• AI visibility

Guide · AI search

How can logistics software companies win more customers through AI search?

By being named, and described accurately, when shippers, carriers and third-party logistics providers (3PLs) ask AI assistants which transportation, warehouse or fleet software fits their operation. These three buyers search differently and buy differently, so one AI visibility plan will not serve all of them. The common thread is that assistants lean on independent proof, such as reviews, trade coverage and integration details, more than on vendor claims.

By Underneath Team Guide Updated

The short version

  1. Many logistics buyers are about to shop: in Peerless Research Group’s 2026 survey (opens in a new tab), 25% of companies planned to evaluate, purchase or upgrade a warehouse management system (WMS) within two years, and 12% a transportation management system (TMS).
  2. Most carriers are small: of almost 580,000 active US motor carriers, 91.5% operate 10 or fewer trucks, per American Trucking Associations (opens in a new tab) citing federal data. They research and buy without procurement teams.
  3. Large fleet deals are big and growing: Samsara (opens in a new tab) reported $1.2 billion of annual recurring revenue from customers paying $100,000 or more, up 37% in its 2026 fiscal year.
  4. Technology now decides 3PL contracts: in the 2026 Third-Party Logistics Study (opens in a new tab), “technology capability is now a decisive selection factor” for shippers choosing a 3PL, which makes 3PLs demanding software buyers.
  5. Buyers worry most about cost and fit: total cost of ownership (32%) and compatibility with existing systems (31%) topped the adoption challenges in the Peerless survey.

Which logistics companies buy this software, and what is each account worth?

Three different buyers: shippers, carriers and 3PLs. Each has its own budget, cycle and definition of value.

Shippers are manufacturers, retailers and distributors that move their own goods. They buy TMS, WMS, visibility and freight procurement tools. Adoption is uneven: a FreightWaves analysis (opens in a new tab) put TMS adoption at about 50% of large shippers but only 25% of medium-size and 10% of small ones. The same piece cites industry research that companies with a TMS typically save 3% to 12% on freight expenses. The undecided majority is the growth market.

Carriers run the trucks. The market is fragmented: American Trucking Associations (opens in a new tab) reports almost 580,000 active US motor carriers with at least one tractor, and 99.3% of them operate 100 or fewer trucks. They buy fleet management, telematics, dispatch, route optimization and safety tools, often after a short search and a demo. How carriers and brokers win freight is covered in how freight providers reach shippers through AI.

3PLs run warehouses and transport for shippers, and software is part of what they sell. The 2026 Third-Party Logistics Study (opens in a new tab), led by Penn State’s Dr. C. John Langley with NTT DATA and Penske Logistics, found 88% of shippers and 100% of 3PLs called their relationships successful, and named “a persistent gap between shipper expectations and 3PL technology capabilities” as a challenge. How 3PLs win those shippers is covered in how warehouse providers make shippers’ AI shortlists.

What a customer is worth varies by segment. At the top end, Samsara (opens in a new tab), a fleet and operations platform, reported $1.9 billion in annual recurring revenue, up 30%, and a record 13 deals worth $1 million or more in new annual contract value in one quarter. SaaStr’s analysis (opens in a new tab) of the results notes Samsara ended the year with 3,194 customers paying $100,000 or more, at an average of $362K each. A small carrier pays far less, but there are hundreds of thousands of them.

Where does AI search sit in logistics software buying?

At the early research stage for all three buyers, though no public study measures logistics buyers’ AI use.

The broad trend is documented for software buyers. When the review platform G2 (opens in a new tab) polled 1,076 software buyers in March 2026, 51% said an AI chatbot, more often than Google, is where their research begins. G2 sells visibility to software vendors and its sample is not specific to logistics, so treat that as context.

Google’s results put AI answers in front of logistics buyers as well. Freight and warehouse software sits inside the most exposed category we measured: across our study of 1,248 US searches, B2B software and technology keywords brought up an AI Overview (Google’s AI summary above the results) on 96.0% of searches, the top rate among eight industries. In our Reddit study, 35.4% of AI Overviews on B2B software searches cited a Reddit thread. Logistics has active practitioner communities, so we infer that driver, dispatcher and warehouse discussions can feed those answers.

The buyers are busy and open to new tools. In the Peerless survey, 26% of respondents said they now use AI, up from 19% a year earlier, and 29% were evaluating it. Buyers who adopt AI in operations, we infer, are also likely to use AI assistants to research it.

Which questions do shippers, carriers and 3PLs ask?

