The race for AI supremacy is not just about models but about securing the underlying infrastructure. The most significant bottlenecks and price appreciation over the next 3-5 years will be in physical assets: land for data centers, permits to build, energy to power them, and the compute itself.

The primary constraint on AI development is shifting from semiconductor availability to energy production. While the US has excelled at building data centers, its energy production growth is just 2.4%, compared to China's 6%. This disparity in energy infrastructure could become the deciding factor in the global AI race.

The rapid expansion of AI is creating unprecedented energy demand in Asia, necessitating a five-year, $5 trillion investment in the energy sector. This figure represents nearly double the investment of the entire previous decade, signaling a massive and urgent reallocation of capital towards power infrastructure.

According to the IEA, the global competition in artificial intelligence will be decided not just by technology, but by the availability and cost of electricity. Data centers are incredibly power-intensive, making energy a critical, and often overlooked, factor for AI supremacy.

Companies like Tesla and AWS are investing in lithium and copper refining to control their supply chains, a new phase of vertical integration driven by AI's massive industrial needs for data centers and batteries.

An AI query consumes 30 times more electrical energy than a standard Google search. As AI becomes ubiquitous, the resulting demand for electricity—and the copper-intensive infrastructure to generate and transmit it—is projected to grow almost infinitely, creating a structural shortage.

The seemingly immaterial world of AI is entirely dependent on a vast physical system. Beyond electricity, AI's expansion drives demand for industrial commodities like copper and aluminum for grids, refined fuels for transport, and robust shipping infrastructure. This links digital growth directly to global commodities and logistics markets.

Most of the world's energy capacity build-out over the next decade was planned using old models, completely omitting the exponential power demands of AI. This creates a looming, unpriced-in bottleneck for AI infrastructure development that will require significant new investment and planning.

Unlike past economic cycles driven by consumer spending, Latin America's next growth phase will likely be fueled by capital expenditures (CAPEX) in infrastructure, AI, and factories, spurred by favorable global and local factors.