Vehicle logistics has traditionally been slower to adopt new technologies than other parts of the supply chain. 

Many shippers still rely on manual data entry, email and text-based communication, and outdated workflows that cannot keep up with modern volumes.

That creates friction with customers and inefficiencies that ripple through operations.

Artificial intelligence (AI) is emerging as a helpful tool for solving these bottlenecks, automating routine work, and improving accuracy to make growth more sustainable.

1. Automating Intake

Creating a load manually on average takes about three minutes, but for more complex shipments, that time can exceed five minutes.

When multiplied across hundreds or even thousands of orders per week, those minutes turn to hours that shippers spend parsing emails, texts, and PDFs to manually create these loads in their systems. 

Those errors and delays happen more often than most teams realize.

Beyond the time investment, the process is vulnerable to human error. The industry average for data entry suggests a 95% accuracy rate with manual entry, leaving a 5% error rate. That seems decent, but that means for every 500 loads, 25 are prone to errors that can lead to negative customer outcomes.

AI-powered intake flips the script. These systems automatically extract details such as VINs, pickup and drop-off points, and dispatch notes from unstructured messages and draft loads, directly within the TMS. Shippers can then review and approve with just a single click. 

This leads to faster load creation, reduced error rates, and a more seamless workflow. Most studies show that AI is at least 99% accurate in data entry, meaning of those 500 loads, just five might have an error.

2. Enhancing Accuracy and Transparency

Manual data entry doesn’t just slow things down; it introduces inconsistencies that continue far beyond the load creation. A single incorrect VIN or mistyped address can trigger a chain reaction across the supply chain, resulting in delays, additional calls, and rescheduling.

When errors occur, they often require additional communication among shippers, carriers, and dispatchers to correct the details. In the best case, that just means wasted time, but in the worst case, it results in missed pickup or delivery windows, empty miles for drivers, and strained relationships between logistics partners. And over time, repeated issues erode trust and reliability in those networks.

AI tools mitigate these risks by cross-checking extracted data against known fields, identifying inconsistencies, and flagging them for review before a load goes live. It’s a mix of AI precision with human oversight, giving teams both speed and control.

3. Enabling Scalable Growth and Future Integration

Perhaps the biggest advantage of AI is seen when you zoom out and look at the bigger picture. The U.S. auto transport sector includes thousands of businesses, most of which are small to mid-sized operators that rely on lean teams and legacy systems. As order volumes grow, manual processes become an operational ceiling.

AI integration within TMS platforms and load boards enables a connected, intelligent supply chain. Repetitive, low-value tasks — such as intake and verification — are handled automatically, allowing staff to focus on higher-impact activities such as invoicing customers, managing drivers, and driving growth for the business. 

And this is just the basics. AI is already playing a significant role in vehicle shipments through AI-powered load matching that pairs drivers with loads tailored to their routes, equipment, capacity, and other preferences. Match that with predictive dispatching that optimizes routes to avoid predictable delays (like rush-hour traffic in Atlanta) and unfit routes with low tunnels or long detours. AI also has the power to forecast demand so carriers can align resources accordingly, 

By adopting AI for load creation today, shippers are preparing for next-generation applications that extend beyond the screen as well. 

Other industries have already introduced AI voice agencies to manage inbound and outbound calls. Since about 70% of calls from shippers are simple status checks, this technology will dramatically reduce time spent on manual phone updates, allowing both parties to stay focused on high-value work.

It’s the automatic text that every parent wants from their teenager when they arrive at their destination safely, or an update about an unexpected delay. Customers will be more satisfied while carriers are less burdened. 

The vehicle logistics industry is at a pivotal moment. AI has unlocked the ability not just to cut time and cost, but to develop smarter workflows that can scale without sacrificing quality or control.

Vlad Kadurin is the chief product and operations officer at Ship.Cars