Artificial intelligence (AI) has the potential to significantly impact oil prices in the coming years. According to a recent report by Goldman Sachs, AI could contribute to a decrease in oil prices by boosting supply. This would happen through cost reductions, improved logistics, and an increase in the amount of profitably recoverable resources.
Why This Matters
The discussion around AI’s impact on the energy sector has largely focused on the demand side, particularly in terms of the expected increase in power consumption. However, the potential negative effects on oil prices could have substantial economic consequences, especially for oil-producing countries. Members of the Organization of the Petroleum Exporting Countries and its allies, known as OPEC+, could see a decrease in income due to lower prices driven by AI advancements.
Key Insights from Goldman Sachs
According to a note from Goldman Sachs, “AI could potentially reduce costs via improved logistics and resource allocation … resulting in a $5/bbl fall in the marginal incentive price, assuming a 25% productivity gain observed for early AI adopters.” This suggests that AI could significantly cut operational costs, leading to a drop in the marginal price needed to incentivize new production.
While AI could also drive a slight increase in oil demand, Goldman Sachs expects this to be modest compared to its impact on power and natural gas demand over the next decade. They estimate that “AI would likely be a modest net negative to oil prices in the medium-to-long term, as the negative impact from the cost curve (c.-$5/bbl) – oil’s long-term anchor – would likely outweigh the demand boost (c.+$2/bbl).”
By the Numbers: The Impact of AI on Oil Production
Goldman Sachs provides specific figures to illustrate the potential effects of AI on oil production costs and reserves. For example, AI could reduce approximately 30% of the costs associated with a new shale well. Furthermore, an AI-driven 10% to 20% increase in the low recovery rates of U.S. shale could boost the country’s oil reserves by 8% to 20%, equivalent to an additional 10 to 30 billion barrels.
Current Market Context
The potential effects of AI on oil prices come at a time when the market is already experiencing volatility. Brent crude futures recently dropped by $3.51, or 4.5%, to $74.02 per barrel, marking the lowest level since December. West Texas Intermediate crude futures also fell, declining by $2.97, or 4.1%, to $70.58, the lowest price since January.
At the same time, U.S. technology companies are pursuing energy assets previously held by bitcoin miners to secure a diminishing supply of electricity. This is part of their strategy to power rapidly expanding AI and cloud computing data centers, further highlighting AI’s growing footprint across various sectors, including energy.
Conclusion
AI’s role in the energy sector is set to evolve over the next decade, with significant implications for oil prices. While AI may provide a modest boost to demand, its impact on reducing production costs and increasing recoverable resources could result in a net negative effect on prices. This potential shift poses challenges for oil-producing countries and companies, suggesting a need for strategic adaptation in an AI-driven future.
