# How AI agents shortlist suppliers: what B2B buying agents read (2026)

> AI agents shortlist B2B suppliers by searching, reading your site and review pages, then naming vendors whose facts agree. See what they read and why.

Canonical: https://www.searchmaxxed.com/research/how-ai-agents-shortlist-suppliers
Last updated: 2026-10-27

BUYER'S GUIDE

AI agents shortlist B2B suppliers by searching, reading your site and review pages, then naming vendors whose facts agree. See what they read and why.

BH

Brenden House

Founder of Searchmaxxed. We build agentic SEO and GEO workflows that help businesses rank on Google and get named in ChatGPT, then turn that search into more customers and revenue.

PUBLISHED 27 OCTOBER 2026 UPDATED 27 OCTOBER 2026 16 MIN READ

AI agents shortlist suppliers by turning a buyer's brief into dozens of web searches. They read what comes back. Then they pull the facts into a comparison table and name the vendors whose facts they can find, check and see confirmed on other sites. Your website, your docs and the third-party pages that mention you are the raw material. If an agent can't read a fact, the fact doesn't exist for that shortlist, and most shortlists are settled before a buyer ever contacts you.

I'm Brenden House. I run Searchmaxxed, an SEO and AI SEO agency for enterprise, B2B SaaS, venture-backed, manufacturing and public-sector companies. On 27 October 2026 (AEST) I reread the help pages OpenAI, Microsoft, Google and Perplexity publish on how their tools search and fetch. Then I checked our own ChatGPT tests.

## In summary

- **Buyers already do this.**  Forrester found 94% of business buyers used AI in their buying process, and 61% use private AI tools their employer provides.
- **Each agent searches its own way.**  ChatGPT uses its own search crawler, Copilot sends short queries to Bing, and Google's AI Mode fans one question out into many searches.
- **Reading isn't citing.**  About three in four results it reads never make the answer, going by our own ChatGPT panel on 2 October 2026.
- **Third-party pages carry the shortlist.**  Agents check your claims against review sites, lists and press, and they favour vendors whose facts agree everywhere.
- **The fix is ordinary, careful work:**  readable pages for every buyer brief, facts that match across sources, and mentions on the sites agents trust.

## Do B2B buyers use AI agents to research suppliers?

Yes. It's now the default first step. Forrester's 2026 buyer research found 94% of business buyers use AI in their buying process. AI now beats every other source. Forrester says "twice as many buyers" rated generative AI above any other source, "far outpacing vendor websites, product experts, and sales" ([Forrester](https://www.forrester.com/blogs/b2b_buyers_make_zero_click_buying_number_one/)).

The tools sit inside the firewall. Forrester says 61% of business buyers use private AI tools their organisation provides. They're "four times as likely to use Microsoft Copilot as consumers" and twice as likely to use ChatGPT. For a supplier, that means Bing matters again, because Copilot searches through it.

Timing matters more than the tool. In 6sense's 2025 study of nearly 4,000 buyers, "Ninety-five percent of the time, the winning vendor is already on the Day One shortlist" ([6sense](https://6sense.com/science-of-b2b/buyer-experience-report-2025/)). The same study found buyers lean on LLMs most in the middle of the journey. Their top use is comparing vendor offerings.

| Finding | Number | Source, date |
| --- | --- | --- |
| Business buyers using AI in the buying process | 94% | Forrester, 2026 |
| Buyers using private AI tools from their employer | 61% | Forrester, 2026 |
| Stakeholders in a typical buying decision | 13 internal, 9 external | Forrester, 21 Jan 2026 |
| Deals where the winner was on the Day One shortlist | 95% | 6sense, 2025 |
| B2B buying forecast to run through AI agents by 2028 | 90% | Gartner forecast, 21 Oct 2025 |

Gartner goes furthest. It forecasts that "By 2028, 90% of B2B buying will be AI agent intermediated", with over US$15 trillion of spend flowing through agents ([Gartner](https://www.gartner.com/en/newsroom/press-releases/2025-10-21-gartner-unveils-top-predictions-for-it-organizations-and-users-in-2026-and-beyond)). That's a forecast, not a measurement. The research shift is already here, though.

