US transportation has steadily become more efficient through advances in engine technology, infrastructure upgrades and increasingly sophisticated logistics networks.
The next wave is different. Automation is turning transportation networks into continuously optimising systems that consume less energy per unit moved, operate for longer hours, reduce labour bottlenecks and reshape demand for fuels and electricity.
Across rivers, roads, rail and air, software increasingly determines how energy is consumed and how goods move throughout the US.
Driverless trucks are hauling commercial loads in Texas, while AI is being deployed on Mississippi River tugs. Railroads are relying more on machine vision and automated inspection systems, as aviation regulators are preparing for a future in which cargo flights may operate with far less human involvement.
Viewed separately, these developments may appear incremental. Together, they point to a freight economy that is increasingly autonomous, continuously optimised and more productive.
Transportation is the largest source of energy demand in the US, accounting for around 37 per cent of total energy consumption, according to the Energy Information Administration (EIA). It also accounts for around 70 per cent of total US demand for petroleum products.
Any major overhaul of the transportation sector could therefore have far-reaching repercussions for both US and global energy markets over the next decade.
The oldest freight artery in North America — the Mississippi River — is among the newest adopters of AI.
America's inland waterways move hundreds of millions of tons of commodities annually, including fertiliser, grain, biofuel feedstocks, petroleum products and chemicals.
The Mississippi system remains one of the most energy-efficient ways to move bulk cargo, with waterborne transportation accounting for only four per cent of US transportation fuel use.
Traditionally, river navigation depended on human experience. Captains relied on local knowledge, visual observation and accumulated judgement to navigate changing river conditions. That is changing. Last year, Southern Devall installed Mythos AI's advanced pilot assist system on a commercial Mississippi River towboat, introducing machine-learning navigation to the inland waterway.
The technology monitors hazards, tracks vessels, calculates stopping distances, analyses river conditions and identifies fuel-saving strategies.
The implications extend beyond navigation.
River transportation already has a substantial energy-efficiency advantage over trucking, as tugs let buoyancy and the flow of the water do most of the work.
One gallon of fuel can currently move a one-ton cargo more than 500 miles on a barge, compared to around 60 miles on a truck, according to the US Army Corps of Engineers.
Automation promises to widen that advantage by reducing fuel waste, improving planning, minimising delays and making barge traffic more predictable.
This matters because many commodities travelling via these waterways are themselves energy-related, from crude oil, coal and fuel to biofuel inputs. Lower transportation costs can ripple through commodity markets, ultimately resulting in lower consumer prices for many energy-intensive goods and services.
The common narrative surrounding transport automation is that machines are replacing people. That is too narrow. The better way to frame it is that software is replacing inefficiency.
Idle trucks. Empty backhauls. River delays. Unnecessary fuel burn. Preventable rail slowdowns. Underutilised aircraft. These inefficiencies represent hidden energy consumption embedded throughout the economy. Automation targets those losses directly.
As transportation systems become more intelligent, freight movements can become smoother, assets can operate for more hours, maintenance can become predictive rather than reactive and logistics networks can become increasingly synchronised.
The result may be an economy capable of moving significantly more goods without a proportional increase in energy consumption.
Energy transitions are often understood as fuel transitions. But history suggests the biggest economic transformations frequently come from productivity transitions.
Steam power mattered because it multiplied human effort. Electrification dramatically increased the productivity of factories and households. Computing reduced the cost of information.
Transportation automation belongs in that lineage. From AI-assisted towboats on the Mississippi to autonomous trucks in Texas, the US is building a freight system that wastes less time, burns less fuel and extracts more output from existing infrastructure.
The most important transportation story of the next decade may not be whether trucks run on diesel, batteries or hydrogen. It may be whether they ever need to stop.
(Reporting by Gavin Maguire; Editing by Marguerita Choy and Anna Szymanski)