How AI Agents Are Changing B2B Buying for Manufacturers

An AI agent is a research tool working on your buyer's behalf, and it is already reading your website, comparing you to competitors, and deciding whether you make the shortlist before anyone at the buying company picks up a phone. For manufacturers, this changes where deals are won and lost: not in the sales conversation, but in a research session you will never see.

I've watched B2B buying behavior shift for 30+ years, and this is the fastest change I've seen. Here's what's happening, what the research shows, and what to do about it.

What is an AI agent in the B2B buying process?

An AI agent is software, like ChatGPT, Perplexity, or Claude, that a buyer instructs to research a problem, compare options, and recommend suppliers. The buyer describes the application and constraints; the agent reads whatever it can find about every vendor in the category and returns a comparison in minutes that used to take an engineer weeks.

The behavior is no longer fringe. Forrester reports that almost 95% of buyers anticipate using generative AI to support their decision and purchase process, per its State of Business Buying 2024 research. Your engineers use these tools to write code and summarize specs. Your buyers' engineers use them to evaluate you.

Here's the part that should get a manufacturing leader's attention: the agent can only recommend what it can read. Your application expertise, your tolerances, your service record, all of it counts exactly as much as the version of it that exists in extractable text on the open web. Knowledge locked in your salespeople's heads or buried in PDFs is, to an AI agent, knowledge that doesn't exist.

How much of the buying process happens before a manufacturer hears about it?

Most of it. The 6sense 2025 B2B Buyer Experience Report found that 94% of buying groups had ranked their preferred vendors before first contact, and that early favorite wins the deal roughly 80% of the time. The same research shows buyers initiate first contact more than 80% of the time, and the 2024 edition found 85% had largely established their purchase requirements before reaching out.

In our work with manufacturers, we see buyers and their AI tools eliminate 70 to 80 percent of potential vendors before a single conversation happens. The sales team never gets a swing at those deals. They never even see the pitch.

None of this should surprise anyone who's been paying attention. When Dan Tyre and I wrote Inbound Organization (Wiley, 2018), we put it this way: "Technology is going to continue to improve the ability of companies to connect to more people who want a more personal level of service. If you have a product-based or an internally based mindset, the distance between what you're doing and what people expect will dramatically increase." We were describing search engines and self-educating buyers. We were also, it turns out, describing AI agents five years before they existed. The distance we warned about is now measured in eliminated deals.

What do AI agents look for on a manufacturer's website?

AI agents extract direct answers, and they reward sites that provide them. When an agent evaluates your company, it's hunting for plainly stated facts: what you make, who you serve, what it costs to work with you, what results customers have gotten, and how your approach compares to alternatives. It pulls the paragraph that answers the question completely and cites it. It skips the site that makes it dig.

That means the things that quietly worked against you with human visitors actively disqualify you with agents. Key claims locked inside button images. Headers that say "Solutions" instead of answering a question. Case studies that say "generated amazing leads" with no number, no timeframe, no name. Pricing pages that don't exist. A human visitor might call anyway. An agent moves to the competitor whose page answered.

There's a second-order effect manufacturers consistently miss: agents also read what third parties say about you. Trade publications, industry communities, customer reviews, and yes, the sources other AI systems cite. If your company isn't present in the places your category's information comes from, you don't exist in the agent's picture of the category. Manufacturing marketing in 2026 includes earning that presence, not just publishing on your own site.

What happens to a manufacturer's website that AI tools can't read?

They lose deals they never knew existed, and the loss is invisible by design. There's no lost-deal report for a buying process you were never in. Pipeline just gets thinner, trade show leads feel softer, and leadership blames the market.

In Inbound Organization we wrote: "Many companies recognize the need to change marketing tactics, to use content, develop a digital marketing presence, and adapt to the ability of buyers to control the process. Few see it as fundamental to the operation, structure, and strategy of the entire organization." That sentence was true in 2018 and it's truer now, because the buyers controlling the process brought machines. The manufacturers treating AI visibility as a marketing tactic are repeating the exact mistake the book documented; the ones treating it as a structural question about how the whole company shows up to its market are the ones taking share.

The proof this is fixable: Exothermic Molding had 50 years of reaction injection molding expertise and a website pulling fewer than 100 visits a month with zero inbound leads. Eighteen months after that expertise became findable, structured content: 750+ monthly visits and 10 to 15 qualified inquiries a month from engineers with real programs.

How do you find out if you're being eliminated?

Run the test buyers are running. Ask ChatGPT or Perplexity what your company does, who it's for, and how it compares to the two competitors you lose to most. Grade the answers against what you'd want a serious buyer to hear. Then score your site honestly across the dimensions agents evaluate.

If the scores are ugly, that's actually the good outcome, because now the invisible problem has numbers, and problems with numbers get fixed. Where you go from there is a strategy question, not a tactics question, and that's exactly how we work.