Different questions for each buyer: fit and integration for shippers, cost and compliance for carriers, client-facing capability for 3PLs. We wrote the example prompts below to show how each logistics buyer might phrase a question; they are not observed data.

BuyerIllustrative prompt
Shipper“What’s the best TMS for a mid-sized manufacturer shipping LTL and truckload across the US?”
Shipper“Which WMS integrates with NetSuite and handles ecommerce returns?”
Carrier“Best fleet management software for a 25-truck company, with ELD and dashcams?”
Carrier“Samsara vs Motive for a small fleet: which is cheaper over three years?”
3PL“Which WMS do multi-client 3PL warehouses use for billing by customer?”
3PL“What visibility tools can a 3PL offer shippers as a customer portal?”
Any“Alternatives to our current route optimization software that work with Microsoft Dynamics?”

A question about a TMS or a fleet tool does not stay a single search. Google says AI Overviews and AI Mode may use a “query fan-out” technique (opens in a new tab) that splits it into subtopics, and OpenAI says ChatGPT search rewrites a question (opens in a new tab) into narrower, targeted queries. In our hidden-searches study of 80 buyer questions, ChatGPT searched for a specific feature in 47.5% of its answers and for reviews or ratings in 46.2%. For logistics software, features like electronic logging, carrier integrations and multi-client billing are exactly what those searches would look for, we infer.

How does an AI answer become a signed logistics software deal?

By different routes: self-serve demos for carriers, formal evaluations for shippers, and partner-led deals for 3PLs.

Carriers: answer, demo, contract. A small fleet owner asks an assistant for the best tool for their size and budget, gets three or four names, and books demos. Without a procurement team, the path from answer to sale can be short. We infer that the AI answer carries more weight here than in enterprise deals, because fewer people check it.

Shippers: answer, longlist, evaluation. A logistics director uses AI research to frame the market before a formal selection. The Peerless survey shows how cautious that can be: the share of respondents holding off on software investments rose that year, up from 34% in 2025. The vendors named during research are the ones invited when the budget opens. Procurement professionals often sit in on selections like this, and how they vet vendors with AI is covered in selling procurement software to RFP buyers.

3PLs: answer, pilot, expansion. A 3PL picks a WMS or visibility tool it will put in front of its own clients. The 3PL study found more than half of shippers do not rebid at contract end, so a 3PL wants software it can rely on for years, and its software choices are sticky too.

Expansion is where the value compounds. SaaStr reports that 96% of Samsara’s $100,000-plus customers subscribe to two or more of its products. A customer who first met you in an AI answer is a starting point for later modules.

A fleet owner who books a demo after asking ChatGPT rarely leaves a referral trail, so freight and warehouse deals need other signals; what lost clicks mean for pipeline explains which ones.

Why does an assistant name one TMS or WMS vendor and not another?

No platform documents how it chooses; studies point to independent sources, and logistics buyers want proof of fit and cost.

Documented by the platforms. Both Google and OpenAI say their AI answers search the web and cite what they find, but neither explains how a TMS, WMS or fleet vendor gets picked over its rivals.

Observed in studies. Chen and colleagues (opens in a new tab) looked at US software questions and found AI search drew 72.7% of its sources from earned media, such as reviews and independent publications, against 45.4% for Google. When our reputation study asked assistants “Is this brand legit?”, 88.0% of the answers cited a review or complaint platform, the kind of site where a dispatcher or warehouse manager leaves a verdict.

What logistics buyers weigh. In the Peerless survey, the top adoption challenges were:

Challenge with logistics softwareShare of respondents
Total cost of ownership32%
Compatibility with existing systems31%
User acceptance30%
Integration with existing software applications29%
Lack of resources to implement and maintain28%

The return on investment also varies widely: 32% said their WMS took more than 18 months to pay back, while 39% saw a TMS pay back in six to 12 months.

Our inference. Cost, integration and payback are facts an assistant can only repeat if they are published. A reasonable expectation is that vendors with public pricing ranges, integration lists and customer results with numbers give AI answers, and buyers, more to work with. Nobody has yet tested it on freight or warehouse software.

What happens to a logistics vendor that assistants leave out?

Lost demos from small fleets and lost evaluations from shippers, though no study puts a figure on it.

