Embracing the automation revolution in trucking

Four emerging trends that show how automation is changing the way the trucking industry operates.

In brief

• In the face of rising costs and ongoing supply chain challenges, the trucking industry is looking to automation to create a more responsive operating model.
• Artificial intelligence (AI) has applications across the logistics sector, both in trucking and through channels that support the industry.

The trucking industry, which moves 70% of America’s goods, has been navigating a maze of challenges impacting its effectiveness and profitability. An aging workforce and a waning interest in trucking careers among younger people have exacerbated labor shortages, which in turn have increased wages and caused delivery delays. In fact, labor costs account for about 40% to 45% of overall truck operation expenses. The industry has also been battling rising maintenance costs and changing regulatory frameworks around emissions, drivers’ hours of service and other operational aspects. In response to these challenges, trucking and other logistics companies are embracing automation and artificial intelligence (AI) technologies for a variety of tasks.

Our research has shown four key trends emerging from automation and AI technologies that are revolutionizing the US trucking industry:

1. Upgrading freight handling through automation
2. Embracing AI to optimize routes
3. Improving the in-store experience through automation
4. Automating back-office processes

Three scenarios for the future of trucking

The following are three plausible scenarios that we believe could transpire in the near future within the trucking and logistics industry:

1. Accelerated adoption of automation and AI technologies

The challenges brought about by the pandemic and recent geopolitical events underscore the need to fast-track the integration of automation technologies. In addition to these advances, sustainable and green technologies also gain prominence, given the increasing emphasis on environmental responsibility. Through AI and automation, tools such as route optimization and advanced driving systems narrow the distance to full autonomy.

2. Slow and cautious adoption of automation and AI technologies

Slow and cautious adoption allows companies to build a robust ecosystem of blended operations. This approach employs automation tools, robots and AI algorithms to carry out repetitive, mundane or high-volume tasks, helping to ensure efficiency and precision while humans handle more intricate roles. However, labor costs might only barely decrease as human expertise remains essential.

3. Patchwork regulatory environment complicates technology adoption

In this scenario, trucking and logistics companies navigate diverse regulations across different regions, as well as backlash from labor unions, and factors related to technology integration. Inconsistent regulations slow down the research and development phase, and companies are reluctant to develop new solutions without being confident in the regulatory landscape they’ll be entering.

Avinash Sagar, Ankit Khatri, Deepak J. Samavedam and Syed Ahmed Ali also contributed to developing this article.