This Industry Is Most at Risk of Being Replaced by AI

The American Trucking Association estimates there are approximately 3.6 million truckers — about 2 percent of the U.S. workforce today. The Census Bureau puts the total income of U.S. trucking industry workers, including the back-office logistics support, at a little more than $300 billion.

Let’s imagine for a moment that the technical hurdles to using autonomous vehicles for trucking can be surmounted and truckers are entirely replaced by autonomous vehicles. (This is unlikely in the foreseeable future, but let’s use this extreme case.)

Here is how the $300 billion currently going to workers overall might get redistributed:

• Transportation costs will decrease by one-third, which means that about $100 billion will be saved by companies that pay for transportation as a component of the cost of goods. Assuming they pass on some of these savings to the customer, businesses and the general public together will benefit to the tune of $100 billion.
• Although AI companies will earn $200 billion a year in revenue once this changeover occurs, they will have had to invest significantly to achieve this goal. Each will need to have raised billions to invest in the necessary research and development.
• Those AI companies that go about the development of autonomous vehicles for trucking in the right way will be able to provide substantial returns for investors, while other companies, whether as a result of poor timing, poor execution or poor luck, will go bust. Our estimates indicate that $1.75 trillion to $3 trillion in shareholder value will be created by autonomous-vehicle companies if they can overcome the technical and regulatory hurdles.
• At the same time, if autonomous vehicles are successful, valuations of transportation companies that are not able to make the transition will decline. Overall, there will be a net gain in shareholder value based on increased profitability of transport companies using autonomous-vehicle technology, but the wealth will shift to those with successful AI.

In this scenario, consumers collectively save billions of dollars, AI companies make billions in new revenue, and shareholders funding these AI businesses create more than a trillion dollars in wealth.

But what about the 3.6 million drivers and back-office workers that collectively lost $300 billion in annual income? They will need to find new jobs or exit the workforce.

Let’s discuss the steps business leaders can take to prepare for a future in which artificial intelligence replaces people in jobs at an accelerating rate.

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How Could AI Displace Drivers?

Currently, based on population, trucking is the largest single occupation that AI could replace.

The transition to a largely AI-operated trucking industry is likely to come in stages as the technology develops, and there are any number of scenarios possible depending on what seems feasible and profitable.

In 2018, five companies building self-driving trucks reported that all of them intended to keep a driver behind the wheel. The job would change, they noted, “to something more akin to an airplane pilot,” with drivers taking over for stretches of road that are not freeways.

Alternatively, advances in remote control are possible with high-speed 5G cellular and low-orbit satellites such as Starlink.

If vehicles can be controlled remotely, like flying a drone, then fewer drivers are needed.

If a driver needs to physically meet the vehicle at a waypoint to enter the vehicle and take control, such as when exiting a freeway to navigate a city for delivery, then more drivers are needed compared to the drone-controlled scenario — but still fewer than the scenario in which a driver is always on board.

Considering the pace of AI change, at what scale will the economy be able to absorb a displaced workforce? (That is, assuming that many truck drivers may not necessarily reskill for new roles.)

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How Can Leaders Prepare for AI Job Displacement?

If the questions of sorting the labor market may seem bigger than an individual decision-maker at a given AI company can address, that’s because they are.

However, business decision-makers should acknowledge that there are risks to the success of their AI business model that go beyond the technical challenges and that require a different type of countermeasure.

Engaging at an industry level through trade associations and other stakeholder groups to proactively develop initiatives to address the social issues connected to the adoption of AI can help.

Here are some suggestions:

• Your industry should align on a vision of what an AI future looks like — in terms of both benefits and costs and including the change in the labor market. Create the vision for the benefits you want to get from AI so that you have a reference point for how to make decisions that move toward the future you want.
• Fund measurement over time to chart the major shifts, such as gains achieved by AI and the labor-market changes (addition and reduction of jobs). This may be like tracking the incoming tsunami rather than running to higher ground, but a key model for improved decision-making starts with observing and orienting to the information you find and then moves on to determining what to do about what you have observed and acting on your decision.
• With an industry working group, develop a transparent and public-facing dashboard to track the changes. For example, in the trucking industry you might ask: How many autonomous trucks are on the road? What is their percentage of the total trucks on the road? What share of the pie is going to AI companies? How many people do the AI companies employ? What is the profile of who is employed? What programs address displaced workers, and what is their success rate?
• Engage stakeholders, including labor, academics and political leaders, in the vision of the overall economic benefits of AI, how labor transition is expected to unfold, as well as the variables that could influence the pace of change.
• Develop an academic partnership. Academics can be great partners in objectively measuring and tracking the transformation as well as formulating programs to ease the transition, but they lack the ability to implement programs the way that industry leaders can. Establish partnerships to brainstorm and systematically test solutions.
• Develop an industry and government working group to conduct experiments. Sam Altman of OpenAI cofunded an experiment on providing a universal basic income, and the Canadian government is also experimenting with it. Many other countries have a value-added tax that could redistribute the concentrated wealth AI is likely to generate. The Industrial Revolution led to trimming the work week from six days to five: Would a four-day work week be successful in redistributing the productivity dividend to knowledge workers? Researching under what circumstances the programs succeed could help scale based on success.

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Decision-Makers, Aim for a Fair AI Future

We admittedly don’t have a solution to job displacement; rather, we are encouraging leaders to engage in collectively forming a vision for where all of us want to go in our industries and as a society, tracking changes and systematically testing and learning how to steer to an outcome that is broadly beneficial for society.

To date, we see little evidence of meaningful leadership to ameliorate a dislocation in the workforce, but perhaps now is the moment for leaders to emerge and trade associations to systematically track the trajectory of AI’s transformation of their labor market and engage in programs that will steer the course to the outcome we want for society.

Excerpted from The AI Conundrum: Harnessing the Power of AI for Your Organization—Profitably and Safely by Caleb Briggs and Rex Briggs. Reprinted with permission from The MIT Press. Copyright 2024.