AI Could Lower Oil Prices Via Improved Logistics And Resource Allocation: Goldman Sachs
On Tuesday, Goldman Sachs reportedly stated AI could lower oil prices over the next decade by reducing costs and increasing recoverable resources, boosting supply.
The bank says that AI’s impact on energy and metals has largely centered on the demand side, anticipating a rise in power demand. However, a negative effect on oil prices could reduce the incomes of producers, including OPEC+ members.
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Goldman Sachs anticipates a modest potential increase in oil demand from AI over the next decade, especially compared to the larger impact AI is expected to have on power and natural gas demand.
Goldman Sachs estimates that AI could reduce the costs of a new shale well by about 30%. Furthermore, AI-driven improvements in recovery factors for U.S. shale could potentially increase oil reserves by 8% to 20%, adding 10 to 30 billion barrels.
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Goldman Sachs said in a note, “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.”
“We believe 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),”
Notably, Brent crude oil prices have experienced significant selling pressure recently, dipping to 77.21 USD per barrel on Tuesday.
Although there has been a slight recovery from earlier lows, the overall market sentiment remains bearish.
Investors are reacting to recent data from OPEC, which indicates that 8 OPEC+ members plan to increase their production by 180,000 barrels per day. This anticipated rise in supply casts a shadow over the oil market, particularly as it coincides with weakening demand indicators from major economies.
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