From GPUs to Copper: How AI Is Reshaping the Global Commodities Market

The development of artificial intelligence is increasingly affecting not only the semiconductor market but also the cost of the raw materials needed to build a modern computing infrastructure. If Nvidia accelerators and HBM memory chips have been the main focus of investors' attention over the past two years, copper has now emerged as another key beneficiary of the AI boom. Its price on the London Metal Exchange has once again climbed close to its historical high, reflecting the growing shortage of one of the most important industrial metals.

The reason is not only the rapid construction of AI data centers. Power grids, server equipment, cable infrastructure, and cooling systems require enormous amounts of copper, while additional demand continues to come from electric vehicles, which require several times more copper than conventional internal combustion engines.

At the same time, supply is no longer keeping pace with demand. One contributing factor has been the decline in production at Indonesia’s Grasberg mine, the world’s second largest source of copper ore. Following last year's landslide, the recovery in production has been much slower than expected. Meanwhile, geopolitical risks are also being priced into the market. The United States is considering imposing import tariffs on refined copper starting in 2027, prompting suppliers to redirect shipments toward the U.S. market. Copper inventories on the LME are declining, while trading volumes on COMEX have risen by more than 40% since the beginning of the year.

The shortage is particularly acute in China. Copper inventories on the Shanghai Futures Exchange have fallen by about 80% since March, reaching their lowest level in two and a half years. Despite the country’s high level of domestic production, a significant share of production is exported, primarily to the United States, widening the domestic supply deficit and increasing the cost of imported copper.

However, copper is only one part of a much broader challenge. Building new data centers requires more than constructing facilities and purchasing servers. It also requires significant investment in energy infrastructure, which has become one of the industry's biggest bottlenecks. Large power transformers, essential for connecting modern data centers to the electrical grid, are in increasingly short supply. Industry analysts estimate that about 40% of new data centers in the United States may be put into operation later than planned due to transformer shortages and issues with connecting to the power grid.

The situation is further complicated by the fact that transformer production also depends on copper, specialized electrical steel, and skilled labor. Equipment manufacturers are already expanding production capacity, and US authorities have designated these supply chains as critical to national economic security. Meanwhile, some of the recent market movers, including Amazon and Microsoft, have become the largest buyers of this equipment as they continue to ramp up investment in AI infrastructure.

For investors, this means that the key constraints are gradually moving further upstream in the supply chain. Previously, Nvidia accelerators were the primary bottleneck. Today, attention is shifting toward suppliers of the materials and components needed to build the broader AI infrastructure. That is why even relatively small segments are beginning to attract market attention. For example, Chinese manufacturers of synthetic diamonds have seen a sharp increase in interest after the start of commercial shipments of diamond heat sinks for advanced chips. Due to their exceptionally high thermal conductivity, these materials enable more efficient cooling of powerful AI processors and could play an important role in the next generation of server hardware.

As a result, the investment story around AI is gradually expanding far beyond chip manufacturers, with investor attention increasingly extending beyond Nvidia stock to the broader AI infrastructure ecosystem. The growing demand for copper, transformers, specialized materials, and advanced cooling technologies suggests that the industry's primary constraint is no longer computing accelerators alone, but the entire industrial infrastructure necessary for their operation. As AI deployment continues to accelerate, these upstream industries could become the next major beneficiaries of the investment cycle.