At our AI forum in Atlanta last week, one of our speakers talked about how fast agents and ecommerce are changing the way buyers find and choose suppliers. I saw a version of this play out years ago, in the early days of onsite replenishment.
Customers who ordered from us every week suddenly went quiet. No complaint, no lost bid, no phone call. The orders just stopped. When we dug in, we saw something evolving more. A competitor had put someone on site, or stood up onsite replenishment, and the account was gone before we knew it was in play. The reason wasn’t a coincidence. As organizations got leaner, they were looking for ways to keep their people in the building instead of running to a branch, waiting at a counter for material, and hauling it back. Onsite replenishment gave them that. By the time the drop-off showed up in our numbers, there was nothing left to save.
What lost us those accounts wasn’t price and it wasn’t service. It was a change in how the customer wanted to buy, and we found out about it too late to respond. The buying process moved, and we were still standing where it used to be.
What’s coming with AI agents is that same silent loss, with one difference that makes it worse. With onsite replenishment, I could eventually walk into that customer’s facility and see my competitor’s rep restocking the shelves. The cause was visible once I went looking. With an agent, you won’t watch it bypass your site for another supplier. You won’t get a shot at winning the deal back. The agent will read your product data, find it wrong or incomplete, and move on to a supplier whose information is clean. You’ll never know the agent was there. The agent saw everything.
For 20 years, ecommerce in distribution meant one thing. A human went to a website, searched for a part, compared a few options, and clicked buy. Every version of that process, from paper catalogs to punch-out to modern web stores, was built around a person doing the browsing. The whole apparatus, the product photography, the merchandising, the search bar, the account login, assumes a set of human eyes on the other side of the screen.
That assumption is breaking.
AI agents are starting to do the shopping. Not recommend. Not assist. Shop. An agent gets a task from its owner, a procurement manager, a facilities director, a contractor, and it goes out and finds the part, compares specs and price across suppliers, picks a winner, and starts the purchase. No human looks at your website. No human reads your product page. No human ever sees your brand. The buyer set the intent. The machine does everything after that.
This isn’t a forecast for 2035. The pieces are already in the field. Buyers are running research through chatbots. Procurement teams are testing agents that pull quotes across suppliers. The technology to let an agent complete a purchase end to end exists now. What’s still forming is how fast your specific customers adopt it, and that timeline is not yours to control.
What the Navu Data Actually Showed
At our AI forum in Atlanta, John Greely from Navu put numbers to a shift most distributors feel but haven’t measured. More than 80% of searches that return an AI overview now end without a click to any website. Ninety percent of B2B buyers research before they ever talk to you. Half of B2B software buyers start their buying journey inside an AI chatbot, not on Google.
Read those three numbers together and the picture is clear. Fewer visits. Higher intent on the ones you get. And a growing share of buying decisions that get made before a human ever reaches your site, or without a human reaching it at all.
Greely made a second point that matters just as much. The distributors still measuring their website by raw traffic are measuring the wrong thing. Traffic volume was the right metric when the goal was getting found by as many people as possible. That goal is fading. When a smaller number of higher-intent buyers, and their agents, come to your site, every visit carries more weight than the one before it. The question stops being how many people showed up. It becomes whether the ones who did, human or machine, got what they needed.
The website’s job used to be getting found. Now the job is answering. And the thing doing the asking is increasingly not a person.
Why This Is Different from Every Ecommerce Shift Before It
Distributors have lived through disruption before. Catalogs went to websites. Phone orders went to online orders. EDI and punch-out wired us into customer procurement systems. Marketplaces showed up and took a slice of the transaction. Each of those changes moved the buyer somewhere new, but the buyer stayed human. You could still influence the decision with a relationship, a rep who knew the account, a service reputation, a clean website. The human on the other end could be persuaded, reminded, recovered.
An agent removes the human from the search entirely. It doesn’t care about your relationship. It doesn’t remember that your counter team saved the customer’s job last spring. It reads structured data, checks price and availability and spec compliance, and it decides. If your product information is incomplete, out of date, or hard for a machine to retrieve, you don’t get a lower ranking. You get skipped. The agent never surfaces you as an option, and the buyer never learns you were one.
That’s the part worth sitting with. The old failure was losing a comparison. The new failure is never being in the comparison. When a human shopped your site and left, you at least had a chance at analytics, a retargeting ad, a follow-up call. When an agent evaluates you and rejects you, there’s no bounce to measure and no cart to recover. The rejection happens inside a system you can’t see, based on data you may not know is wrong.
