What Silicon Valley and Wall Street Are Missing About AI and Advanced Computing.
As I travel across the USA, attend business workshops, and speak with founders, fund managers, and engineers alike, one theme has become abundantly clear: the rise of artificial intelligence (AI) is the most accelerated technology boom since the electric vehicle (EV) explosion between 2012 and 2024. Startups are being formed at breakneck speed, investor decks are flooding in boxes, and capital is flowing toward anything labeled “AI.” But underneath this gold rush lies a familiar pattern, and a critical oversight that could prove costly for Silicon Valley and Wall Street.
The Pattern: Hype Without Infrastructure
The EV sector's rapid expansion taught us a powerful lesson. While massive investments were funneled into flashy, front-facing components vehicle designs, battery startups, and charging stations, many overlooked the upstream fundamentals. Companies failed to account for resource bottlenecks, manufacturing scalability, and supply chain constraints. The result? Dozens of startups collapsed under the weight of capital inefficiency and logistical friction.
Now, the same pattern is emerging in AI and advanced computing.
Yes, AI models are impressive. Yes, the innovation pace is thrilling. But most of these startups are building castles on sand. Behind the algorithms and GPU clusters lies a more sobering truth: AI, like EVs, is infrastructure dependent. And the foundational element behind this infrastructure isn’t just silicon or code it’s COPPER.
The Missing Link: Copper and the AI Energy Backbone
Copper is the unsung hero of the digital revolution. Every server rack, every high-performance computing (HPC) unit, every data center and edge node rely on efficient electrical conductivity, and nothing delivers that like copper. As AI models grow larger and data centers scale up to meet computing demands, the need for high-capacity power delivery and heat management will skyrocket. You can’t electrify a data-driven future without copper.
Yet, in boardrooms from Menlo Park to Midtown Manhattan, copper barely enters the conversation. When was the last time an AI pitch deck discussed mineral sourcing? When did a hedge fund analyst last model in copper price volatility as a risk to compute scalability?
Meanwhile, China isn’t making this mistake.
China’s AI growth is tightly woven into its control of the global supply chain. From solar panels to EVs, wind turbines to server farms, China produces at 30–40% lower costs than the U.S. or Europe. Why? Because they dominate upstream mineral access, especially copper. Their small- and large-scale miners, smelters, and refiners operate at a scale the West has yet to match.
Wake-Up Call: AI, Renewables, and the Geopolitics of Supply Chains
What Wall Street and Silicon Valley continue to ignore is the convergence of AI, renewables, EVs, and mineral supply chains. These aren’t siloed industries. They’re intertwined threads of the same future. AI data centers demand renewable energy to be sustainable. Renewable grids require efficient storage and transmission. All of this depends on minerals, especially copper.
If the U.S. hopes to remain competitive in AI and computing infrastructure, it must invest not just in chips and models, but in mines and refineries. This means forging relationships with countries that possess these critical resources.
A New Frontier: Zambia and the Copper Opportunity
The good news? It’s not too late.
Countries like Zambia, long known for their copper reserves are seeing a resurgence of strategic interest. Companies such as Bbabsal Mines Ltd, which I lead, are actively exploring and securing mineral rights across Northern Zambia and the Copperbelt Province. Our mission is clear: to build a responsible, transparent, and scalable source of copper that supports global AI infrastructure and clean energy transition.
This isn’t about extraction for profit. It’s about aligning the mineral economy with the data economy. If the U.S. can reimagine its approach, if venture capitalists, policymakers, and technologists can connect the dots between AI and geology, we have a chance to build a future that’s not just intelligent, but sustainable and secure.
Final Thought
In the AI race, models matter. Chips matter. But minerals matter more than most realize.
Silicon Valley must look beyond silicon. Wall Street must look beyond balance sheets. The next AI unicorn won’t just run on machine learning it’ll be powered by copper mined in places like Zambia, refined through sustainable partnerships, and delivered through a reimagined global supply chain.
The age of AI is here. But without copper, it won’t run.