Key information
- AI is expected to have a slightly negative net effect on oil prices over the next ten years.
- The positive impact of AI on supply will far outweigh the impact on demand, resulting in lower prices.
- Goldman Sachs estimates the overall effect at around $5 per barrel over ten years.
Goldman Sachs recently studied the potential impact of artificial intelligence (AI) on crude oil prices over a ten-year horizon. Its findings suggest that the positive effect on supply will far outweigh the impact on demand, leading to lower prices.
Rapid advancements in AI are causing significant impacts across various industries. Bain & Company predicted last year that AI could take over half of game development in the next five to 10 years, up from less than 5 percent currently. McKinsey has identified banking, deep technology and life sciences as industries poised to undergo major transformation through AI.
The oil industry’s response
Although it is not immediately apparent, the oil industry is also influenced by AI. Goldman Sachs observed that AI was increasingly mentioned in industry conferences and earnings calls, even outpacing other sectors.
On the demand side, the impact of AI is expected to be relatively modest, with a maximum increase of 700,000 barrels per day (compared to global demand of around 100 million barrels per day) over the next five years. in the next ten years. This results in a price effect of $1-2 per barrel, primarily driven by a “wealth effect,” with AI boosting global GDP and therefore increasing oil demand.
The impact on supply
Over a ten-year period, economists at Goldman Sachs predict that AI will cumulatively increase global GDP by 1 percent, while the OECD estimates it at 2 percent. Based on certain assumptions regarding the elasticity of oil demand relative to GDP growth, the bank estimates a positive impact ranging from 200,000 to 700,000 barrels per day.
The most significant impacts are expected on the supply side. Goldman Sachs predicts that AI will reduce logistics and drilling costs while improving automation. “We estimate that approximately 30 percent of the costs associated with a new shale well could be reduced using AI, with other costs largely determined by physical requirements (cement, sand, fluids, etc.) that cannot not be streamlined in any significant way,” explains Goldman Sachs. This could lead to a 25 percent productivity gain and a potential 7 percent reduction in well operational costs over ten years.
Other impacts of AI
Beyond cost reductions, the bank recognizes other impacts of AI. Improving predictive maintenance could minimize production downtime, while AI-enabled advances in geological engineering could increase exploitable reserves. Goldman Sachs expects oil extraction efficiency to improve, with resource increases of 8 percent to 20 percent, equivalent to 10 million to 30 million barrels per day.
In conclusion, Goldman Sachs estimates an overall effect of around $5 per barrel over ten years, which more than offsets the impact of $1 to $2 on demand. “Overall, we believe that AI should have a slightly negative net effect on oil prices in the medium to long term,” concludes the American bank.
Short-term outlook
In the short term, Goldman Sachs has revised its Brent price forecasts downward, anticipating prices between 70 and 85 dollars per barrel. The international oil benchmark is currently trading at the lower end of this range, at $71.78 per barrel, having fallen 7.3 percent since the start of the year. The decline is attributed to concerns over Chinese and US demand following weak economic indicators, as well as potential increases in production from Saudi Arabia.
UBS highlighted disappointing data from China and weak demand in the US and India of late. However, the Swiss bank estimates that Brent will exceed $80 per barrel in the coming months due to supply constraints.
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