The artificial intelligence (AI) hype cycle may be coming to an end. Technology giants and investors alike are enthusiastic about AI’s potential to drive productivity gains and transform the economy.
But certain resource constraints could prevent AI growth rates from meeting lofty expectations. Indeed, investors in recent months have begun to question how long it will take for the multibillion dollar investments in AI to translate to profit growth. But the bottlenecks might not be where you expect.
“One of the ironies of producing an advanced technology like AI is that it requires vast physical resources, and you might not think of such advanced technology as being physically constrained,” says U.S. economist Jared Franz.
Not all resource constraints will make the news like shortages of advanced semiconductors made by NVIDIA and other chipmakers. Here are four resource constraints that could slow the growth of AI — and present opportunities for old economy companies.
Generative AI tools like ChatGPT run on large language models hosted on thousands of servers in massive data centers. These data centers require cooling systems to help the servers run more efficiently, as well as a power infrastructure consisting of transformers, generators and transmission lines. Most of these elements require copper. The construction of a $500 million Microsoft data center near Chicago required 2,177 tons of copper, for example.
“If the projections by the hyperscalers are right, data centers constructed over the next eight years will require one million tons of copper in the U.S. alone,” Franz says. “And you’re going to have to think globally about this build-out.”
Demand for copper in electric vehicles, clean energy technology and the modernization of the U.S. electric grid is already expected to create growing deficits. The planned construction of AI data centers will push those deficits to more than six million tons by 2030, according to JPMorgan. “The question is, can miners extract enough copper out of the earth quickly enough to meet expectations for the AI build-out?” Franz asks.
Anticipating shortfalls, global mining companies are focusing on acquiring and expanding copper operations. Grupo México, a conglomerate that operates some of the lowest cost copper mines, restarted work in south Peru this past July to boost production. Similarly, the fourth largest copper producer, Glencore, is turning to operations in Argentina to double its output in the coming years.
AI, like just about any advanced technology, needs power. A lot of power. Data centers could consume as much as 9% of total U.S. electricity output by 2030, more than double current usage, according to the Electric Power Research Institute. “The demands on the grid from both data centers and electric vehicles are going to drive an increase in consumption we haven’t seen in about 20 years,” says Cheryl Frank, an equity portfolio manager for American Mutual Fund® and CGCV — Capital Group Conservative Equity ETF.
Sources: Goldman Sachs, U.S. Energy Information Administration (EIA). Estimates from Goldman Sachs as of April 28, 2024. CAGR is the compound annual growth rate. “Other” includes the impact of energy efficiency improvements and the change from categories not listed.