## Which AI agents do buyers use, and how does each one research?

The main tools are ChatGPT, Microsoft Copilot, Gemini, Google's AI Mode and Perplexity. Each uses its own index and bot. That's why a vendor can lead in one tool and vanish in the next.

An **AI agent**  is software that takes a goal, plans the steps and uses tools like search and a browser to return a finished result. **Deep research**  is the mode that does this for a research question, then writes a cited report.

| Tool | How it finds pages | What it does with them | What shows in your server logs |
| --- | --- | --- | --- |
| ChatGPT search and deep research | ChatGPT search, which needs OAI-SearchBot access | Proposes a research plan, searches the web or chosen sites, writes a report with citations | OAI-SearchBot, ChatGPT-User |
| ChatGPT Work with cloud browser | A browser on a separate computer in the cloud | Reads pages, clicks, fills in forms, can request quotes | Not published by OpenAI |
| Microsoft Copilot and Researcher | Short queries sent to Bing | Grounds answers in Bing results plus the buyer's own work files | Bingbot (indexing) |
| Gemini Deep Research and AI Mode | Google Search, with "query fan-out" | Browses "up to hundreds of websites", plus Gmail and Drive if allowed | Googlebot, Google-Agent |
| Perplexity | Perplexity search, which needs PerplexityBot access | Searches the web, reads pages and cites them in answers | PerplexityBot, Perplexity-User |

Some details from each maker's own pages:

- **ChatGPT.**  OpenAI's help page says ChatGPT agent "is no longer available". Long, multi-step tasks moved to ChatGPT Work, and its cloud browser "can read web pages, click buttons, enter information into forms" ([OpenAI](https://help.openai.com/en/articles/20001280)). Deep research can "search the public web or specific sites, and use enabled ChatGPT apps", such as SharePoint ([OpenAI](https://help.openai.com/en/articles/10500283-deep-research)).
- **Copilot.**  Microsoft says Copilot "generates a short query based on your prompt and sends it to Bing" ([Microsoft](https://support.microsoft.com/en-us/microsoft-365-copilot/how-web-search-works-in-microsoft-365-copilot-chat-and-agents)). Researcher, its deep research agent, has a web search toggle.
- **Gemini.**  Google pitches Deep Research for due diligence, including "analyzing a company's products, funding history, team and competitive environment" ([Google](https://gemini.google/overview/deep-research/)).
- **Google AI Mode and AI Overviews.**  Google says both "may use a 'query fan-out' technique", meaning they issue "multiple related searches across subtopics and data sources" ([Google Search Central](https://developers.google.com/search/docs/appearance/ai-features)).

One deep research setting deserves attention. A buyer can restrict research to sites they name, or tell it to "Prioritize these sites, but allow full-web search". If your category's review site or analyst is on that list, your profile there is the first thing the agent reads.

## What happens, step by step, when an agent builds a shortlist?

An agent turns the brief into a plan and runs many searches. It reads what comes back, extracts the facts the brief asks for, then names and cites the vendors that fit. Vendors drop out at every step, mostly because the agent can't find or confirm something.

Here's a worked example. It's illustrative, built from how OpenAI and Google describe their tools, not a log of one real run.

A procurement lead at a 2,000-person Australian manufacturer opens deep research and types:

> Shortlist five supplier risk platforms that integrate with SAP Ariba, hold ISO 27001, keep data in Australia and suit a team of 20. Compare pricing model, implementation time and reviews.

1. **Plan.**  ChatGPT "creates a proposed research plan" the buyer can edit before it starts. Each criterion becomes something to check.
2. **Search.**  The agent breaks the brief into separate searches: the category, "best" lists, each vendor plus "SAP Ariba", "ISO 27001", "data residency" and "reviews".
3. **Read.**  It opens the vendor pages those searches return: product, integrations, trust centre, pricing, case studies. Then review sites, lists and news.
4. **Extract.**  It fills a table, one row per vendor and one column per criterion. Wherever it finds no fact, it writes "not stated" or leaves the vendor out.
5. **Check.**  It hunts for the same claims elsewhere. A certification shown only in a gated PDF loses to one stated in text and repeated on a review profile.
6. **Name.**  It returns five vendors with citations, and the buyer forwards the table to the other 12 people in the buying group.

