No. AI in a TMS takes over the typing, matching and chasing that eat a dispatcher's day. The phone calls, the judgment calls and the customer relationships stay with your people.
That's the short answer. The longer one matters more if you're deciding whether AI dispatch tools are worth it for your fleet, because the value depends on which tasks move off your team's plate and which ones don't.
AI is already on a lot of dispatch desks. About 48% of fleet managers surveyed for the 2026 State of Sustainable Fleets report said they use AI, according to CCJ. Data is the sticking point. A May 2026 Fleet Advantage study found 71% of fleets named data integration as a barrier to AI. What's changing is the work inside the job, and how well it goes depends on the setup.
What AI and automation handle today
Most of what AI takes on in dispatch is repetitive work: reading, entering, matching and updating. Here's what a modern TMS can do, with examples from Tracx.
| Task |
What the software does |
| Building loads from paperwork |
Reads a rate confirmation, tender or bill of lading and fills in the load details, so nobody retypes them |
| Taking in new loads |
Pulls loads in from EDI tenders, customer systems and a dedicated email inbox |
| Suggesting driver assignments |
Weighs driver availability, location, hours of service and equipment, then suggests who should take each load |
| Planning routes |
Orders stops, plans fuel and rest breaks, and looks for backhauls to cut empty miles |
| Sending status updates |
Sends arrival, departure and delay updates to customers and your team when trucks hit set locations |
| Flagging problems early |
Spots late loads, route changes, temperature swings and count mismatches while there's still time to act |
| Checking margins |
Compares each load's margin against your own lane history |
| Answering questions |
Lets a dispatcher ask for things like driver availability or a revenue summary in plain language |
Each one saves minutes on a single load, and those minutes add up across hundreds of loads a week.
What stays with your dispatchers
AI is good at patterns. Dispatch is full of situations that don't fit one. Your team still owns:
- The final call on assignments. Software can rank drivers by hours and distance. It doesn't know that one driver needs to be home Friday, or that another does better at a certain customer's dock.
- Problems on the road. A breakdown, a closed highway or a sick driver takes a phone call and a decision, not a suggestion.
- Customers. Negotiating a rate, calming down a shipper after a late load and winning the next lane are relationship work.
- What to do about an exception. AI can flag a late load early. A person decides whether to swap drivers, call the receiver or push the appointment.
- Freight with special rules. Livestock rest and welfare decisions, fixed USPS schedules and reefer temperature calls carry real consequences, and they need someone who knows the freight.
The shift is in where the hours go. Less time on data entry and status calls means more time on the exceptions and customers that actually decide whether a load makes money.
How much time it saves
Tracx customers report saving about 30 minutes of dispatcher time per load, and Tracx estimates its automations cut manual entry by 75%.
Your number depends on how much of your day is typing today. Time one load from tender to dispatch, count the minutes spent retyping or chasing updates, and plug them into this formula:
How many dispatcher hours could you get back?
Time one load from tender to dispatch and count the minutes spent retyping or chasing updates. Enter your numbers below.
×
÷
Minutes in an hour (fixed)
=
Where AI still struggles
Be wary of any vendor who says their AI never makes mistakes. Here's where it most often needs a person to step in:
- Bad paperwork. Blurry scans, handwritten bills of lading and unusual rate confirmation layouts are where document reading slips. Someone should check what the AI filled in before the load is saved.
- Not enough history. Margin estimates built on your lane history get better with time. Tracx uses 13 months of history, so a new lane or customer starts with less to go on.
- Bad data in, bad suggestions out. If equipment records are out of date or your ELD isn't connected, driver suggestions will be off. In the Fleet Advantage study, 64.5% of fleets named inaccurate input data as a barrier.
- Confident wrong answers. An AI assistant can answer smoothly and still be wrong, so treat its answers as a starting point. Check anything that affects money or a customer.
- Doctored documents. Fraudsters can plant misleading details in paperwork, like changed payment details or pickup instructions. Confirm any change like that with a phone call to a number you already have on file
How to get good results from AI dispatch
The fleets that get the most from AI treat it like a new hire: set it up properly, give it clear rules and check its work early on.
- Clean up your records first. Drivers, trucks, trailers, customers and locations should be accurate before you switch anything on. AI suggestions are only as good as the data behind them.
- Connect your ELD. Driver suggestions need live hours of service and location. Without them, the software is guessing. Fleet Advantage found 51.6% of fleets haven't connected their telematics data to their AI tools
- Set the approval rules. Decide which suggestions a dispatcher must approve and who can override them. Write it down so every shift works the same way.
- Start with one task. Document reading on one customer's rate confirmations is a good first step. Measure the time saved, then expand.
- Track the overrides. When a dispatcher rejects a suggestion, note why. A pattern usually points to a data problem or a missing rule you can fix.
How fast will it help? Tasks like document reading and status updates can help from the first week. Anything built on your history, like margin estimates, gets better as your lane data builds up.
Where Tracx fits
Tracx was built so dispatchers spend their time on decisions instead of data entry. In practice, that looks like:
- Auto Schedule on the dispatch board, which suggests drivers for unscheduled loads based on availability, location, hours of service and equipment.
- Create Load by Document, which reads a broker or carrier confirmation PDF and builds the load.
- Trucky, an AI assistant that answers questions like "show driver availability" or "give me a revenue summary."
- 12 core automations covering load intake, routing, status updates, exception alerts, compliance and documents. See the full list on our TMS automation page.
It's also built for specialized freight, so the automations understand things like livestock welfare clocks, fixed USPS trip schedules and reefer temperature records.
Want to see what your dispatchers would stop doing by hand? Book a demo and bring one of your real rate confirmations.
Frequently asked questions
Will AI replace truck dispatchers? No. AI takes over repetitive work like data entry, driver matching suggestions and status updates. Dispatchers still handle road problems, customers, exceptions and the final call on assignments.
What dispatch tasks can AI do today? Read rate confirmations and build loads, suggest driver assignments, plan routes, send status updates, flag late or off-route loads, and answer questions about your data.
How much time does AI dispatch save? It depends on how much manual entry your team does now. Time one load from tender to dispatch, count the minutes spent retyping or chasing updates, and multiply by your weekly volume.
Can AI dispatch loads without a dispatcher? Some routine work can run automatically, like status updates, recurring contracted lanes and fixed USPS trips. For everything else, decisions about who hauls what should stay with a person, and good software lets you require approval.
Is AI dispatch worth it for a small fleet? If your dispatchers spend a big part of the day retyping paperwork and making check calls, yes. The time saved scales with load volume, so run the estimate above with your own numbers.
Sources
• CCJ: How are trucking fleets using AI? (May 6, 2026)
• FleetOwner: 2026 fleet AI study, Fleet Advantage (May 12, 2026)
• Tracx automation
• Tracxfeatures
