result is technological leadership in the basic models that dominate headlines today. The focus is clearly on software, on generative AI, and of course – one must not forget – on semiconductors and national security. The thing is: this leadership comes at a price. The development of these models is absurdly expensive and energy-intensive. It's a game for billionaires and tech giants. For a German Mittelstand company, the ecosystem in the USA is difficult to access and often not geared towards its needs – i.e., B2B, industry, high reliability.

The weakness of the US approach is its imbalance. While enormous sums are poured into developing chatbots that can imitate Shakespeare, practical application in the mundane but value-creating reality of manufacturing halls often falls by the wayside. I spoke with a developer from the Valley last week. His words: "Manufacturing? Oh, you mean like, making physical stuff? Sounds complicated." That pretty much says it all. The USA delivers the groundbreaking algorithms, but integration into the complex processes of an industrial company? That's not their core focus. The risk for us: we become technologically dependent on a handful of US corporations whose priorities are not ours.

Candidate 2: China – The State-Controlled Dragon

Shift to the East. China plays a completely different game. Less Wild West, more five-year plan. Private investments, compared to the US, are a joke. But that's only half the truth. The real power lies in the hands of the state, which, with 119 billion dollars in pledges and a clear plan, sets the direction. And this plan is formidable. China's focus is razor-sharp on the real economy: autonomous systems, smart manufacturing, healthcare, and the associated infrastructure. Large companies plan to invest around 78 billion dollars in data centers and cloud infrastructure by 2027. This isn't about poetry; it's about efficiency, scaling, and global dominance in production.

China's great strength is this ruthless speed of implementation. I've seen factories near Shanghai that were built from scratch within 18 months and now boast a degree of automation that would give some German works councils nightmares. They skip entire stages of development. And they are clever. Instead of copying expensive US models, they rely – see the DeepSeek example – on cost-efficient, open-source models. This massively lowers the hurdles for companies and accelerates broad adoption. This is a model that must be taken very, very seriously.

But of course, there's also a downside. Centralized control makes the system fast but also rigid and carries political risks. The issue of intellectual property remains a perennial problem – there's no getting around it. And then there's this new, subtle offensive: Chinese direct investments in European tech companies reached the 10 billion dollar mark in 2024, an increase of 50%. The focus is particularly on manufacturing hubs in Hungary and Spain. Is this a cooperative outstretched hand or an attempt to secure know-how and market access? I doubt that's an easy question to answer. For the Mittelstand, this means: China is both a massive threat due to its economies of scale, but also a potential source of cost-effective technologies and a lesson in consistent implementation.

Candidate 3: Europe & DACH – The Deliberate Federalist

Our Path: Different, But Not Necessarily Worse?

And then there's us. Europe. The continent of thinkers, poets, and… procrastinators? If you only look at the numbers, you might think so. Germany's AI commitment of 13 billion dollars since 2013 seems modest compared to US sums. Private venture capital for large AI models is scarce. We appear fragmented, slow, over-regulated. The conservative forecast that Europe's AI market will "only" reach 600-800 billion euros by 2040, while others think in trillions, seems to confirm this picture. One could despair.

But perhaps that's too simplistic. Perhaps we're not trying to keep up with the others' sprint, but are preparing for a marathon. Diego Perino, director of the BSC AI Institute, recently told me a crucial sentence: "Europe's strength lies in long-term, structural capabilities: talent, data, and computing power." That's the point! We have excellently trained engineers. Thanks to (yes, really!) the GDPR, we have high-quality, well-structured datasets. And we are specifically building a federal infrastructure, the so-called "AI Factories," which are intended to make high-performance computing accessible specifically to small and medium-sized enterprises.

Our approach is not to found the next OpenAI in a Parisian suburb – even if beacons like Mistral show that we could. Our approach is to lay the foundation so that the hundreds of thousands of Mittelstand companies in Europe can work with AI. The focus is clearly on industrial applications, on German core competence. We are not aiming for the product, but for the ecosystem. Our weakness – our fragmentation – could become a strength if it leads to a resilient, decentralized network. Our obsession with regulation could prove to be a "differentiating advantage," as Perino calls it. Because who wants to entrust their highly sensitive production data to an American cloud or a Chinese state-owned company? "Trustworthy AI" is not a buzzword; it could become our most important selling point. It's a slower, perhaps less glamorous path. But possibly the more sustainable one.

The Great AI Arms Race in Direct Comparison

To make the differences tangible, I have summarized the decisive factors in a table. This is not about grading, but a strategic roadmap that shows where the respective strengths and weaknesses lie.

Capital Efficiency: Who Gets the Most for Their Money?

The sheer billions can be deceptive. Far more interesting is the question of capital efficiency. Who achieves the greatest impact with their investment, especially in the industrial sector relevant to us? Here, too, philosophies diverge widely.

That's the crucial point. While the USA builds a cannon to shoot a sparrow, China builds thousands of precise air rifles. And Europe? We are just building the shooting ranges and training the shooters. This may seem slow, but it could ultimately lead to everyone in the country being able to hit targets safely and effectively, instead of just watching a cowboy with a bazooka.

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My Recommendation: What the Mittelstand Must Do Now

So, to return to the question of the managing director from East Westphalia: Yes, you have to deal with it. But no, you don't have to panic. The worst thing you can do now is to fall into paralyzing awe of the billions from overseas or frantically start some half-baked AI projects. Stop waiting for the next big all-rounder model from California. That's not your playing field. And please don't try to transfer the processes of a Chinese gigafactory with 50,000 employees to your company with 500 people. That's madness.

The only sensible path for the German and European Mittelstand is the European way – with a good dose of pragmatism. Focus on your domain expertise. You know your process, your customer, your market better than any AI. Identify one or two very specific bottlenecks in your company. Is it the elaborate lead generation in sales? Quality control at the end of the line? Predictive maintenance of your machines? Don't look for AI; look for the problem. And THEN evaluate which technology – often much smaller and less spectacular than expected – can solve this problem. Use the networks that are emerging here: the Fraunhofer Institutes, the cluster initiatives, the AI Factories. I bet that the winners in three years will not be those who had the biggest AI budget, but those who used it most intelligently for a clearly defined problem. That is the Mittelstand DNA. And that is our greatest asset in the age of AI.

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The 3 Decisive Questions for Your AI Strategy

Every managing director should not get carried away now, but ask themselves and their management team three very simple, but brutally honest questions.

1. Which specific business problem, not which technology, do we want to solve in the next 12 months? Be specific. "Filling the sales pipeline" is better than "introducing AI."
2. Do we have the data, the money, and above all, the talent to build our own solution, or is it smarter to access already trained, trustworthy AI through European ecosystems and specialized providers? Overestimating oneself is the most expensive mistake.
3. How do we measure success? In nebulous "innovation prestige" or in hard, cold euros in the bank account, in saved process costs, or in additional sales closures? Define your KPIs before you start.

Anyone who honestly answers these three questions is already ahead of 90% of the competition. The AI arms race of the superpowers is the big stage. But the real game, which decides the future viability of our industry, is taking place right here – in the companies of the Mittelstand.