Europe’s security wake-up call at Munich in 2025 was loud, public, and overdue. The message was straightforward: American security guarantees could no longer be treated as automatic, and defense readiness could no longer be managed as a legacy system optimized for peacetime efficiency. What followed was a surge in spending, urgency in rhetoric, and a growing realization that intent does not equal output.
“Strategic advantage today is less about innovation alone and more about reliability, predictability, and sustained delivery. Nations are not rejecting American technology because it is inferior. They are hedging against dependency.”For the United States, this moment should feel familiar. While Europe is confronting the gap between budgets and production in real time, the US has been operating inside that gap for years. The issue is not funding. It is not talent. It is not technology. It is execution at scale under pressure. The same structural frictions Europe is now naming openly already exist across American defense, infrastructure, energy, and advanced technology systems. This dynamic is no longer limited to weapons and manufacturing. It is now reshaping global trust in American technology leadership, particularly in artificial intelligence. The United States invented the transistor, the internet, and the transformer architecture that powers modern AI. It remains a technological powerhouse. Yet actions taken across multiple administrations have made allies increasingly wary of over-reliance on US-controlled systems. This concern is not ideological. It is operational. In 2022, sanctions following Russia’s invasion of Ukraine led to financial systems being shut off not only for sanctioned elites but for ordinary consumers. More recently, AI diffusion export controls limited access to advanced chips for many nations, including allies. These moves were legal and policy-driven, but they carried a clear signal: access can be revoked. Under an accelerated America First posture, the signal has grown louder. Broad tariffs applied inconsistently to allies and adversaries, aggressive rhetoric toward partners, and a sharply hostile posture on immigration have all contributed to a perception of unpredictability. Highly skilled, law-abiding professionals abroad increasingly hesitate to travel to or work with US institutions, citing fear of arbitrary enforcement and detention. These perceptions, amplified globally, matter in an era where talent mobility and trust underpin technological leadership. AI’s strategic importance intensifies these concerns. Nations do not want to risk having their access to foundational technology cut off by a foreign power. The result is growing interest in sovereign AI. Sovereign AI does not mean full independence. That is neither realistic nor necessary. There are no substitutes for US-designed AI chips manufactured in Taiwan, and critical components across the compute stack are produced globally, including in China. But there is a clear desire to reduce reliance on frontier models controlled by a small number of US companies and governed by US policy decisions. This is why open-weight and open-source models are gaining traction worldwide. Chinese models such as DeepSeek, Qwen, Kimi, and GLM are seeing rapid adoption outside the US. At the same time, countries across the Middle East, Europe, and Asia are investing in domestic foundation models and sovereign compute infrastructure. The UAE recently launched K2 Think, an open-source reasoning model. India, France, South Korea, Switzerland, Saudi Arabia, and others are pursuing similar paths. The strategy is pragmatic. Sovereign AI does not require building everything. By participating in global open-source ecosystems, nations ensure that no single actor can control their access. This mirrors how Linux, Python, and PyTorch became global infrastructure. No country owns them. No country can revoke their use. That property now matters more than performance at the margin. This fragmentation carries real risks. Erosion of trust among democratic allies is not a win. Yet there is a potential upside. Increased competition could slow consolidation, encourage regional champions, and keep innovation distributed rather than centralized. History offers precedent. US search engines came to dominate globally, but local champions thrived in China and Russia. AI may follow a similar path. Europe’s defense reckoning and the global push toward sovereign AI are symptoms of the same underlying issue. Strategic advantage today is less about innovation alone and more about reliability, predictability, and sustained delivery. Nations are not rejecting American technology because it is inferior. They are hedging against dependency. Europe is now being forced to translate political consensus into industrial output. The United States faces a parallel test of a different kind. Whether it can align policy, capital, and trust in a way that sustains its leadership rather than fragments it. Ironically, America First policies may end up strengthening global access to AI by accelerating open-source adoption and domestic alternatives elsewhere. The outcome will not hinge on who invents the next breakthrough. It will hinge on who others feel safe building with. The question is not whether the US can lead. It is whether it chooses to lead in a way others can rely on.