Now picture vendor six. Its Ariba connector exists, but the only mention sits in a sales deck. Its data centre is in Sydney, but the website never says so. It might be the best product here. It still misses the list. Nothing the agent read said it fits, so as far as the shortlist goes, vendor six doesn't exist.

Our own testing shows the filter at work. We put 300 Australian agency-buyer questions to ChatGPT three times each, with search on. It pulled 17,870 search results into those 900 answers and kept 4,389 as sources. Being found is the easy part. About three in four results it reads never make the answer.

That panel is a one-day snapshot from 2 October 2026, and AI answers shift between runs.

## What does an AI agent read on your website?

An agent reads the text it can get from your HTML, plus any structured data and markdown you serve. Headings, tables and plain statements come through best. The llms.txt proposal puts the problem well: turning a web page "back into clean text is difficult and imprecise". Content that loads only through JavaScript, text inside images and gated PDFs are the usual casualties.

Here's the set of pages an agent reaches for on a typical B2B brief, and what it needs to find there:

| Page | What the agent looks for | Common reason a vendor drops out |
| --- | --- | --- |
| Product or solution page | What it does, who it suits, in one plain paragraph | Slogans with no stated use case |
| Industry or use-case page | Proof you serve the buyer's sector | One generic page for every industry |
| Integrations page | Named systems, with depth of each connector | Integrations listed only as logos |
| Security and compliance | Certifications, data location, standards, in text | Facts only in a gated document |
| Pricing page | Pricing model, what's included, what changes the quote | Nothing on how pricing works, so the agent guesses |
| Case studies | Customer type, problem, numbers, timeframe | Quotes with no figures |
| Comparison and alternatives pages | How you differ from named rivals | Left to third parties to describe |
| About page | Company facts: founded, size, locations served | Facts that differ from LinkedIn or press |

Two newer files help agents read faster:

- **llms.txt**  is a markdown file at your site's root that summarises the site and links its key pages. The proposal behind it says "thousands of sites publish an llms.txt file" ([llmstxt.org](https://llmstxt.org/)).
- **Markdown versions**  of pages strip out navigation and scripts, and the same proposal suggests serving them at the page URL with `.md` added.

Keep them in proportion. Google's guidance for AI Overviews and AI Mode says to "apply the same foundational SEO best practices" ([Google](https://developers.google.com/search/docs/appearance/ai-features)). It asks for no special file. Chrome's Lighthouse checks for llms.txt but marks a missing one "Not Applicable", since "providing the file is optional at the moment" ([Chrome for Developers](https://developer.chrome.com/docs/lighthouse/agentic-browsing/llms-txt)). Treat them as a cheap way to make your facts easier to fetch.

We run both on our own site. Searchmaxxed's [llms.txt](https://www.searchmaxxed.com/llms.txt) states what we do in two lines and links a markdown copy of every core page. Each copy names its canonical URL. Articles and service pages add a "Last updated" date, so it knows how fresh they are. Copy that pattern.

Schema helps only if it agrees. Google's AI features guide lists "Making sure your structured data matches the visible text on the page" among its best practices. Schema that claims something the page doesn't say gives an agent two facts to reconcile.

## Where else do AI agents look, and why do third-party pages matter so much?

Agents check vendor claims against review sites, "best of" lists, directories, press coverage and forums. Those pages often decide the shortlist. Why? A few trusted sites turn up in a large share of answers.

We saw this in our ChatGPT panel. Across 900 ChatGPT answers about Australian agencies, a single third-party "best agencies" site was cited in 168 of them. The next three were a second listicle, Semrush's agency directory and Clutch. If you want to be recommended, the job is getting onto the handful of pages the model already trusts.

