H-1B Workers are Critical for AI Dominance
Attracting and retaining talent will be critical in deciding whether the United States can stay ahead of China in the race to build out Artificial Intelligence technologies — an obvious lesson that now appears lost on American policymakers, but not on China.
Last August, the Chinese State Council announced its most comprehensive AI policy initiative to date. One directive of this “AI+” initiative is to expand China’s AI talent pool by encouraging enterprises to appeal to skilled workers using equity, stock options, and other incentives. The Chinese State Council has also announced a new visa for foreign STEM graduates.
Meanwhile, support for the American AI workforce is conspicuously absent from the White House’s recent AI Legislative Framework. And recent proposed and enacted changes to the H-1B visa program (for skilled immigrants) and OPT (Optional Practical Training, which eases a college student’s path to employment after graduation) either make it harder for AI experts to remain in the United States or fail to help their prospects.
The booming AI sector in the United States has greatly benefited from immigrant founders and engineers.1 Without sustaining and enhancing America’s AI talent advantage, we risk ceding ground to China in a competition with significant national security implications.
By the numbers
Estimates vary widely, but there are between about 50,000 and 200,000 AI jobs in the United States.2 Workers employed in these jobs are in high demand, with postings accelerating by the day.3
And as the sector becomes more and more important, the share of H-1B workers who work in AI has also climbed.
Using the most recently available FOIA data on H-1B approvals, we estimate that nearly a thousand workers who received H-1Bs in 2024 work in AI-related occupations,4 representing 1.12 percent of all approvals that year.
That figure may not sound huge, but this share far exceeds AI’s presence in the broader American workforce, in which AI jobs account for only 0.06 percent of all jobs.5 (The AI share of H-1B approvals also does not include university researchers in AI, for which an uncapped, or theoretically unlimited, number of H-1Bs can be issued.)
These annual flows of H-1B workers into AI are starting to add up. Using the share of approved H-1B Labor Condition Applications (LCAs) — a prerequisite for filing an H-1B petition — we estimate that H-1B workers now represent 4.3 percent of the nation’s total AI workforce.6
Nearly four out of five new H-1B holders working in AI also completed their education in American universities, compared to 52 percent of H-1Bs overall. Losing many of these workers to China would undermine the domestic AI industry and could threaten American national security.
In the small but rapidly growing AI labor market, the addition of 1,000 high-skilled workers each year would have an outsized impact on American competitiveness. With reforms to the H-1B visa selection process, we could attract even more AI experts.
How to Triple the Number of AI Workers on H-1Bs
Had H-1Bs been selected by EIG’s proposed wage-ranking system in 2024, the number of AI workers admitted would have more than tripled, rising to 3,330.7 A shift of that magnitude would amount to a meaningful expansion of the American AI talent base.
H-1B workers in AI are already well compensated, earning a mean wage of $150,000 — 37 percent above the already high average wage of H-1B holders broadly. A wage-ranked selection system would boost their mean wage even higher to $169,000.
Beyond their direct contributions to AI development, each worker generates substantial fiscal returns: the average federal fiscal impact of current H-1B AI workers is $38,000 per worker, rising to $44,000 under a wage-ranking system.8
Another way to clearly see the superiority of the wage-ranking model is to simulate what would have happened if it had already been adopted in the past. Under wage-ranking, the share of new H-1B visa recipients in AI would have been 3.9 percent in 2024 rather than 1.1 percent.9
The current H-1B lottery-based system favors large tech firms and relies on easily-manipulated occupational classifications.10 By reflecting actual market demand signaled through wages, a ranking system would satisfy frontier AI startups’ hunger for talent, generate positive fiscal impacts for the American people, and boost American innovation into the future.
According to the National Foundation for American Policy, 65% (28 of 43) of the top AI companies in the United States have at least one immigrant founder. 70 percent of full-time graduate students in AI-related fields at American universities come from abroad.
Estimates of the number of AI workers in the United States vary considerably. Lacking national estimates, researchers typically rely on survey data and private databases. The following list provides a few examples:
According to OCInsights, there were 101k AI professionals in 2025, including university researchers and non-university workers.
Jonathan Westover and Fei Tang estimate 90k workers with AI job titles.
CBRE’s 2025 Scoring Tech Talent report identifies 285,235 AI jobs as of 2024.
UMD-LinkUp identifies 50k AI jobs as of January 2026.
At the low end, based on standard occupation codes, the BLS reports 40,300 computer and information research scientists in 2024.
See UMD-LinkUp AI Maps, and LinkedIn’s Jobs on the Rise trends data for example.
Fiscal Year 2024, as referenced throughout this post.
H-1B AI workers were identified based on job titles provided on I-129 forms, as well as those who have a tech job for small AI-focused companies. 811 workers had an AI-related job title, and the remaining 232 were identified as AI workers based on their employer. See our github page for more information on methodology.
This estimate uses the share of approved LCA beneficiaries for an H-1B visa application that have an identified AI-related job. Assuming a 6-year stay, these shares are applied to the capped number of annual H-1B visa approvals (85,000) for 2020-2025.
To estimate how many AI workers would gain H-1B visas under wage-ranked selection, we reconstruct the full applicant pool from lottery winners. Because the lottery selects randomly, we can repeatedly sample from actual winners to simulate the complete set of entries. We then apply wage-ranking criteria to this reconstructed pool and average results across 200 iterations to derive robust estimates.
Projecting wage-ranked H-1B estimates to FY2025 and Q1 2026 is not feasible. Wage-ranking simulation outcomes do not vary linearly with LCA data, preventing reliable extrapolation.
“H-1B Middlemen Bring Cheap Labor to Citi, Capital One”, Bloomberg, June 27, 2025