If you hang around the industry long enough, you’ll see the same themes repeat: margins are thin, markets are ugly, and the only ones really winning are the ones with better systems.

In a world where freight is often a commodity and pricing feels like a race to the bottom, the main lever left isn’t “squeezing drivers harder” or “trying to out-cheap competitors.” It’s productivity and precision, and that’s exactly where AI and modern software can move the needle.

This isn’t theory. We can see it in broker margins, public company earnings, and the way working brokers talk about their tech stacks every day.

What do margins actually look like right now?

Let’s set the stage.

DAT data shows that broker gross margins typically average 12–18%, and notes that small and mid-sized brokers have seen margins drop below 15% in a loose 2025 market where shippers are in the driver’s seat on price.

On Reddit, you see the human side of those numbers. Brokers in r/FreightBrokers venting about gross margins that are so low the volume would have to be crazy to make it worth it. Others are talking about LTL (less than truckload) being a “dead horse” because there’s no margin left unless you own the tariff.

Theme: You can’t count on fat spreads. You either get more efficient per load, or you get squeezed out.

What are brokers saying about systems and tech?

If you read r/FreightBrokers as a kind of “unfiltered ops channel,” a few patterns jump out:

• In a thread on High Margin Customers, one of the top answers: “The type with a TMS.” In other words, customers who have their own systems and data are often the ones you can do more and better business with.
• A long thread on “What TMS are you guys using?” turns into a mini case study: one broker raves that their TMS plus integrated tools was “hands down the single best investment” they’ve made besides their team.
  
  
• In a “How much do freight brokers make?” thread, another broker is blunt if the margins are low: “It doesn’t sound like you’re using TMS systems or AI systems to cover your loads with your vetted carriers.” The implication: you can’t scale revenue per head without serious tech.

For brokers and carriers with brokerage authority, the emerging consensus is:

Margin pressure + manual workflows = pain.
Margin pressure + strong TMS + AI tooling = a fighting chance.

What does ROI from AI look like in the real world?

This isn’t just about scrappy Reddit carriers and owner-operators. We’re seeing the same pattern at the large-enterprise level.

C.H. Robinson: a live example

C.H. Robinson (CHRW), the largest U.S. freight broker, has become a kind of case study in AI ROI:

• Reuters reports its shares surged 20% in a day to a record high after a profit beat “due to AI-driven efficiencies,” even as the broader freight market struggled.
• CHRW is using AI to generate quotes, schedule pickups/deliveries, and track shipments, reducing manual work and operating expenses by 12.6% year-over-year while cutting headcount by ~10.8%.
• Business Insider notes that, thanks to generative AI, CHRW increased shipments per person per day by about 40% since 2022 while boosting margins through lower expenses.

That’s textbook “do more with the same (or fewer) people.” In a flat or down market, those productivity gains are the margin.

McKinsey: early adopters vs. everyone else

McKinsey’s work on AI in supply chain and logistics has been remarkably consistent: early adopters of AI-enabled supply chain management have seen, on average:

• 15% lower logistics costs
• 35% lower inventory levels
• 65% better service levels than slower-moving competitors

That doesn’t all fall straight to the bottom line, but a chunk of it does. In a business where brokers sit at 12–18% gross margins and small carriers hover near breakeven, a 5–15% cost swing is an edge, not a rounding error.

How exactly can AI improve margins for carriers and brokers?

You don’t need a billion-dollar lab. The ROI levers are straightforward:

1. More revenue per person

AI and modern TMS tools can:

• Pre-fill lanes, rates, and carrier options so a human can quote in seconds instead of minutes.
• Auto-match loads to vetted carriers based on history, lane preference, and compliance data.
• Autocomplete booking emails, confirm appointments, and push tracking updates.

That’s the same pattern you see at the enterprise level; more loads per head without proportionally more people. For a small brokerage or carrier with a brokerage desk, that might mean a one-person team handling what used to take three.

