Leveraging AI to Control Recruiting Costs in the Next Freight Bull Market

The freight market is turning a corner after 18-24 months of "freight recession." Optimism for recovery is growing, with expectations of rate increases in 2025 and potential long-term growth driven by the policies of the new administration. However, the last bull market in 2020-2021 serves as a cautionary tale. Fleets grappled with high turnover, inflated advertising costs, and overwhelmed recruiting teams as they scrambled to hire drivers amidst fierce competition. This time, fleets have an opportunity to be proactive, leveraging advances in AI to mitigate these challenges and keep recruiting costs under control.

The Challenges of the Last Bull Market

During the 2020-2021 freight boom, driver recruiting became a costly, reactive process. High turnover, driven by competitive sign-on bonuses and lucrative opportunities for owner-operators, forced fleets to spend excessively on advertising and add recruiters just to keep up. Many also turned to costly third-party recruiting agencies. The result? Bloated recruiting budgets and strained teams with little time to focus on retention.

This time around, it doesn’t have to be that way. The technology available today—specifically AI—offers transformative potential for fleets to optimize their recruiting processes and navigate the challenges of a tightening market with far greater efficiency.

How AI Can Transform Driver Recruiting

Many things have been said in the past year or so about the transformative power of AI and how it can shape the future. When it comes to recruiting, my personal opinion is that the human touch will continue to be there, especially in the moments of truth. Having said that, below I explore 3 concrete use cases that I believe could help not only carriers grow efficiently in the coming market, but also recruiters have a more fulfilling day to day/

1. Early Engagement: Speed and Efficiency

A large portion of hiring costs is tied to lead generation and conversion. As cost-per-lead rises in a tighter market, improving lead-to-hire conversion becomes essential. This is where AI can make a significant impact.

AI-powered virtual recruiters and chatbots can engage with driver applicants within seconds of submitting an inquiry. These tools not only generate brand awareness but also answer initial questions, qualify drivers, and schedule interviews. Speed to first contact is often the difference between securing a driver’s interest and losing them to another fleet.

Additionally, AI can handle repetitive, time-consuming tasks such as follow-ups. In the last bull market, recruiters often made up to 12 attempts per lead across calls, texts, and emails. By automating these efforts, AI ensures leads are contacted efficiently while freeing recruiters to focus on high-value tasks like relationship-building and closing hires. This approach reduces the need for large recruiting teams and allows fleets to handle increased demand without adding excessive headcount.

2. Streamlined Processing and Qualification

Driver qualification is another labor-intensive aspect of recruiting. From ordering and reviewing reports to chasing verifications, the manual workload can be overwhelming. Some carriers even maintain dedicated processing departments for these tasks.

AI can revolutionize this process. By automating report ordering and using algorithms to assess them against hiring guidelines, fleets can categorize applicants into three buckets:

• Clearly qualified

• Clearly not qualified

• Cases requiring manual review

This triage approach maintains the necessary nuance for complex cases while significantly accelerating the process for straightforward ones. The result? Faster time-to-hire and reduced reliance on manual labor, saving both time and money.

3. Retention: The Ultimate Cost-Saver

Retention is the holy grail of cost control in driver recruiting. In a market where onboarding a new driver can cost $5,000-$10,000, reducing turnover is critical. AI offers fleets a powerful tool for identifying and addressing the factors that drive churn.

Fleets already collect vast amounts of operational data—ELD logs, GPS data, CSA scores, camera footage, and more. Patterns that signal driver dissatisfaction, such as late deliveries, rejected loads, or declining safety scores, are often identified only after the fact. AI can monitor these metrics in real time, flagging potential issues early and allowing retention teams to intervene before drivers decide to leave.

While not all turnover is preventable, even modest improvements can have a meaningful financial impact. For example, reducing churn by just a few percentage points could save fleets tens of thousands of dollars annually while stabilizing operations.

Why Fleets Must Act Now

The freight market recovery presents a critical window for fleets to rethink their recruiting strategies. The lessons of the last bull market underscore the dangers of reactive hiring practices. By exploring AI-powered solutions now, fleets can position themselves to thrive in the next bull market without repeating the mistakes of the past.