AI could transform fuel trading — OilPrice
Artificial intelligence tools could significantly transform global fuel trading by accelerating the analysis of market data and the search for potential deals. As OilPrice reports, the technologies already make it possible to process in seconds volumes of information that previously required the work of specialized teams of traders.
The fuel trading market has traditionally been concentrated in the trading divisions of oil and gas companies, refineries and major commodity traders. The spread of AI tools could open access to market analytics for new participants. At the same time, identical recommendations generated by similar models could cause participants to concentrate on the same transactions and amplify distortions in certain petroleum product markets.
The advantage of major traders
McKinsey analysts believe that over the next five to ten years, AI could fundamentally change the internal organization of trading companies. In their assessment, people and AI agents will work together, enabling faster results and lower costs.
McKinsey also expects that changes in the geopolitical situation will shorten cycles of market volatility and alter trade routes. Among related trends, the consultants cited further market consolidation, technological transformation, and more active investment in trading capabilities and risk management.
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The first to scale AI solutions are likely to be companies with sufficient capital: major international oil and gas corporations, trading houses and traders already working with large datasets. According to McKinsey, optimizing trade in oil and petroleum products could potentially create an additional $20 billion in value, mainly in North America and Asia.
AI for physical deliveries
Boston Consulting Group notes that energy trading will not be transformed by a single universal AI tool. Predictive models and optimization systems are more important for quantitative markets, including electricity trading and financial energy contracts.
For pipeline gas, liquefied natural gas and liquid fuel markets, BCG sees greater potential in AI agents capable of organizing operational and contractual procedures and approvals. In the physical trade of liquid cargoes, the key task is to gain a more accurate understanding of what volumes can be moved, when this can be done, to which specifications and after which approvals. To achieve this, companies need to standardize data, the rules for managing it and approaches to using models.
