The AI Minerals Gap: How the World Can Meet Increasing Critical Minerals Demand Driven by AI
September 6, 2026
to accelerate. However, less attention is being paid to the critical minerals required to support this
exponential AI demand. Minerals such as gallium, germanium, and copper make the rapid AI buildout
possible.
Many investors don’t fully appreciate how important these minerals are to the AI revolution.
However, AI cannot reach its full potential unless sufficient critical minerals are secured to support its
rapid expansion.
What are Gallium and Germanium?
technology. Real world use cases include the production of chips for mobile phones, 5G base stations,
Wi-Fi equipment, solar power, military radar systems and more. Gallium, a soft silvery metal that has a
low melting temperature of ~30°C, allowing an easy transition from solid to liquid state which is
useful for advanced engineering and electronics. Germanium is essential for fiber-optic cables as it
controls how light travels through the cable safely without escaping. Both commodities are byproducts of
US Dependence on Foreign Mineral Imports
refining capacity. Both gallium and germanium are essential to the high-performance chips and
fiber-optic infrastructure underpinning AI compute. The U.S. Geological Survey (“USGS”) found a 30%
disruption to gallium supply alone could reduce U.S. economic output by $600 billion, equating to ~2%
of national GDP. Additionally, the International Energy Agency's ("IEA") own data center forecasting,
shows gallium demand growing 11% by 2030 compared to 2024 levels, the fastest of any mineral tied to
the data center buildout, against 2% growth for copper and silicon and 3% for rare earths broadly.
With rising geopolitical tensions, the gap between critical minerals needed for AI and domestic supply
continues to grow. This could become a potential national security issue as AI development continues to
expand at a rapid pace.
Africa’s Role in Critical Minerals
The Atlantic Council puts Africa's share of global critical mineral reserves at roughly one-third, yet the
continent remains locked out of the value chain by a lack of geological data and developed infrastructure,
exporting its minerals largely unprocessed into Chinese-dominated supply chains.
Ironically, AI itself is helping to support mining exploration. Atlantic Council researchers Anthony
Carroll and Jef Karel Caers find AI and data applications can reduce drilling time by up to 80%,
while also modernizing operations and de-risking investment, with firms like KoBold Metals already
turning that into real discoveries, including the Mingomba project, a major copper discovery in Zambia.
The goal is to construct this as a “smart mining” initiative, rather than seeing it as separate siloed AI and
mining investment tracks. The intersection between AI and mining will continue to grow and become
prevalent. Ironically, the mining industry will need to continue to leverage AI to make new discoveries
and reduce the time to production in order to meet growing supply deficits driven by AI.
Canada’s Position
Canada holds world-class reserves of important critical minerals such as cobalt, nickel, copper, and
uranium, ranking as the world's fourth largest cobalt producer, a top six nickel producer, and the
second largest uranium producer globally.
With a GDP of ~$2.3 trillion in 2025, Canada is a fraction of the size of economic superpowers like the
U.S. and China. However, the AI paradigm shift could make Canada a more important player on the
economic stage with its vast supply of quality mineral deposits.
The real question isn't whether Canada's critical minerals will be needed. It's whether Canadian capital
and Canadian operators capture that value. With Canada’s lower domestic processing capabilities, the
country remains dependent on Chinese processing & foreign offtake agreements like prior commodity
cycles, such as the 2021-2023 EV battery metals boom.
The Investment Potential
The bottleneck isn't the mining itself. It's the centralization of the midstream. The Oregon Group's read of
the IEA's own numbers shows ~60% of refined copper comes from just three domestic producers, and
90%+ of aluminum and silicon is concentrated almost entirely in China. Meanwhile copper and
aluminum insulation alone make up ~50% of the cost of a transformer, and grain oriented electrical steel
accounts for another 20%. Meaning the equipment layer connecting a data center to the grid is itself a
concentrated-materials bet.
While AI driven explorations could potentially shorten the discovery phase, there’s still bottlenecks
around processing and refining capacity sitting between raw minerals and usable finished products.
Much like how AI infrastructure requires good refined data to be trained, AI hardware requires critical
minerals to be refined for material utilization.
Institutional investors should not only look to invest in mining equities, but should also deploy capital
towards building the processing and refining infrastructure that converts raw extraction into actual
industry supply chain sovereignty and assets with growing intrinsic value thanks to the growing demand
for AI.
Hyperscalers and investors continue to spend CapEx on AI data centers, meanwhile a significant
investment opportunity exists in the critical minerals required to make the AI revolution possible.
Mutually Beneficial Results
In addition to financial returns, the mining of critical minerals and resulting development of AI can also
support the communities where the minerals are found. The communities sitting on mining endowments
of mineral resources are often the same communities that stand to gain the most from mining production
and AI. Many of which are in emerging markets, thus the wealth created can result in affordable
healthcare access, education infrastructure, and financial inclusion.
Countless forecasts exist on how AI will boost GDP. Almost none address how AI is quietly boosting
demand for the critical minerals that power it. It has still yet to be determined how the world will meet
the growing demand for critical minerals and which countries will be winners from this increasing
AI demand.
References
4. USGS. Quantifying Potential Effects of China's Gallium and Germanium Export Restrictions on the
5. Government of Canada. Canada's critical minerals. Source. June 30, 2026. Accessed September 5,
6. S&P Global Market Intelligence. From Discovery to Delay: Mine Permitting Stretches Project
8. CNBC. What are Gallium and Germanium? China curbs exports of metals critical to chips and other
tech. Arjun Kharpal. Source. July 6, 2023. Accessed September 6, 2026.
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