For most of the past decade, the press release was the task no one in freight wanted to own. It sat near the bottom of the marketing budget, treated as an obligation rather than a strategy. Executives who would approve a six-figure trade show booth without hesitation would hesitate at 500 words crossing the wire.

That status quo shifted when machines started reading them.

A quarter-long field test by LeadCoverage found that press releases leading with a specific, economically relevant number earned 3.5 times more AI citations than releases without one. Over the quarter, the Atlanta-based go-to-market agency for freight and supply chain companies published one release per week and logged 1,058 AI citations, up from nearly zero. ChatGPT accounted for roughly 90% of those citations. The test coincided with a period when ChatGPT, Perplexity, and Google's AI Overviews were all expanding their use of retrieved web content to compose sourced answers, giving freight marketers an early read on how those systems select citations.

The implications for carriers, brokers, and 3PLs are concrete. When a shipper asks a large language model (LLM) which provider handles omnichannel distribution out of Florida, the answer arrives before anyone visits a website. The company that published a relevant number gets named. Those who did not are absent from a conversation they never knew was taking place. That shift is particularly consequential for an industry that has historically lagged other B2B sectors in digital marketing maturity, leaving many companies without established content infrastructure to draw on.

"AI Cannot Invent a Number"

The finding is more specific than a blanket directive to send more press releases. That specificity is the point. Ordinary releases centered on company announcements, personnel changes, or awards generated minimal citations. Releases built around a hard figure carried the entire result.

"AI cannot invent a number, so it cites whoever published one," said Kara Brown, CEO and co-founder of LeadCoverage, in an interview with FreightWaves.

That constraint explains the underlying mechanics. Language models generate text; they do not report. When a query requires a figure, the model retrieves a source that provided one, and wire copy is unusually accessible. Every release on GlobeNewswire follows the same structure: headline, subhead, data, and quotes. AP style, applied uniformly, turns out to be machine-readable by accident.

Brown's warning to companies sitting on proprietary data is direct.

"The companies that publish specific, useful data on a consistent schedule are the ones AI cites most, and that citation is often the first impression a prospect gets before they ever visit your website," she said. "The companies sitting on their data simply aren't getting citations, and they never see the potential prospects and deals that pass them by."

Why AI Citations Favor the Middle Market

Google was always an auction — that was the part freight marketers understood, and the part that priced most of them out.

"If you pay Google money, they will put you at the top of the answer whether or not it's organic or paid," Brown said. "If you don't pay Google, they will diminish your visibility on Google."

She describes the arrangement as mercenary. Google has advertisers to serve and a business reason to serve them. LLMs, at least for now, operate on different incentives. There is no keyword auction for a citation.

For a mid-market 3PL, broker, forwarder, or tech vendor with a specific niche, that gap represents the entire opportunity, because the traditional route is effectively closed.

"You can't compete with Old Dominion on LTL," Brown said. "They already own the search volume for LTL. Trying to outrank them on that term isn't a fight worth picking."

The window has a time limit. Brown describes the citation effect as a flywheel with a half-life: early participants accumulate weight the way compound interest does, while latecomers spend their budget fighting incumbents who started first.

"The earlier you start, the more time you have to let this half-life percolate with the LLMs," she said. "The later you start, the more you're competing with the folks that have already started."

Outspending competitors on keywords — the old escape hatch — does not exist inside an answer engine. It is a structural change, not a budget shift, and it comes as freight marketing departments are already under pressure from a prolonged freight downturn that has constrained discretionary spending across the sector.

Trade Press, Reweighted

Two figures from Muck Rack are reshaping where marketing effort should go.

About 1% of all answer engine optimization citations come directly from a press release, translating to roughly 33,000 searches per day resolved by wire copy. Separately, 27% of industry-specific searches are answered by trade publications.

The second number carries particular weight in freight, where queries are rarely generic. No one asks an LLM for a nearby dentist. They ask which 3PL runs omnichannel distribution near a Florida headquarters, and the model searches for a publication that has already answered.

Brown's recommended order of operations follows accordingly: wire first, trade press second, website third. This sequencing runs counter to the instinct of most supply chain marketers, who default to redesigning the site.

"The LLMs don't care about your website. They're not going to your website," she said. "The content on your website is important, but the order of operations is: send more press releases, get picked up by the trade media, and then make sure that you have pretty good content on your website."

The reasoning is arithmetic, not aesthetic. No model will crawl 50,000 broker websites to find the one that answers a niche question in the fraction of a second it has to respond. It will reach for the wire and the trade desk that already did the work.

The consequence for an industry that has spent a decade dismissing trade coverage as legacy media is uncomfortable. "Trade press is more important than it was a year and a half ago," Brown said.

The Index Is Where the Number Comes From

If the rule is to publish a number, the operational question is where that number originates. Brown's answer is an index, and she recommends one to nearly every company she advises.

Two structures have proven effective. The first is mode-specific, where the discipline lies in selecting a lane nobody owns.

Competing with DAT on macro rate data, for example, is a losing proposition, and the talent that built that advantage has since spread across the industry. Ken Adamo, DAT's former chief of analytics and general manager of its shipper business, joined EASE Logistics as chief strategy officer in May. "He's crushing it," Brown said.

Competing in an unclaimed mode is a different prospect entirely. ITS Logistics built its Port/Rail Ramp Freight Index into effective ownership of drayage commentary, to the point that Paul Brashier appears in the news whenever something disrupts operations at a port. Brown identifies heavy and light final mile as territory still open.

The second structure is industry-specific, and the addressable audience is smaller than most marketers expect. One LeadCoverage client derives roughly 30% of its business from steel. There are 123 steel manufacturers and distributors in the United States.

"The niche inside the niche is so small," Brown said. The program reaches 1,200 to 1,400 people per month with an index on factors driving steel transportation rates: energy prices, fuel, and disruption in the Middle East. One new customer per quarter clears the bar.

The origin story Brown returns to is Redwood Logistics, a client since 2020. Redwood maintained an internal cross-border newsletter — a straightforward rundown of numbers and shipping data built for internal use, not for outside consumption.

Brown and her team recognized an opportunity. They proposed repurposing that internal newsletter into an external index the industry could use. That concept became Redwood Mexico, which eventually brought CNBC to the company's Laredo operation for a mini-documentary.

"The PR works if you are sharing regularly with the press a point of view with an economic perspective that matters to the shipper," Brown said.

The Measurement Trap That Kills AI Citation Programs

The industry cannot yet prove the value of these programs the way a CFO would want. Attribution tracking for citations is, by Brown's own assessment, not yet reliable, and she is candid about the gap. The tooling is roughly six months old. Agencies can observe citation volume and which model delivered it, but what happens after is opaque.

"We can tell you how many times you've been cited, but we can't tell you what happens after that," she said.

A buyer might click through. A buyer might note the name, or include it in an analysis for a superior. None of that activity is visible today.

Meanwhile, the metrics that are visible appear wrong to anyone still using the old scoreboard. LeadCoverage's search impressions rose 83% during the test period. Google clicks fell, because AI answers were resolving buyer questions before a click could occur. Direct and brand traffic continued to climb — the pattern that emerges when buyers find a company through channels other than search.

Read with 2019 assumptions, that dashboard looks like failure. Brown expects that misreading to become the industry's costliest mistake.

"The most common mistake we expect to see is companies grading these programs on clicks and shutting them down right as they start working," she said. "Clicks are declining across the board. The measure that matters now is whether AI cites you when a buyer asks about your category. The source cited today is hard to unseat tomorrow, because these systems reward freshness and repetition. This is a position to claim before a competitor claims it."