The engines differ, too. Perplexity cited a review directory (Semrush Agencies, Clutch, DesignRush and the like) in 36 of 44 agency answers. ChatGPT did it in 20 and Claude in 15. One agency's Clutch profile had six reviews and was cited 20 times.

That second panel ran on 29 September 2026. Treat both as snapshots of a moving target, not fixed rates.

Buyers behave the same way. Forrester says AI answers "often deliver incomplete or unreliable information, creating mistrust", so buyers seek "validation from trusted sources" ([Forrester](https://investor.forrester.com/news-releases/news-release-details/forresters-2026-buyer-insights-genai-upending-b2b-buying-leaders/)). Agent and human both look past you.

For a B2B supplier, the third-party pages agents read usually include these:

- **Review platforms:**  G2, Capterra, Gartner Peer Insights, Clutch.
- **"Best X for Y" lists**  that rank for your category searches.
- **Trade press**, including interviews, product news and customer stories that name you and say what you did for whom.
- **Analyst and association pages.**
- **Partner marketplaces**, such as the SAP Store or Salesforce AppExchange.
- **Forums**, Reddit included, where practitioners compare suppliers.

Keep your own profiles current. It's quick work, and it belongs to your team rather than an agency. Earning coverage on lists and in the trade press is a different, slower job, because editors and list owners decide when you appear. That one takes digital PR and links, which is where an agency like ours spends much of its effort.

## What makes an agent name one supplier over another?

An agent names the suppliers whose facts match the brief, can be confirmed on other sites, and come from sources it trusts. Size helps less than clarity. A well-documented mid-sized vendor can beat a market leader whose pages say little.

| Factor | What the agent checks | What you control |
| --- | --- | --- |
| Fit to the brief | Does a page state the exact use case, industry, integration or standard? | A page for each real buyer brief |
| Readable facts | Can it get the fact from text, without logging in? | HTML text, tables, markdown versions |
| Agreement across sources | Do your site, profiles, press and partners say the same thing? | One fact sheet, applied everywhere |
| Third-party mentions | Do trusted lists, reviews and press name you for this category? | Digital PR, links, review requests |
| Recency | Is the page dated and current? | Updated dates, refreshed numbers |
| Access | Can its crawler fetch the page at all? | robots.txt, firewall and bot rules |

Search rankings still feed all of this. ChatGPT, Copilot, Gemini and Perplexity all start from a search index. A page that ranks in Google and Bing for a category search is more likely to reach the agent's reading list.

## Can you tell when AI agents visit your site?

Partly. Most AI crawlers and fetchers announce themselves by name in your server logs, so you can count them there. Analytics tools are far less reliable, because agent visits can look like ordinary traffic or like a bot attack.

Check robots.txt first. OpenAI says sites that block OAI-SearchBot "will not be shown in ChatGPT search answers" ([OpenAI](https://platform.openai.com/docs/bots)). Perplexity asks sites to allow PerplexityBot for the same reason ([Perplexity](https://docs.perplexity.ai/guides/bots)). Perplexity's own docs explain how to allow its bots through Cloudflare and AWS firewalls, so check yours too.

User-triggered fetches follow different rules. For ChatGPT-User, OpenAI says "robots.txt rules may not apply" because a person started the request. Perplexity says Perplexity-User "generally ignores robots.txt rules". Google lists Google-Agent for "agents hosted on Google infrastructure" acting "upon user request" ([Google](https://developers.google.com/crawling/docs/crawlers-fetchers/google-user-triggered-fetchers)).

Don't trust an "AI traffic" line in GA4 until someone checks it for bots, because agent visits and automated junk look alike in reports. Here's one enterprise B2B client's account. A client's GA4 showed AI-assistant visits jump from 354 to 6,050 in a month. Almost none of it was real. About 5,700 came in three one-hour bursts: same 1920x1080 desktop Chrome, all new users, no referrer, about 20 seconds each, landing on two pages. Real AI traffic was 385 sessions against 354 the month before, roughly flat.

The better measure is the answers themselves. Run the same buyer briefs through each tool every month and record which vendors each one names. Our guide to [AI visibility tools](https://www.searchmaxxed.com/research/ai-visibility-tools) compares the software that automates this.

