When fuel prices move 40% in a year, the logistics industry’s traditional playbook stops working; carriers who built their margins around stable diesel costs and predictable routes are finding themselves exposed, and those who invested early in AI-driven platforms are not just surviving – they’re pulling away.
The numbers tell a stark story. U.S. diesel has risen by $1.69 per gallon – a 44% rise year-over-year. And, in Europe, pump prices have climbed to €2.10 per litre, a near 47.5% annual increase.
For those logistics operators running on thin margins, that is not a macro concern – it’s an existential one.
While the Organisation for Economic Co-operation and Development (OECD) warns that persistently high energy prices are eroding industrial competitiveness and threatening de-industrialization, AI-driven platforms are countering these risks by using predictive analytics and data cleansing – optimising costs through accurate demand forecasting.
By mitigating the impact of the Strait of Hormuz blockade, this approach makes the logistics of fuel distribution more secure, cost-efficient and operationally resilient.
“In a geopolitical shock like the Iran tensions, where fuel markets go haywire, our platform shifts from forecasting to real-time analytics and margin protection,” said Asparuh Koev, CEO of Bulgaria-based AI logistics firm Transmetrics, while in conversation with 150sec.
“That gives operators clear visibility into securing profitable future capacity, rejecting bad freight, and reallocating trucks before cash burn accelerates.”
The company also has operations across Europe and the Middle East. Transmetrics, in fact, leverages machine learning to transform logistics planning into a high-precision predictive science, combining human-led operations with AI to reduce environmental impact while maintaining long-term sustainability.
Prediction is no longer enough
For decades, the logistics industry’s answer to volatility was, simply, improved forecasting: feed more data into a model, sharpen prediction, plan further ahead. The Hormuz crisis, however, has exposed the limits of that approach.
As fuel prices continue to rise, the demand for traditional logistics models shrinks in favor of more efficient, tech-driven solutions. According to a 2026 study, 70% of supply chain professionals have now designated advanced predictive and prescriptive analytics as a top priority.
This shift is driven not only by a need for better forecasting, but by the necessity of understanding risk implications and identifying resolutions during major disruptions – such as the Strait of Hormuz blockade.
When a chokepoint closes and fuel costs spike within hours, historical patterns become unreliable. What carriers need is not a better forecast of a world that no longer exists, but the ability to simulate an entirely different one.
This, Koev described, is a shift from predictive to prescriptive logistics. Where traditional forecasting tells operators what is probably going to happen, AI-driven simulation tools run continuous what-if scenarios.
What does this lane look like if diesel rises another 15%? Which loads remain profitable if this corridor closes? Where should trucks be repositioned before the next price move hits?
“Transmetrics stays reliable for live optimization and ‘what-if’ scenario testing, but we cannot override human judgment when relationships or strategic survival trump the numbers,” the CEO stressed. The system maintains profitability during chaos, but it does not remove the chaos itself.
Market integration data by Gartner confirms that by the second quarter of 2026, 75% of all supply chain management vendors have been compelled to integrate AI into their platforms to meet soaring demand. This widening efficiency gap – triggered by the global fuel shock – has forced the remaining segment of the industry into a rapid implementation of AI logistics platforms in a desperate bid to ensure corporate solvency.
Empty miles and the margin filter
In the context of the current Iran conflict, traditional logistics has been reduced to a reactive game of catch-up – fixing costly errors like fuel waste after they have already hit the balance sheet.
One of the most immediate casualties of a fuel shock is the empty mile – the truck running a return leg with no load, burning diesel that, in present conditions, no invoice will cover.
Transmetrics uses real-time reverse logistics tools to scan available freight and fill return trips, converting what would otherwise be a pure cost into a revenue leg.
The cumulative effect is significant: AI-driven fleets have reduced empty miles by between 15% and 20% during the current crisis period, with a corresponding reduction in carbon emissions.
That environmental dividend is largely incidental – the primary driver is financial survival – but Koev sees the two goals as increasingly inseparable:
“I do not see efficiency and sustainability as opposing forces; they reinforce each other. Higher fuel prices make every wasted liter more painful, so our efficiency tools become even more valuable for cutting empty miles and optimizing routes, which directly lowers emissions,” he added.
Beyond the empty mile solution, AI platforms are also enabling what might be called a margin filter: the systematic rejection of low-profit loads that would, under normal conditions, still be worth taking.
With annual fuel costs up more than 40%, hauling freight that barely breaks even is no longer a volume strategy – it is a slow drain on reserves. Firms using AI to enforce margin thresholds are preserving cash that competitors are burning on no-profit hauls.
Redefining sustainability through crisis survival
The infrastructure being built to survive this crisis is not going away when it ends. The real-time telematics, fuel-burn tracking and lane-level profitability data that carriers are generating now will become the operational baseline going forward.
And, increasingly, the foundation for regulatory compliance as green mandates tighten through the end of the decade.
In fact, industry benchmarks from the first quarter of 2026, indicate that fleets utilizing these new resilience tools are 40% better prepared for the upcoming 2027-2030 international green mandates.
More broadly, the crisis is accelerating a reclassification of AI in logistics. For many operators, these tools spent years as efficiency investments; useful, yet optional. The Homuz shock has made that framing obsolete.
“I believe the current shocks will reshape logistics optimization companies by forcing a shift from ‘nice-to-have’ analytics to mission-critical decision support,” Koev said. “Firms that survive will specialize in real-time resilience, not just efficiency in calm markets, the market will favor those who can prove ROI during chaos”.
The numbers back him up: the 2026 Logistics Performance Index found that companies using AI-driven simulations maintained a 14% higher operational uptime during the peak of the Iran transit blockages – compared to those firms relying on traditional, reactive approaches.
That reframing, from efficiency tool to survival infrastructure, may be the most durable consequence of a crisis that has upended so much else.
Featured image: Cash Macanaya via Unsplash+
Disclosure: This article mentions clients of an Espacio portfolio company.
