Aramco Deploys Industrial AI as Strait of Hormuz Crisis Threatens Fuel Supplies
The company warns gasoline and jet fuel inventories are falling rapidly amid prolonged supply disruptions.
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[Image source: ChetanJha/MITSMR Middle East]
With ongoing geopolitical tensions disrupting global energy supplies, Saudi Aramco warns of tightening fuel supplies. At the same time, the company is investing in industrial artificial intelligence to improve the efficiency of its refineries.
Speaking to analysts during the company’s first-quarter earnings call, Aramco CEO Amin Nasser warned that prolonged disruption in the Strait of Hormuz could delay the oil market’s recovery until 2027. He said the market was already losing nearly 100 million barrels of oil a week as tanker traffic through the strategic waterway sharply declined.
“The longer the supply disruptions continue, even for another few more weeks, it is going to take a much longer time for the oil market to rebalance and stabilize,” Nasser said, adding that only two to five vessels were currently crossing the strait daily compared to roughly 70 under normal conditions.
Nasser also said that global supplies of gasoline and jet fuel could drop to “critically low levels” before the summer travel season if the disruption persists. Aramco reports that refined fuel stocks are falling faster than crude oil stocks, raising concerns about shortages, inflation, and broader economic instability.
In response, Aramco is expanding its use of industrial AI with a new refinery optimization platform developed with Emerson. This system integrates Emerson’s Aspen Hybrid Models into Aramco’s refinery planning, which is called one of the world’s largest multi-site refinery optimization systems.
The system combines engineering models, industrial AI and real-time plant data to improve refinery planning accuracy, even as conditions change. Traditional refinery models often struggle to adapt to changes in feedstock quality, production rates, and rapidly shifting market conditions. These vulnerabilities become more pronounced during supply disruptions.
According to the company, the AI platform has achieved prediction accuracy levels of up to 98.5% in key refinery units.
This move is part of a broader trend in the Middle East energy sector, where national oil companies are starting to see industrial AI as a core operational capability. For refiners facing volatile supply chains and geopolitical uncertainty, AI-driven optimization is emerging as an important tool to improve flexibility, performance, and planning reliability in large-scale operations.
