“The end of Nicolas Maduro's rule in Venezuela along with U.S. threats to Iran shows we are in a new imperial age.
This time, it isn't only about armies, it's about data. Artificial intelligence is revising our concepts of sovereignty and power, adding an important realm in which two nations dominate: the U.S. and China. The story is still being written, but power is concentrating in these two poles.
Sovereignty here doesn't mean access to powerful tools or building applications on top of them. It means the ability to design, train, operate, secure and deploy foundational AI systems capable of highly advanced functions in national defense and other sensitive areas of the state without external permission or dependence. By that definition, the field already looks far narrower than most policy debates assume.
Look how the global environment has changed. For roughly 35 years after the Cold War, globalization favored efficiency. Supply chains linked across continents. Manufacturing migrated to lower costs. Capital and talent flowed freely. States accepted dependence in exchange for market access. The internet connected markets, narratives and politics.
That era began to unwind in the early 2020s. The pandemic exposed the fragility of supply chains, borders closed, and governments rediscovered sovereignty under pressure. What began as diversification hardened into localization. Migration slowed across the U.S. and Europe. Security displaced efficiency as the organizing principle of economic policy.
Geopolitics followed. China accelerated its bid for primacy. Across the Middle East, South Asia and the Pacific, integration gave way to rivalry, and dependence became a liability.
Yet even as globalization reversed, connectivity didn't. Space-based networks extended internet access. Data, content and influence continued to move across borders. The result is a world that is simultaneously deglobalizing and hyperconnected. In this strange new environment, modern AI emerged.
As frontier models, the technology capable of large-scale problem-solving, became widely available starting in 2022 as ChatGPT, adoption occurred at an unprecedented pace. Within months, billions of people had access to these powerful cognitive tools. Control over the underlying systems, however, concentrated into the hands of a few firms in the U.S., with China as the only rival ecosystem.
This concentration reflects three hard requirements of AI sovereignty.
First, elite competence. Not mass digital literacy, but a very small pool of people capable of building, training and operating large-scale frontier AI models. This talent is scarce, globally mobile and increasingly clustered.
Second, energy at scale. AI is power-intensive. Training and operating frontier models requires vast quantities of reliable electricity. This is a physical constraint, not a regulatory one.
Third, financial depth. Frontier AI demands sustained investment over long time horizons, often without near-term returns. Only systems with extraordinary amounts of capital can absorb that cost.
At present, only the U.S. and China appear to have all three at the necessary scale and under sovereign control.
A few countries have some of what AI sovereignty requires. The Gulf states have capital and energy but lack elite AI competence. The U.K. has exceptional talent but lacks energy scale and sufficient financial depth, as shown by the sale of DeepMind to Google in 2014.
Britain can claim DeepMind as a national success, proof that British universities and culture can produce world-class AI talent. But that talent now serves U.S. strategic priorities, operates under U.S. corporate governance, and would be subject to U.S. export controls in a crisis. The building is in King's Cross. The sovereignty is in Mountain View.
Continental Europe should possess all three requirements but has struggled to retain its best people, many of whom now work for American-owned firms. Russia is perhaps in the worst position: It has energy, but elite competence and capital are fleeing.
There is also a fourth, less-discussed constraint. AI isn't merely built; it must be trusted. As AI becomes embedded in the military, intelligence and cyber programs of the state, dependence on foreign systems becomes harder to justify. So autonomy is yet another requirement of AI sovereignty.
For countries outside the U.S. and China, this doesn't mean the race is over, but it is narrowing. Some will align closely with one of the leaders. Others will seek partnerships to secure influence at the margins. Few will be able to sustain the fiction of full independence.
AI sovereignty isn't a prize many nations can win. The strategic task then is to determine how to retain agency when technological power is concentrating rather than dispersing.
---
Mr. Tugendhat, a Conservative, is a member of the British Parliament and a distinguished fellow at the Hudson Institute. Mr. Ahlberg is CEO of Recorded Future, a cybersecurity company.” [1]
The building of AI that is smarter than all the people is still a research project. The results of research tend to be unpredictable. DeepSeek case shows that great research results could be reached for a moderate investment. Then the AI economy goes into a deep crisis, the emerging imperial powers in AI are humbled.
Here are the facts that can be verified:
AI is still a research project: The building of AI that is smarter than all people (AGI or superintelligence) remains a research goal, with experts debating when or if it will occur.
DeepSeek's impact: The Chinese AI startup DeepSeek did make headlines in early 2025 for releasing high-performing, cost-effective open-source models that challenged the assumption that only massive investment could produce top-tier AI.
Economic concerns: There are ongoing discussions and concerns among economists and analysts about the potential for an AI investment bubble and a future economic crisis if highly leveraged investments in the sector go bad, or if rapid AI adoption causes massive job losses.
US leadership challenges: DeepSeek's success was described as a "Sputnik moment" that shook Silicon Valley's complacency and challenged the assumption of unwavering US dominance.
If you have some money to invest into AI, you have to understand the risk of this research project.
1. The New Bipolar World of AI. Tugendhat, Tom; Ahlberg, Christopher. Wall Street Journal, Eastern edition; New York, N.Y.. 30 Jan 2026: A15.
Komentarų nėra:
Rašyti komentarą