## How do you become the supplier AI agents shortlist?

Make every fact a buyer's brief might ask about readable, consistent and confirmed by sites other than yours. Then keep testing real briefs to see where you drop out, and fix those gaps first. Most of it is SEO.

Here's the checklist I'd run for a B2B supplier, in order:

1. **Write down ten real buyer briefs.**  Take them from sales calls, RFPs and lost-deal notes, with the integrations, standards and constraints buyers state.
2. **Run each brief through ChatGPT deep research, Copilot, Gemini and Perplexity.**  Record which vendors it names, which pages it cites and where you're missing.
3. **Open the doors.**  Allow OAI-SearchBot, PerplexityBot, Bingbot and Googlebot in robots.txt and your firewall. Make sure Bing indexes your key pages.
4. **Put key content in the HTML.**  Product facts, tables and specs shouldn't depend on JavaScript to appear.
5. **Build pages for the briefs you want.**  Use case, industry, integration and comparison pages, each answering its question in the opening lines.
6. **State the facts procurement checks.**  Certifications, data location, security standards, implementation time, support terms and how pricing works.
7. **Write one fact sheet.**  Then make your site, LinkedIn, partner listings, review profiles and press boilerplate match it word for word.
8. **Add llms.txt**  and markdown copies of core pages.
9. **Earn third-party coverage**  on the lists, reviews and trade press agents cite for your category.
10. **Measure monthly.**  Track the answers next to enquiries and pipeline.

Our [AI search source readiness checklist](https://www.searchmaxxed.com/research/ai-search-source-readiness-checklist) goes deeper on steps 6 to 9. For ChatGPT specifically, see [how to rank in ChatGPT](https://www.searchmaxxed.com/research/how-to-rank-in-chatgpt).

## Where does Searchmaxxed fit?

Searchmaxxed is an SEO and AI SEO agency for enterprise, B2B SaaS, venture-backed, manufacturing and public-sector companies. We do technical SEO, content, link building, digital PR, GEO, AEO and LLM SEO. The aim is simple: rank in Google and get named in ChatGPT, Copilot, Gemini, Perplexity and Google's AI answers when your buyers research.

Here, that means three things. We build and fix the pages agents read, in clean HTML with matching schema, llms.txt and markdown versions. We make your facts agree. And we earn the links and press coverage that put you on the lists agents trust when they build a shortlist for your category.

| Package | Who it suits | What it includes |
| --- | --- | --- |
| Growth System | A company growing in one or two markets | 30 page releases a month, work on up to 4 existing pages, one qualified link action a month, AI visibility tracking |
| Agentic Search Engineering | A crowded category or national market | 50 page releases a month, comparison, industry and integration page families, digital PR and link campaigns, AI answer tracking across ChatGPT, Gemini, Perplexity and AI Overviews |
| Custom & Enterprise | Several brands, several markets or a large site | Dedicated engineering, custom reporting and original first-party research |

A page release is an approved new page or a substantial rebuild of one. Integration and comparison page families matter most here, because B2B briefs so often name an integration or a rival. Our [AI search optimisation service](https://www.searchmaxxed.com/services/ai-search-optimization) sets out the full scope, and our [enterprise SEO](https://www.searchmaxxed.com/services/enterprise-seo) page covers large, multi-market sites.

Here's how we do it. We build on a website you own, our Agentic Website. AI agents pull your Search Console and GA4 data, read the Google results and check what AI answers say about you and your competitors. That feeds the Managed Search Loop, which shows which page, fix or link should win the most enquiries next. We build it, check the live page and measure what changed. Off your site, the Off-Page Source Layer builds the links, digital PR and mentions AI answers draw on.

Searchmaxxed's work has generated more than A$10 million in revenue through search for its clients.

