(News Bulletin 247) – In a recent study, Goldman Sachs looked at the potential impact of the development of artificial intelligence on crude oil prices over a ten-year horizon. As a result, the positive effect on supply would clearly exceed that on demand, thus pushing prices down.

The rise of artificial intelligence (AI) has obviously multiple and sometimes dizzying repercussions. Last year, Bain & Company estimated that half of video game development could be done by generative AI in the next five to ten years, compared to less than 5% currently. McKinsey, for its part, considered that banking, high-tech and life sciences are the sectors expected to experience the most significant upheavals.

What about oil? This is not necessarily the area we think of most spontaneously. Goldman Sachs, however, looked into the subject in a note published earlier this month, noting that companies in the sector were increasingly mentioning AI during their conferences with analysts and even more than the majority of other companies. , From now on.

On the demand side, the rise of AI should only lead to modest progress. The bank estimates the impact at a maximum of 700,000 barrels per day (compared to demand of around 100 million barrels per day) over the next five to ten years, with an effect on prices of 1 to 2 dollars per barrel. This impact would essentially be linked to a “wealth effect”, that is to say that AI would increase global gross domestic product (GDP) and consequently the demand for oil.

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An impact of 5 dollars per barrel in the medium term

Over ten years, Goldman Sachs economists estimate that AI will cumulatively increase global GDP by one percentage point (compared to 2 for the OECD). By extrapolating with certain hypotheses, the elasticity of oil demand according to the evolution of GDP, the bank retains a positive impact of 200,000 to 700,000 barrels per day.

It is on the supply side that the repercussions are most notable. Goldman Sachs believes that AI will reduce logistics costs, as well as drilling costs, while improving the automation of certain processes.

“We estimate that approximately 30% of the costs associated with a new shale well could be reduced using AI, with other costs largely determined by the needs for physical products (cement, sand, fluids, etc.) which do not cannot be rationalized in any significant way”, explains Goldman Sachs. This would translate over ten years into productivity gains of 25% and a reduction in well operating costs of potentially 7%.

Oil currently struggling

Apart from costs, the bank sees other impacts. Predictive maintenance perfected by AI could, for example, reduce production downtime while engineering advances in geology enabled by artificial intelligence would expand exploitable reserves. The efficiency of oil extraction would be improved and Goldman Sachs estimates that resources could increase by 8% to 20%, or by 10 million to 30 million barrels per day.

Ultimately, Goldman Sachs quantifies the effect at around five dollars per barrel over ten years, which would more than offset the effect on demand, from 1 dollar to 2 dollars, therefore. “Overall, we believe that AI is expected to have a modest net negative effect on oil prices in the medium to long term,” concludes the American bank.

In the shorter term, Goldman Sachs has revised downwards its short-term forecast for Brent prices, seeing them fluctuate between 70 and 85 dollars per barrel. The international oil benchmark is currently trading at the bottom of this range, at $71.78 per barrel. The contract has lost 7.3% since the start of the year, weighed down recently by fears about Chinese and American demand following poor economic indicators. As well as potential production increases from Saudi Arabia, more recently.

“Chinese demand data has been disappointing, and demand in the United States and India has been weak recently,” UBS listed this week. However, the Swiss bank believes that the price of Brent will return above 80 dollars per barrel in the coming months, due to supply tensions.