TL;DR
Four AI systems. Same question. Four completely different answers.
On July 28, 2026, we ran a single prompt across Claude, ChatGPT, Gemini, and Perplexity, with no prior context, no memory, and no hints about who we are:
Recommend a freight broker for a mid-market manufacturer shipping 200 refrigerated loads per month in the Southeast. We need proven cold-chain experience and a dedicated account team.
It is the kind of query a vice president of supply chain might use when building a shortlist.
www.cowtownexpress.com domain, but excluded from the final shortlist
ChatGPT positioned RLS as a cold-chain specialist rather than a generalist broker that also handles refrigerated freight.
Gemini emphasized NTG’s Atlanta headquarters and Southeast lane density.
Cowtown was discovered in Claude’s research, but it was not recommended in Claude’s final answer.
The research trace suggests why. Claude found Cowtown through the company’s old domain, while the businesses that made the shortlist had stronger public signals around the exact criteria in the prompt: refrigerated volume, cold-chain specialization, Southeast coverage, and dedicated account support.
Cowtown Logistics surfaced in an independent, context-free search alongside much larger freight companies. That is meaningful evidence that the freight-specific content and discoverability foundation are working.
It also gives us a clear next improvement list:
What Cowtown needs next
Same shipper. Same freight. Same question. Four AI systems. Zero overlap in the top recommendation.
That is not simply a search-ranking problem. It is a visibility problem. And it is playing out in a channel where 73% of B2B buyers reportedly use AI tools during purchase research .
In a Searchable analysis shared with BrokerOS covering 127 logistics companies, freight brokerage recorded a median AI visibility score of just 6%, the lowest of the six logistics segments tested.
The visibility gap
I have been watching this gap widen for more than a year. What surprises me is not that brokers are invisible in AI search. It is that most do not realize it is happening, and the ones who do are not sure what to do about it.
Shippers are changing how they find freight brokers, and it is happening faster than many people in this industry want to admit.
It used to be referrals, trade shows, and cold outreach. Then Google entered the picture, and brokers with useful websites started earning inbound leads. Now there is a third channel, and it is growing quickly: AI assistants.
Procurement managers and logistics coordinators are opening ChatGPT, Perplexity, and Google AI Overviews and asking questions like:
These are the kinds of queries that used to go directly to Google. Increasingly, they are also going to AI. The answer is only as good as the content the system can find, interpret, and trust. If your website does not clearly address those questions in specific, structured language, your brokerage is less likely to appear.
A Google ranking is a position on a list. An AI citation can become part of a recommendation, sometimes one of only a few options delivered in the response. That distinction matters more than many brokers realize.
Here is where the real problem lives. I talk to freight broker owners regularly, and awareness is not the issue anymore. Most have heard of AI search. Many have even searched for AEO or GEO. A few have asked their web developer about it.
But awareness without infrastructure does not create visibility.
The same Searchable analysis found that only 14% of the freight brokers evaluated publish content monthly. Think about what that means for a broker that wants to appear in AI answers. AI engines rely on what is publicly available on the web. If your site has a homepage, an About page, a generic services page, and a contact form, there is little for an AI system to extract, trust, or cite.
To show up in an AI answer, your website needs to give the system something useful to work with:
Take a mid-sized broker running flatbed loads out of the Midwest. The company has been in business for 18 years, has relationships with 400 carriers, and knows every lane from Chicago to Dallas. But its website says, “We move freight across North America. Call us today.”
That is not enough information to support a citation. It is a brochure.
When a shipper asks ChatGPT for a flatbed broker with Midwest experience, that 18-year operation may not appear at all. A newer brokerage with a well-structured website may.
That is the execution gap: not awareness or strategy, but the absence of the right content in the right structure.
The good news is that AI search visibility is still early enough for brokers that move now to establish a stronger position. The companies appearing in AI answers today are not always the ones with the best relationships or longest track record. They are often the ones whose websites gave the AI something clear to read, trust, and cite.
That window will not stay open. As more brokers build out service pages, lane content, and structured proof points, the bar will rise. The brokers that act in 2026 can compound that advantage over the next three to five years. The ones that wait will spend that time trying to catch up.
We wrote a deeper breakdown of why most freight broker websites are not showing up in ChatGPT or Google Gemini if you want the full picture of what blocks visibility.
We have also seen the opportunity firsthand. After migrating BrokerPro.com to BrokerOS Discover and shipping semantic improvements, Google Search impressions increased 210% in under 90 days. Cowtown Logistics rebuilt its site around freight-specific content and structured service pages, and a Searchable snapshot recorded an early AI visibility score of 16%.
The Cowtown Logistics case study and BrokerPro discoverability breakdown show what the execution looks like. These results are directional rather than proof that every gain came from a single change, but they demonstrate the value of a stronger, continuously improved discoverability foundation.
Most brokers have not meaningfully updated their websites in three to five years. No new service pages. No case studies. No lane-specific content. Just the same homepage that was good enough when Google was the only major digital discovery channel.
It was not built for AI, and it shows. If that sounds familiar, the window to fix it is open now. This breakdown of freight broker website architecture is the right place to start.
The practical first step is an honest audit. Run your core service queries across ChatGPT, Claude, Gemini, and Perplexity. See who appears. Review the sources they cite. Compare what those companies have published with what your site is missing.
If you want the full framework behind that, the freight broker website structure piece breaks down what Google and AI systems actually need to understand your business.
The window is open
Many freight brokerage websites use generic language, publish infrequently, and lack dedicated service, industry, lane, and proof content. That leaves AI systems with too little specific, trustworthy information to cite when a shipper asks for a recommendation.
Not consistently. In this BrokerOS point-in-time test using the same refrigerated-freight prompt, each platform produced a different top recommendation and the lists overlapped only partially.
AI systems need clear service pages, industry and lane specificity, proof of experience, useful answers to shipper questions, strong internal links, and structured content they can interpret reliably.
No. AI answers and source selections change over time. Visibility requires ongoing measurement, content improvement, technical refinement, and repeated testing. That continuous optimization is part of BrokerOS Discover , not a one-time website project.
Start by running several important service and shipper-intent prompts across major AI platforms. Record which brokerages appear, which sources are cited, where your company is absent, and which missing pages or proof points could close the gap.
If you’re not sure where your brokerage stands in AI search, the first step is finding out. We do website and AI visibility reviews specifically for freight brokers: we look at your current site structure, run your service queries across the major AI platforms, and show you exactly what’s missing and what it would take to fix it.
Book a website and AI visibility review with BrokerOS and we’ll walk you through where you stand and what to do next.
Keep reading
Most CRMs are built for software sales pipelines. Freight brokerages have carriers, shipper prospects, onboarding flows, and TMS data that do not fit that model — and adapting a generic tool to freight usually creates more problems than it solves.
Shippers are increasingly using ChatGPT and Google Gemini to find freight brokers. Most brokerage websites are invisible to those tools — not because they do not deserve to show up, but because they are not built for it.
This BrokerOS Web release expanded shared LocalBusiness schema coverage, improved maintenance workflows for synced sites, and made the news hub clearer and easier to keep current.
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