The American Competitiveness and Workforce Improvement Act (ACWIA) mandates a fee within each H-1B application. This money is specifically used by the Department of Labor to fund training for U.S. workers in technology and other high-demand fields, directly linking the hiring of foreign talent to upskilling the domestic workforce.
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Bringing manufacturing back to the US won't mean a return of old assembly line jobs. The real opportunity is to leapfrog to automated factories that produce sophisticated, tech-infused products. This creates a new class of higher-skill, higher-pay "blue collar plus" jobs focused on building and maintaining these advanced manufacturing systems.
As the U.S. tightens immigration for skilled workers, innovation may shift to countries with more welcoming policies. This macroeconomic trend presents a personal finance strategy: diversifying portfolios with international ETFs to capture growth in emerging tech hubs and hedge against a potential decline in U.S. competitiveness.
The 30-40% pay premium for AI PMs isn't just because "AI is hot." It's rooted in the scarcity of their specialized skillset, similar to how analytics PMs with statistics backgrounds are paid more. Companies are paying for demonstrated experience with AI tooling and technical fluency, which is rare.
Don't hire based on today's job description. Proactively run AI impact assessments to project how a role will evolve over the next 12-18 months. This allows you to hire for durable, human-centric skills and plan how to reallocate the 30%+ of their future capacity that will be freed up by AI agents.
U.S. Citizenship and Immigration Services (USCIS) is almost entirely funded by application fees, not taxes. A portion of these fees, including those from H-1B visas, is distributed to agencies like the Department of Homeland Security and ICE to investigate visa abuse and fund enforcement operations.
When introducing AI automation in government, directly address job security fears. Frame AI not as a replacement, but as a partner that reduces overwhelming workloads and enables better service. Emphasize that adopting these new tools requires reskilling, shifting the focus to workforce evolution, not elimination.
Instead of fearing job loss, focus on skills in industries with elastic demand. When AI makes workers 10x more productive in these fields (e.g., software), the market will demand 100x more output, increasing the need for skilled humans who can leverage AI.
Data from 2004-2023 reveals low unemployment in occupations that heavily utilize H-1B visas, such as tech and engineering. This suggests that foreign workers are filling a talent gap rather than displacing a large number of available American workers, challenging the narrative that immigration is a primary cause of job loss in these sectors.
In remote, services-based businesses, pressure to deliver quality and the difficulty of junior mentorship make hiring senior engineers a necessity. The cost and complexity of building remote training programs often outweigh the benefits of hiring less experienced talent.
In a paradigm shift like AI, an experienced hire's knowledge can become obsolete. It's often better to hire a hungry junior employee. Their lack of preconceived notions, combined with a high learning velocity powered by AI tools, allows them to surpass seasoned professionals who must unlearn outdated workflows.
