Schick's move to Texas corresponds to the geographical restructuring of the US AI industry. San Francisco still controls models, venture capital, and software talent, but Texas is attracting data centers, electricity, semiconductor supply chains, and industrial computing projects; AI is shifting from pure software competition to a capital-intensive industry that requires land, power grids, gas power generation, cooling, and high-voltage transmission.

In terms of capital pathways, the US has formed a continuous financing chain of "venture capital - public markets - hyperscale cloud providers - debt financing - data center construction." McKinsey estimates that by 2030, global data centers will require about $6.7 trillion in investment, with AI data centers needing about $5.2 trillion; this scale is more favorable for the US, which has a deep equity and debt market, dollar financing capability, and large tech buyers.

Historically, the gap between the US and Europe has not always widened. Around the year 2000, European productivity was closer to that of the US; since then, the US has formed centralized tech giants in internet platforms, cloud services, mobile computing, and AI, while Europe has retained more manufacturing, finance, public services, and small to medium-sized enterprise structures. Only 4 of the 50 largest tech companies in the world are located in Europe, indicating that the gap is mainly concentrated in high-profit, scalable software and platform layers.

This is a matter of capital concentration. The AI economy does not raise incomes equally across countries but prioritizes regions that own model companies, chip supplies, cloud platforms, data centers, and capital market exit channels. Europe does not lack talent or investment, but lacks the organizational capacity to rapidly convert technological experiments into global platform profits; the acceleration of the US wealth advantage is essentially the compound interest of technological and financial returns within the same system.

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