It’s the same trap as those onsite replenishment losses, moved into software and sped up. Back then, at least a rep could eventually notice the account had gone cold and go find out why. An agent doesn’t leave that trail. The account just quietly stops showing up in the pipeline, and the explanation lives in a data quality problem nobody flagged.
A Scenario Worth Picturing
Picture a regional electrical distributor with a solid book of business. Good branches, loyal counter customers, a website that works fine for the humans who use it. One of their larger industrial accounts brings in a procurement agent to manage routine reorders, the repeat-buy items the customer purchases every month without much thought.
The agent’s job is simple. For each item on the reorder list, find a supplier with the right spec, in stock, at a competitive price, and place the order. It checks this distributor’s site along with three others. On most items the distributor is competitive. But on a handful of SKUs, the website shows a lead time that’s three weeks stale, and on two others the spec fields are blank because that data never got filled in after a catalog update. The agent can’t confirm those items meet the requirement, and it won’t guess. It routes those lines to a competitor whose data is complete.
Nobody at the distributor sees this happen. There’s no lost bid in the CRM, no angry phone call, no RFQ that came in and went out. The monthly reorder volume from that account just slowly pace is lower than prior and. If anyone notices, the likely first assumption is pricing, and the sales team goes chasing a discount that was never the problem. The problem was three stale lead times and two empty spec fields that a machine read, judged, and acted on in under a second.
That scenario is illustrative, not a named account. But every piece of it is happening in the field right now in some form, and the failure mode is exactly the kind of thing that hides in plain sight until the numbers force the question.
What You Actually Control
None of this means the distributor is helpless. It means the point of leverage moved. It used to sit in the sales conversation and the customer relationship. A lot of it now sits in your data.
Three things decide whether an agent can find you and choose you. First, your product information must be complete and correct. Specs, dimensions, compatibility, availability, price. The stuff a human counter rep fills in from memory is exactly the stuff an agent needs on the page because the agent has no counter rep to ask. Second, that information must be structured so a machine can retrieve it cleanly, not buried in a PDF, locked behind a lead-capture form, or trapped in an image nobody tagged. Third, it must be current. An agent working from your stale availability data will quote a customer a lead time you can’t meet or skip you for a competitor who shows real stock. Wrong data doesn’t just cost you that order. It teaches the agent your site can’t be trusted, and agents don’t forget.
That’s not a marketing project. It’s an operational one. And it belongs to the same people who already own product data, inventory accuracy, and pricing discipline. The work that makes you visible to an agent is the same work that makes your counter faster, your quotes more accurate, and your customers less likely to get a surprise on a lead time. You’re not building a new capability from scratch. You’re finishing the data work most distributors have been putting off for a decade.
What Changes Monday Morning
Start by asking a question you can answer this week. If an agent searched your category today, would it find you, and would the data it found be right? Pull up your ten highest-volume SKUs and look at them the way a machine would. Is the spec information complete? Is availability accurate? Is price current? If the answer is no on your best-selling items, it’s worse everywhere else, and everywhere else is where the long tail of your margin lives.
Then look at where your product data lives. If the real answers sit in a rep’s head, a supplier PDF, or a spreadsheet nobody syncs, an agent can’t use any of it. Map the gap between what your best people know and what your website can prove. That gap is your exposure. Every item in it is a line an agent might route to a competitor because it couldn’t confirm you were a fit.
Third, change what you measure. If your website scorecard is still built on sessions and pageviews, you’re grading yourself on a test that’s being retired. Start tracking whether high-intent visits, human or machine, find complete and accurate answers. Greely’s framing is worth stealing outright. Ask what the top ten questions were that your buyers, and their agents, asked last month, and whether your site answered them.
The buyers who still show up as humans will forgive a thin product page. They’ll call the branch, and your counter team will save the day like it always has. The agent won’t call. It will read what’s there, judge it, and move on. Silently. The distributors who get ahead of this aren’t the ones with the flashiest site. They’re the ones whose information is complete, structured, and current, so the machine can trust it, and choose it.
This is the conversation we’re having at the Applied AI for Distribution Conference. If you’re trying to get ahead of the agent-driven buyer, that’s where to be. appliedaifordistributors.com
Join DSG in Birmingham: Distribution Strategy Group will bring its Applied AI for Distributors Forum to the U.K. and Europe on Oct. 15, 2026, at the National Conference Centre in Birmingham, England. The one-day event will bring together distribution executives and AI leaders to examine how distributors are putting artificial intelligence to work across sales, operations, customer service and other parts of the business. Learn more and register at Distribution Strategy Group’s AI Forum UK & EU
Share this article:
