Continental Drift
Europe in the Age of the Technodollar
Europe’s relative tech underperformance is often explained in terms of culture, regulation, or capital. These are symptoms, not causes. Regulation is uneven but not uniquely burdensome. Capital is abundant, perhaps disproportionately so considering the size of Europe’s native tech sector. And in my experience there is very little difference in the work ethic or risk appetite of the best European and U.S. startups.
What’s missing is not effort, talent, or money. It is the scaled platforms that make an ecosystem compound over time.
This missing industrial layer now matters more than ever. The rise of AI is not just a new product category. It’s an architectural shift in the global economy. And it intersects directly with Europe’s traditional strengths: automotive, pharma, chemicals, and supply chain and logistics. The age of the technodollar is not just about tech dominance, it is about industrial transformation. Europe needs an industrial policy built around energy, fostering AI powered industrial platforms, and attracting (or retaining) the people needed to run them.
The Missing Middle: Platforms that Compound
Innovation economies rest on three pillars. Universities advance the frontier of knowledge. Startups absorb new tools and mutate them into fresh business models. But between them lies a critical middle layer: scaled firms that turn insight into infrastructure.
This layer does two things. First, it performs the heavy lifting of systematization. As W. Brian Arthur noted, new technologies do not change economies through invention alone. They must be embedded: converted into platforms, products, and operational standards that people can build on. Second, scaled firms become schools of scale for executives, advisors, and investors, who can take these lessons into the next generation of startups.
Firms like Amazon, Google, and Nvidia don’t just dominate markets, they become infrastructure for new innovation. Their platforms offer APIs, capital, and talent networks that lower the cost of building adjacent ventures.
Europe excels at the bookends. Its universities remain world-leading. It has no shortage of ambitious founders and has produced high-quality firms such as ASML, SAP, Spotify, and Adyen. But these firms do not function as platforms in the North American sense. They are tightly bounded, optimized for excellence within vertical domains, and generally lack ecosystem-wide spillover. They generate value but not gravity.
The result is a structural absence at the heart of Europe’s innovation economy. Without scaled tech incumbents, there is no machinery to absorb frontier science, no internal labor market to circulate talent, no recursive loop through which knowledge compounds. Europe becomes a source of ideas and a site of consumption but not the ground on which the next industrial regime is assembled.
Deepmind fits awkwardly into this mix as it is now a key part of Google’s scaled R&D efforts but began as a startup not a lab. But it also shows where Europe’s issues are and aren’t: Deepmind had no problem raising money from global investors; but when it needed to get hold of truly scaled compute and capital West Coast US tech giants were the only answer. It is unlikely that Deepmind could have achieved its various breakthroughs as a standalone entity, and unthinkable as part of Siemans or SAP.
Why the Gap Exists: The Industrial Policy Mistake
Marios Draghi’s report on European competitiveness highlights tech as a key difference between European and US productivity. But Draghi’s framing, comparing Europe to the U.S., misses the more instructive contrast: China. The divergence between the two is a live A/B test in industrial strategy.
China responded to the emergence of the digital economy with strategic intent. It pursued a recognizably Listian approach to industrial policy. The Great Firewall was also a digital tariff wall, insulating local platforms as they scaled. At the same time, export-oriented subsidies flowed to firms like Alibaba, Tencent, and Huawei, enabling them to build capacity and eventually compete abroad.
Europe, in contrast, maintained an open market posture but failed to build internal defences. Industrial policy was not simply neglected, it was actively discredited, viewed as incompatible with the principles of an efficient, liberalized economy. Meanwhile, competition policy, guided by a narrow focus on consumer pricing and choice rather than national or bloc development, became a barrier to the strategic consolidation or nurturing of domestic champions. In practice this meant that while Europe welcomed global tech entrants it too often failed to cultivate its own.