## Is Searchmaxxed right for you?

We suit marketing and growth teams at enterprise, B2B SaaS, venture-backed, manufacturing and public-sector companies who want the work built and shipped. If you want a dashboard of AI mentions and nothing more, we're the wrong call.

| Searchmaxxed is a good fit if | Look elsewhere if |
| --- | --- |
| Your buyers research with ChatGPT, Copilot or Gemini before they call | Your sales come from a few known accounts and tenders only |
| You want pages, fixes and digital PR shipped each month | You only want to monitor AI answers; a visibility tool costs less |
| You need SEO and AI search from one team | You want a one-off schema or llms.txt fix |
| You want to own your site, repository, content and data | You want strategy advice with no changes to your site |
| You compete in a crowded or multi-market category | You need search to fill this month's pipeline on its own |

If you're in the right-hand column, a tool, a freelancer or your own team will serve you better.

## Frequently asked questions

### Will AI agents replace human buyers in B2B?

No, not on current evidence. Agents build the shortlist, and people choose from it. Forrester found buyers still seek validation from trusted people, and the typical decision involves 13 internal stakeholders and nine external influencers.

### Which AI tool do B2B buyers use most for vendor research?

Forrester's research points to ChatGPT and Microsoft Copilot. It says business buyers are twice as likely as consumers to use ChatGPT and four times as likely to use Copilot. Copilot searches through Bing, so check your Bing visibility too.

### Do I need an llms.txt file for AI agents?

It helps, but it's optional. llms.txt gives agents a short markdown map of your site. Google asks for no special file for AI Overviews, and Chrome's Lighthouse treats a missing one as not applicable. Add it once the basics are done.

### Should I block AI crawlers from my website?

Allow the search crawlers. OpenAI says blocking OAI-SearchBot keeps you out of ChatGPT search answers. Its training crawler, GPTBot, has a separate robots.txt setting, so you can block training and still appear in search.

### Does SEO still matter if buyers use AI agents?

Yes. ChatGPT, Copilot, Gemini and Perplexity all search an index before they answer. Pages that rank in Google and Bing are likelier to reach an agent's reading list. Google says its AI features rest on the same SEO foundations.

### How do I find out if AI agents recommend my company?

Run ten real buyer briefs through ChatGPT, Copilot, Gemini and Perplexity, and note which vendors and pages each one cites. Repeat monthly, because answers change between runs. Judge the trend over a quarter.

### How long does it take to get shortlisted by AI agents?

Access fixes are fast: OpenAI says robots.txt changes reach its search systems in about 24 hours. New pages wait on crawling and indexing. Third-party coverage takes longest, because editors and review sites move at their own pace. Give it a quarter before you judge.

## What should you do next?

Take three briefs your best customers would give an AI agent. Run them through ChatGPT deep research and Copilot this week, and note where you fall off. If you'd like us to fix what you find, [let's talk pricing](https://www.searchmaxxed.com/contact).

REFERENCES

1. [Forrester](https://www.forrester.com/blogs/b2b_buyers_make_zero_click_buying_number_one/)
2. [6sense](https://6sense.com/science-of-b2b/buyer-experience-report-2025/)
3. [Gartner](https://www.gartner.com/en/newsroom/press-releases/2025-10-21-gartner-unveils-top-predictions-for-it-organizations-and-users-in-2026-and-beyond)
4. [OpenAI](https://help.openai.com/en/articles/20001280)
5. [OpenAI](https://help.openai.com/en/articles/10500283-deep-research)
6. [Microsoft](https://support.microsoft.com/en-us/microsoft-365-copilot/how-web-search-works-in-microsoft-365-copilot-chat-and-agents)
7. [Google](https://gemini.google/overview/deep-research/)
8. [Google Search Central](https://developers.google.com/search/docs/appearance/ai-features)
9. [llmstxt.org](https://llmstxt.org/)
10. [Chrome for Developers](https://developer.chrome.com/docs/lighthouse/agentic-browsing/llms-txt)
11. [Forrester](https://investor.forrester.com/news-releases/news-release-details/forresters-2026-buyer-insights-genai-upending-b2b-buying-leaders/)
12. [OpenAI](https://platform.openai.com/docs/bots)
13. [Perplexity](https://docs.perplexity.ai/guides/bots)
14. [Google](https://developers.google.com/crawling/docs/crawlers-fetchers/google-user-triggered-fetchers)

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