AI talent is unique for its finite property, mid-mobility, and high dependence on education and immigration policies. It’s renewable, but only through long-term investment.

Unlike infrastructure or energy, which require years of heavy investment, talent can be imported. By hiring skilled professionals from abroad, you’re reaping the benefits of 20+ years of education funded by another country’s taxpayers. Mid-level and senior talent, in particular, can deliver measurable impact in less than three years.

And unlike data, endlessly replicable with a flick of a license agreement, talent is semi-liquid and finite.

Think of AI talents as rare Pokémon, which makes the AI war nearly a zero-sum game, especially in the short run. Every researcher, engineer, or scientist gained by one country is a loss for another.

My inspirations for this article:

* I was an expat once, now a Brit. I thought it’d be romantic, until reality hits. I am now ready to explore yet another continent that I could call home.

* Reports like those from OECD.ai and Tortoise Media look impressive—eye-catching headlines and sleek dashboards. But if you take their numbers at face value, you risk misleading your business—or worse, your country’s policy.

What happened in our world today?

In the UK, we feel the economy is stuck in reverse since Brexit. In Germany, the decline of manufacturing casts a shadow over its future. In the U.S., millions are bracing for what another Trump term might mean:

American interest in moving abroad is about to ‘go into overdrive.’ — Fortune

For some of you who live in Ukraine, Israel, or Taiwan, uncertainty is your daily life (link below).

When you can’t fix the system, you do the next best thing: you move to another. A better life for yourself, your career, and your family.

I am slowly building up an AI knowledge database. I aim to share it with you hopefully before Christmas, as a holiday gift 🎁 for you.

This article is about understanding—where nations stand, what’s overlooked by the AI data companies, and how this AI arms race could change your opportunities.

The questions I aim to answer:

* Some history: what’s the cost of losing talent?

* Are the big-name AI talent data trustworthy?

* What must go wrong for the US to lose its attraction to talent?

* How likely and how long would it take for other countries to catch up?

The Cost of Losing Talents.

The Talent Exodus to Taiwan and the Cultural Revolution (1940s)

In 1949, as the Chinese Civil War reached its climax, Chiang Kai-shek and the Nationalist government retreated to Taiwan. The exodus included the most brilliant minds like scholars, scientists, and administrators, they joined the journey, driven by fears of persecution under Communist rule.

On the mainland, the Communist Party focused on mobilizing workers and peasants, sidelining intellectuals during its early years of governance. The Cultural Revolution created a significant intellectual gap. This gap led to the further loss of thousands of educated individuals, and many of them chose not to flee to Taiwan. As a result, education and innovation came to a standstill. The process of rebuilding took decades.

Meanwhile, Taiwan flourished.

Those intellectuals who relocated laid the groundwork for a tech-driven future. Today, beyond TSMC, Taiwan is home to other giants like UMC, a pioneer in foundry services, and ASE Group, the largest provider of semiconductor packaging and testing services globally. China is 10 years behind Taiwan on chips.

Operation Paperclip a Post-WWII Rescue Mission.

In the rubble of post-WWII Germany, the U.S. and the Soviet Union weren’t just fighting over territory—they were fighting over brains. Operation Paperclip, a covert U.S. program, brought more than 1,600 German scientists, engineers, and technicians to America, including Wernher von Braun, the man who would later take the U.S. to the moon. The Soviets weren’t far behind, scooping up their own share of rocket experts.

These scientists had been the backbone of technological advances in Germany during the war. The departure slowed the nation’s technological recovery for decades.

In the U.S., these scientists became heroes of the Space Race. Von Braun’s team didn’t just build rockets—they built national pride, culminating in the Apollo 11 moon landing. The Soviets also leveraged their talent, putting Sputnik into orbit and scaring the U.S. into ramping up its own space program.

India’s Brain Drain (1950s–Present)

India is a paradox when it comes to talent.

It produces engineers and scientists by the millions, yet for decades, the country has struggled to retain them. The story begins in the 1950s, just after independence. India was brimming with ambition but hamstrung by red tape, limited infrastructure, and caste-based inequalities…

For many of India’s brightest, the dream wasn’t at home—it was abroad. An exodus of engineers and doctors to the West was underway.

The loss was profound, even until today, and the trend continues. By 2024, it is estimated that around 2 million Indian students will be studying abroad. Among them the top scorers of India’s prestigious Indian Institutes of Technology (IITs) revealed that 36% of the top 1,000 scorers in 2010 migrated abroad, with this figure rising to 62% among the top 100 scorers left.

By 2024, 2 million Indian students study abroad annually, while India’s IT sector misses out on $15-20 billion each year due to talent migration.

Storm Clouds Over the U.S.

The U.S. didn’t stumble into AI dominance—it built it brick by brick over 200 years. Geography, history, and culture all played a part.

English as the internet’s default language gave U.S.-trained models a treasure trove of data. Their policy is tech-friendly, venture capitalists fund bold, moonshot ideas, and their entrepreneurs thrive on risk-taking and learning from failure.

Europe? The moneymen are more cautious, and failure feels more like a career-ender than a lesson learned.

As long as the “US innovative, China replicates, and the EU regulate” pattern stays as is, the US is nearly unbeatable.

The chances of a dramatic fall are slim but gradual erosion?

What Must Go Wrong for the US to Lose Its Attraction to Talent?

* Immigration Blockades: During Trump's first term, there were significant immigration restrictions, including the temporary suspension of H-1B visas. If similar policies return, talent could choose other countries like Canada or Europe.

* Cost of Living Crises: Tech hubs like San Francisco are absurdly expensive. Talented professionals might opt for affordable, thriving alternatives like Berlin or Toronto.

* Supply Chain Disruption: Trade wars and tariffs could choke the flow of critical hardware—think GPUs and chips from Mexico or Asia—slowing AI research to a crawl.

* Worsen Fundamental Education: Only 16% of Americans are “AI literate,” and with the U.S. ranking 36th in general literacy, it means most citizens can’t effectively communicate with AI and include AI in their workflow, let alone develop one. This leaves America reliant on foreign talent and exposed to immigration shifts.

Losing focus on either one of the factors would hand over the lead to nations willing to outwork and outsmart the U.S.

Other developed nations are, of course, building their own AI ecosystems. The U.S. is notoriously hard to enter, much less friendly to stay, and lacks work-life balance; hubs like the UK, Canada, and Germany have become the obvious choice.

Are the Big-Name AI Talent Data Trustworthy?

Education and Salary as a Rough AI Talent Measurement.

Here's the Stack Overflow developer survey data that I got from OECD.ai.

Combined it with Tortoise Media’s AI talent rankings

AI Talent: Finite, Mid Liquidity, Not Scalable, Not Renewable.

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