Pride played a role too. Europe, especially in the peak neoliberal moment between German reunification and the 2008 financial crash, saw itself at the very least as a peer to the U.S. rather than an emerging economy in need of protection. Indeed, for much of the time it appeared as if we had achieved some kind of alchemy: Germany, France, and the UK in particular converging on U.S. GDP per capita while maintaining a more humane form of capitalism.
All this, and the global underestimation of the digital economy in the wake of the dotcom crash, led to an orientation toward legacy strength rather than developing and protecting new domains.
The Technodollar Moment
The technodollar marks a shift in the basis of U.S. global leverage: from finance and force to compute and code. It buys influence over industrial standards, talent flows, and supply chain dependencies. Compute is the new chokepoint.
For Europe, the implications are twofold. On the supply side, the United States and China are now vertically integrating AI from end to end, owning the chips, the models, the infrastructure, and the distribution layers. Europe has no sovereign stake in any of these domains. It is dependent on foreign supply chains for the very tools that will determine the pace and shape of industrial renewal.
On the demand side, European industry is facing direct competition from AI-enabled challengers. This is most pronounced in automotive but similar dynamics are unfolding in chemicals, pharma, logistics, and beyond. AI is not simply augmenting these fields, it is redefining them, and it is doing so largely outside of European control.
Even Europe’s intangible champions, luxury goods and finance, are at risk. Prestige economies don’t float on sentiment alone. Without the ballast of industrial leadership, brand and talent eventually drift elsewhere.
The quandary of the German car industry, caught between Tesla and BYD, or BASF, forced to significantly relocate to China in search of affordable energy, may be coming to all of Europe’s industrial champions.
Let Go of the AI Powerhouse Fantasy
The impulse to compete head-on is understandable but self-defeating. Europe will not win a race in general-purpose AI. The stack is too deep, the capital too entrenched, and the geopolitics too locked in.
Yet many European leaders still speak in slogans: “AI sovereignty,” “AI powerhouse,” “the next Silicon Valley.” These ambitions are not just unrealistic, they misdirect attention and resources.
Europe must reframe the goal. Not AI at the frontier, but applied AI in sectors where Europe already leads. The next industrial champions won’t be those who train models, but those who wield them to reshape existing value chains and create new ones.
A Strategic Response
To build industrial tech strength, Europe needs a coordinated strategy across three axes: energy, platforms, and people.
Energy is foundational. AI consumes immense computational power, and the infrastructures it enables. robotics, semiconductor fabs, automated supply chains, etc, are power-hungry. Clearly climate ambitions must be balanced against industrial requirements. But power supply is actually a bigger question: it will not be possible to compete in an electrified economic world when close to two-thirds of our power comes from imported fossil fuels.
Second, Europe must re-embrace the logic of infant industry protection, though not in the traditional sense. It should target sectors where it retains latent strength: pharmaceuticals, materials science, chemicals, auto, and supply chains. Within these, the priority must be to develop new platforms that apply AI to real industrial problems: molecule simulation, logistics optimization, circular manufacturing, etc. The tools of economic statecraft such as targeted subsidies, strategic procurement, mission-oriented R&D must be directed toward challenger firms. The next industrial champion may already exist, buried inside a legacy corporate, or latent in a university lab. But it will need help to emerge.
Finally, Europe must reckon with its human capital dilemma. Too many of its best operators build elsewhere. It is not enough to tweak tax codes or offer golden visas. What’s needed is a mission-driven talent strategy. One that actively recruits experienced builders and embeds them in strategically important sectors. European governments should be on the hunt for Morris Changs and willing to support them to build TSMCs from automotives to chemicals. Taiwan built an industrial giant by backing one visionary with the right tools and mandate. Europe must do the same and at greater scale.
Conclusion: The Clock Is Ticking
Europe missed the digital wave. It cannot afford to miss the AI-industrial one. The technodollar shift is a window, and, if it acts now, Europe can anchor itself in the next phase of global industrial history. Not as a peer to Silicon Valley, but as a sovereign producer in applied AI.