How AI Could Upend the Secretive World of Fuel Trading
Oil Price
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Oil Price
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AI-powered tools are beginning to reshape the secretive fuel trading market, traditionally dominated by specialized desks at major oil companies and commodity traders. This transformation could democratize market access or risk destabilizing prices through crowded algorithmic trades, according to industry analysts.
The fuel trading market is expanding from an established group of specialized desks at oil majors, commodity trading houses, and refiners to AI-assisted trades.
AI could either make the sometimes opaque fuel trading a level playing field for many new entrants or break the market by overcrowding it in some trades, as Reuters columnist Clyde Russell notes in a recent commentary.
The AI boom and the race to offer and receive “actionable insights” in seconds are equally tempting for the developers of the technology, the commodity analytics firms, and the customers.
Some commodity insights providers have started to offer AI tools to help their customers spot opportunities in the fuel trading market. This momentous change comes at a time when global fuel markets are so tight that crowded trades recommended by similar AI-generated “insights” could further distort the markets of some refined petroleum products in some regions.
It is too early to say if AI would lead to opening the fuel trading industry to a much larger pool of participants than the legacy trading desks at refiners, oil majors, and commodity trading giants.
These groups of traders could increase their advantage over new entrants by using AI to collate information. Or, alternatively, AI could become so widespread in the fuel trading business that it could give new participants a level playing field.
Last year, “many players started their AI journeys while continuing to invest in data and advanced analytics. As these journeys are being implemented, there is growing conviction among industry players that AI could profoundly transform trading organizations,” analysts at McKinsey said in a report earlier this year, just as the Iran war began and took the energy markets by surprise.
The analysts expect a new era of market volatility to occur in much shorter cycles as geopolitics is changing trade patterns.
McKinsey expects three business trends to accompany the new era of market volatility: higher market consolidation, the AI transformation, and a growing appetite for investment in trading capabilities, which would lead to “higher levels of opportunity and risk management as well as new entrants.”
“In the next five to ten years, AI could dramatically change how trading organizations will look from the inside, with human and AI agents working hand in hand, not only achieving outcomes more quickly but also with lower costs,” McKinsey’s analysts wrote.
Early movers with the capital to scale AI technologies will, of course, have the advantage, and these are likely to be merchant trading houses, international oil companies, and large data-native traders, all of which seem to be performing well in the current market, according to McKinsey’s surveys and analyses.
Trading optimization in oil and oil products alone could create an additional $20 billion in value in trading, largely concentrated in North America and Asia, McKinsey’s market research showed. The McKinsey commodity trading survey from January 2026 showed that there is significant appetite for investments in trading capabilities across the energy and metals commodities.
A more recent analysis by Boston Consulting Group (BCG) of how AI is transforming energy trading showed in July that “energy trading will not be transformed by a single AI solution.”
Predictive models and optimization matter most in quantitative markets, such as power and financial energy trading, while AI agents are set to play a larger role in physical environments.
“In pipeline gas, LNG, and liquids—more physical and logistics-heavy markets—the larger opportunity lies in using agentic AI to turn operational, contractual, and approval-heavy work into structured, controlled execution,” BCG’s analysts wrote.
These findings look straightforward, but they are demanding in practice, as companies will need to standardize data integrity, governance, and model discipline, without undermining the ability of traders and analysts to innovate, the consultants noted.
In the physical liquids markets, which are less suited to pure algorithmic trading compared with the power or financial markets, the near-term prize is “gaining visibility into what can move, when it can move, under which specifications, and with which approvals,” BCG said.
By Charles Kennedy for Oilprice.com
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AI could either make the sometimes opaque fuel trading a level playing field for many new entrants or break the market by overcrowding it in some trades, as Reuters columnist Clyde Russell notes in a recent commentary.
The AI boom and the race to offer and receive “actionable insights” in seconds are equally tempting for the developers of the technology, the commodity analytics firms, and the customers.
Some commodity insights providers have started to offer AI tools to help their customers spot opportunities in the fuel trading market. This momentous change comes at a time when global fuel markets are so tight that crowded trades recommended by similar AI-generated “insights” could further distort the markets of some refined petroleum products in some regions.
It is too early to say if AI would lead to opening the fuel trading industry to a much larger pool of participants than the legacy trading desks at refiners, oil majors, and commodity trading giants.
These groups of traders could increase their advantage over new entrants by using AI to collate information. Or, alternatively, AI could become so widespread in the fuel trading business that it could give new participants a level playing field.
Last year, “many players started their AI journeys while continuing to invest in data and advanced analytics. As these journeys are being implemented, there is growing conviction among industry players that AI could profoundly transform trading organizations,” analysts at McKinsey said in a report earlier this year, just as the Iran war began and took the energy markets by surprise.
The analysts expect a new era of market volatility to occur in much shorter cycles as geopolitics is changing trade patterns.
McKinsey expects three business trends to accompany the new era of market volatility: higher market consolidation, the AI transformation, and a growing appetite for investment in trading capabilities, which would lead to “higher levels of opportunity and risk management as well as new entrants.”
“In the next five to ten years, AI could dramatically change how trading organizations will look from the inside, with human and AI agents working hand in hand, not only achieving outcomes more quickly but also with lower costs,” McKinsey’s analysts wrote.
Early movers with the capital to scale AI technologies will, of course, have the advantage, and these are likely to be merchant trading houses, international oil companies, and large data-native traders, all of which seem to be performing well in the current market, according to McKinsey’s surveys and analyses.
Trading optimization in oil and oil products alone could create an additional $20 billion in value in trading, largely concentrated in North America and Asia, McKinsey’s market research showed. The McKinsey commodity trading survey from January 2026 showed that there is significant appetite for investments in trading capabilities across the energy and metals commodities.
A more recent analysis by Boston Consulting Group (BCG) of how AI is transforming energy trading showed in July that “energy trading will not be transformed by a single AI solution.”
Predictive models and optimization matter most in quantitative markets, such as power and financial energy trading, while AI agents are set to play a larger role in physical environments.
“In pipeline gas, LNG, and liquids—more physical and logistics-heavy markets—the larger opportunity lies in using agentic AI to turn operational, contractual, and approval-heavy work into structured, controlled execution,” BCG’s analysts wrote.
These findings look straightforward, but they are demanding in practice, as companies will need to standardize data integrity, governance, and model discipline, without undermining the ability of traders and analysts to innovate, the consultants noted.
In the physical liquids markets, which are less suited to pure algorithmic trading compared with the power or financial markets, the near-term prize is “gaining visibility into what can move, when it can move, under which specifications, and with which approvals,” BCG said.
By Charles Kennedy for Oilprice.com
More Top Reads From Oilprice.com
U.S. Strategic Petroleum Reserve Falls to Lowest Level Since 1982
SpaceX Sends Starship to Orbit and Deploys 26 Starlink V3 Satellites
TotalEnergies Targets 3% Annual Oil and Gas Growth Through 2030
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