AI in the Trucking Industry: The Future of Automated Truck Transportation

AI-powered autonomous vehicles seem like they could be the next holy grail of tech: countless startups are involved in trying to bring this tech to market, and big industry players like Apple, Google, and Waymo are seemingly well on their way toward a future where human driving is an option, not a necessity.

But what about in the trucking industry?

Are we approaching a future where the AI trucking industry is the norm, and human drivers play only small parts in that ecosystem?

It’s possible. In limited testing situations, AI-powered trucks are already performing some portions of the work. Sam’s Club, Georgia-Pacific, and KBX are working with startup Gatik to trial middle-mile autonomous delivery in portions of Dallas-Fort Worth. And poultry giant Tyson Foods is working with C.R. England and Kodiak Robotics to test autonomous trucks between San Antonio and Dallas, a journey of over 250 miles.

We’re still a long ways from an AI-dominated trucking industry, but we’re seeing definite steps toward an increase in real-world use.

Pros and Cons of an AI Trucking Industry

As is often the case when discussing AI and automation, the move toward autonomous transportation and so-called AI trucks carries both tremendous potential and significant downsides.

Pros

Highly efficient: Fleets of fully autonomous trucks someday could run practically 24/7, with higher efficiency than humans could achieve.

Lowers risk of human error: Human errors like inattentiveness, drowsiness, or driving mistakes can be costly and dangerous.

Alleviates an ever-present labor shortage: In an industry that can seemingly never staff enough drivers, AI trucks could lessen the burden.

Cons

Disruption of labor: Widespread adoption of AI vehicles in trucking and freight could threaten jobs, though it could also solve a labor shortage and alleviate some of the most challenging roles.

Risks to lives and property: A fully loaded semi truck is a 40-ton missile, in a way. Imagine the kinds of accidents involving Teslas that have made the news, and then picture the damage that could’ve happened if it were a 40-ton semi, not a 2-ton sedan.

Cybersecurity concerns: Some are concerned at the prospect of cybercriminals “taking the reins” of an autonomous truck. This threat vector could lead to theft risk or worse, given that a semi truck makes a highly destructive weapon if used maliciously.

Liability and legal concerns: If an autonomous truck causes damage, who is at fault? Is anyone criminally liable if a truck kills someone?

Of course, there are points and counterpoints to nearly all these pros and cons. And ongoing tech development can (and should) be steered to mitigate the worst risks and concerns.

Trends and Innovations in Transportation Automation

Many of the trucks being tested today still have a safety driver in the cab, a human that can take over if something goes awry. But in the future, expect more and more fully driverless trucks to enter testing, and eventually regular use.

Right now it’s clear that fully driverless trucks are not ready for every segment of the shipping journey, let alone every route in the US (or abroad). Testing and real-world uses are relatively contained to small segments of predictable road.

There are also questions around the logistics of fully driverless trucks. They can’t load or unload themselves (yet). They can’t fuel up without help. They can’t react to “wild-card” real-world situations and scenarios in the same ways that human drivers can. They may struggle to navigate middle-mile and last-mile deliveries where conditions aren’t ideal.

But on the other side of that coin, AI-powered trucks and logistics systems can operate faster and at a scale that isn’t really possible with human labor alone: big-picture planning and resource allocation could greatly improve thanks to AI, even if in-the-moment decision-making isn’t quite as good.

The Future of Automated Trucking

It seems clear that we’re heading toward a future where at least some trucks in some scenarios don’t have anyone sitting behind the steering wheel. The question is how quickly these technologies will hit the mainstream, and how widespread they will eventually be implemented.

Our prediction is that the transition will be gradual, not sudden: certain routes, scenarios, or functions will get approved sooner than others, and the industry will likely have plenty of time to adapt.