  • Fragmented markets reward the named few. With 91.5% of carriers running 10 or fewer trucks, most buyers will not run a formal search. If an assistant names three tools, we infer the fourth rarely gets a call.
  • Buying windows are narrow. Only 12% of Peerless respondents planned to evaluate, buy or upgrade a TMS in the next two years. Missing that window can mean waiting years.
  • Shortlists shift between runs. Ask ChatGPT the same question five times and the names change: in our consistency study, only 25.2% of the brands it named appeared in all five runs. A WMS or TMS vendor that shows up only some of the time can lose a shipper’s evaluation without ever learning it was open.
  • Wrong facts cost deals. If an assistant misstates your carrier integrations or pricing, a buyer may rule you out before a demo; our guide to correcting wrong brand information in AI answers covers the fix.

What does GEO involve for a TMS, WMS or fleet software vendor?

It puts the proof each logistics buyer needs where assistants can find, read and repeat it. No vendor, and no agency, can make an assistant recommend a particular fleet or warehouse tool.

Generative engine optimization (GEO) means earning accurate mentions in AI answers; for a logistics software vendor it covers:

  1. Clear positioning per buyer. Separate pages for shippers, carriers and 3PLs, stating fleet sizes, freight modes and warehouse types you serve. Assistants answer specific questions; vague positioning gives them nothing to match.
  2. Integration facts in plain text. List the ERP, ecommerce, carrier, load board and electronic logging systems you connect to. Compatibility was the second-ranked challenge in the Peerless survey.
  3. Cost and payback information. Publish pricing ranges or a cost model and customer payback examples with numbers.
  4. Reviews and communities. Encourage detailed reviews from real customers on the platforms buyers use, and take part honestly in trucking and warehouse communities. See legitimate GEO versus manipulation.
  5. Trade press and associations. Coverage in logistics publications, conference talks and industry studies are the named sources assistants search for; our piece on building brand authority for AI search explains why they carry weight.
  6. Measurement across assistants. Track ChatGPT, Google AI Overviews and AI Mode, Gemini, Perplexity, Copilot and Claude, with questions for each buyer type, asked several times.

Logistics is one corner of a larger software market; how B2B SaaS companies earn revenue from AI search covers the rest of it. Legal software shows the same reliance on independent proof, with lawyers trusting what courts and independent testers say, as how legal software firms win law firms shows.

What don’t we know yet about AI search in freight and warehouse software buying?

Nobody has yet measured whether being named by assistants sells more TMS, WMS or fleet software.

  • No study of logistics buyers’ AI use. The AI-in-buying surveys cover software buyers generally, not shippers, carriers or 3PLs.
  • Interested sources. G2 sells review visibility; Samsara reports its own results; the 3PL study is sponsored by a consultancy and a 3PL.
  • Revenue effects have the thinnest support. Of the 45 studies of AI search optimization that Martinez (opens in a new tab) reviewed, the ones on traffic and conversions made up the least supported area.
  • Selection is opaque. Outside the platforms, no one knows exactly how assistants pick a logistics vendor, and the picks vary between runs and between assistants.

How should a logistics software vendor begin protecting its demo pipeline?

Ask assistants the questions your shipper, carrier and logistics-provider buyers ask, and note which vendors come back.

Write ten questions each for shippers, carriers and 3PLs, covering category, fit, cost, integrations and alternatives. Put each one through ChatGPT, Gemini, Perplexity, Copilot, Claude and Google’s AI features more than once, because the named vendors shift between runs. Record who is named, which sources are cited, and whether your integrations, pricing and customer results are described correctly. The gaps show where third-party proof is missing.

For an outside view, ask us to review how assistants describe your logistics product. We will show where AI answers place you with each buyer type, and which gaps are most likely costing you fleet demos, shipper evaluations and multi-year contracts. Separate positioning for shippers, carriers and 3PLs, public integration and cost facts, and repeated checks across assistants are what our generative engine optimization service page covers.

Frequently asked questions

Do trucking companies use AI assistants to choose fleet software?

No public study measures it. Software buyers broadly do, and with 91.5% of carriers running 10 or fewer trucks, most buy without a formal selection process.

Is a TMS buyer different from a WMS buyer in AI search?

Often the same company, but different questions. In the Peerless survey, 25% planned to evaluate a WMS within two years against 12% for a TMS.

Should logistics software vendors publish pricing?

Usually at least ranges. Total cost of ownership was the top adoption challenge, cited by 32% of respondents in the Peerless survey.

Do review sites matter for logistics software in AI answers?

Likely yes. ChatGPT searched for reviews or ratings in 46.2% of answers in our study, and AI search favors independent sources for software questions.

How fast can GEO produce demos?

Faster for small carriers than for enterprise shippers, we expect. Carriers often buy after a few demos; shippers usually run longer, formal evaluations.

Sources

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