The most significant long-term threat to the supply of critical materials isn't a lack of resources in the ground, but a lack of people. The aging workforce of geologists and mining engineers, with a shrinking pipeline of new talent, poses a greater systemic risk to the industry.
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Beyond displacing current workers, AI will lead to hiring "abatement," where companies proactively eliminate roles from their hiring plans altogether. This is a subtle but profound workforce shift, as entire job categories may vanish from the market before employees can be retrained.
LinkedIn's CPO reveals their unique data shows the skills needed for current jobs will change by 70% in just a few years. This rapid obsolescence is the primary driver for rethinking product development, as companies must adapt faster than ever to stay competitive.
The difficulty in hiring young talent is not a temporary trend but a "new ice age." It is driven by a smaller Gen Z population compared to millennials. The problem will worsen: within a decade, more people over 65 will be leaving careers than 16-year-olds are starting them, creating a long-term demographic crisis for employers.
During tech gold rushes like AI, the most skilled engineers ("level 100 players") are drawn to lucrative but less impactful ventures. This creates a significant opportunity cost, as their talents are diverted from society's most pressing challenges, like semiconductor fabrication.
The national initiative to reshore manufacturing faces a critical human capital problem: a shortage of skilled tradespeople like electricians and plumbers. The decline of vocational training in high schools (e.g., "shop class") has created a talent gap that must be addressed to build and run new factories.
AI is rapidly automating knowledge work, making white-collar jobs precarious. In contrast, physical trades requiring dexterity and on-site problem-solving (e.g., plumbing, painting) are much harder to automate. This will increase the value and demand for skilled blue-collar professionals.
Most AI applications are designed to make white-collar work more productive or redundant (e.g., data collation). However, the most pressing labor shortages in advanced economies like the U.S. are in blue-collar fields like welding and electrical work, where current AI has little impact and is not being focused.
While media outlets create hype cycles around certain critical materials like rare earths, other equally vital commodities such as tungsten and tin face similar geopolitical supply risks but receive far less attention. These 'un-hyped' bottlenecks present significant investment opportunities for diligent researchers.
The belief that investing in commodities is 'short human ingenuity' is flawed. These companies are R&D powerhouses in materials science, geology, and chemical engineering. ExxonMobil employs more PhDs than Apple, and their foundational innovations enable the consumer tech we see today.
Even if China could fully automate production to offset its shrinking workforce, its economic model would still collapse. AI and robots cannot replace the essential roles of human consumers, taxpayers, and parents, which are necessary for economic vitality, government revenue, and generational replacement.