2. Lower operating costs

AI and software can shave costs in places that quietly erode margin:

• Manual data entry: OCR + AI can grab fields from ratecons, PODs, fuel receipts, and pump them into your TMS or accounting system.
• Chasing status: Bots or automated workflows can handle “Where’s my truck?” pings and ELD/location checks, leaving humans to deal with exceptions.
• Pricing errors: AI-assisted rating (pulling historical data and accessorial patterns) can reduce the number of loads you accidentally underprice or lose money on.

McKinsey’s 5–20% logistics cost reduction estimates for AI aren’t magic; they’re just the sum of dozens of small friction points removed.

3. Better pricing and lane decisions

Brokers online repeat a simple truth: you can’t win long-term by randomly chasing freight. Tools that blend market data, historical performance, and AI can help you:

• Focus on lanes where you consistently win and earn a clean margin.
• Avoid customers or freight types that are consistently no-margin or negative.
• Spot opportunities to rebalance capacity faster than competitors.

The ROI here is less dramatic visually, but huge over hundreds or thousands of loads.

Why does adopting AI early create a competitive edge?

Three reasons:

1. Compounding productivity
   The earlier you start, the faster you build the processes, training, and data feedback loops you need to really benefit from AI. You can’t flip a switch later and expect 40% productivity gains overnight.
2. Differentiation when everyone’s cheap
   In down markets where shippers are in the driver’s seat, and broker margins are squeezed, service + speed are often what win the freight. AI-driven operations (fast quotes, reliable tracking, fewer errors) give you that edge.
3. Room to invest as the cycle turns
   When the market tightens, those already running lean with AI and solid systems can capture more volume and better yields while competitors are still fighting fires manually.

In other words, carriers and brokers who treat AI as a strategic investment now are setting themselves up to run circles around slower adopters in the next cycle.

What can small fleets and owner-operators do right now?

You don’t need a giant budget to start.

1. Get on a real TMS (even a lightweight one)

If you’re a small fleet or owner-operator with a bit of brokerage authority and you’re still living in spreadsheets and email, your ROI isn’t “AI” yet; it’s basic systemization.

Look for:

• Simple cloud TMS options aimed at small broker/carrier hybrids
• Integrations with loadboards, your accounting, and basic compliance tools
• The ability to store carrier and lane history, not just loads

2. Use AI where you already feel the pain

Good early targets:

• Quoting support: Use AI tools (or a platform like TrueNorth) that blend DAT data with your history to suggest lane rates so you’re not guessing.
• Email and document triage: Let AI summarize long email threads, extract key details from PDFs, or draft responses—you approve and send.
• Load search automation: Tools that automatically watch your key lanes and alert you when loads hit your price band.

Each small piece saves minutes that add up to another load booked, another call made, another driver supported.

3. Treat AI as a co-driver, not a replacement

Especially for tiny teams, the mindset can’t be “this will replace me”; it has to be: “This will handle the boring parts so I can focus on the decisions, relationships, and exceptions.”

Use AI to:

• Draft, not finalize
• Recommend, not dictate
• Handle routine, not judgment

That’s how you get ROI without losing control.

4. Measure something

Even in a one- or two-person shop, you can track:

• Loads per week per dispatcher/owner
• Average margin per load
• Time spent on key tasks (quoting, tracking, paperwork)

When you add AI or upgrade your TMS, watch those numbers. If they’re not improving, adjust.

The takeaway

Markets will always cycle. Margins will always move. What doesn’t change is that the most efficient operators win more often.

Early adopters of AI in logistics are already cutting logistics costs by ~15% and boosting service levels by 60%+ compared to slower competitors. In freight, where brokers hover around 14% gross margin and small carriers flirt with breakeven, that’s the difference between surviving and scaling.

You don’t need to build your own AI lab. You do need to:

• Get serious about your TMS and basic systems
• Layer AI where it obviously saves time or reduces errors
• Think of technology as a margin lever, not a toy

The carriers and brokers who make those moves now won’t just ride out the next cycle. They’ll be the ones setting the price and pace while everyone else is still asking Google how to scale past $60K a month.