Goldman Sachs: AI and the Commodity Supercycle
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Goldman Sachs argues that artificial intelligence will propel commodity demand into a structural supercycle, primarily benefiting key industrial materials such as copper, aluminum, and lithium. The bank highlights that AI-driven electricity demand is projected to surge by 150% by 2030, consequently requiring an additional two million tons of copper. Simultaneously, the rapid construction of AI data centers and supporting power grids is expected to drive aluminum and lithium demand higher by 80% and 120%, respectively.
Goldman Sachs maintains a bullish outlook on copper and aluminum, setting target prices of $10,500 per ton and $3,200 per ton. These projections are underpinned by an anticipated widening of supply deficits through 2026. For lithium, current overcapacity is expected to clear by 2026, allowing prices to bottom out and rebound by 2027.
The overarching narrative links surging AI computing needs directly to an escalating structural deficit in critical metals. The report notes that the impact will gradually materialize between 2025 and 2030, depending heavily on the pace of AI adoption. Key identified risks include a potential slowdown in AI capital expenditure and the accelerated commercialization of substitute materials.
In terms of specific equities, Goldman Sachs recommends Freeport-McMoRan (FCX) and Alcoa (AA) with Buy ratings, setting target prices of $55 and $45, respectively. Albemarle (ALB) is rated Neutral with a target price of $120.
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