More and more, the first round of screening for B2B purchases is no longer done by humans, but by AI agents. Buyers throw their requirements to ChatGPT, Perplexity, or the procurement assistant built into the workflow, and let it run a round of comparisons and narrow down three to five candidates, and then proceed from this list. This means a very real thing: if an AI agent can't read you, grab your price and specs, and put you in that comparison table, you'll be swiped before any human sees you, and you'll have no idea.
How AI agents "compare prices" and "select suppliers"
Let’s break down its actual actions first. What the user usually gives is not a keyword, but a set of conditions: "Help me find customer service software that supports SSO, has SOC 2, has a monthly fee of less than NT$20,000, and can connect to Salesforce." After the AI agent receives this kind of request, it will break it down into several steps.
- Parsing conditions: Split natural language into comparable fields, such as functions, price ranges, compliance, integration, and deployment methods.
- Collection sources: Search and read various official websites, comparison articles, comment sites, and community discussions to retrieve the original text.
- Extract facts: Pull structured data from each source, such as "Starts at NT$18,000/month" "Supports SAML SSO" "Passed SOC 2 Type II".
- Table creation and sorting: Arrange each company side by side into a comparison table, sort them according to the weight that the user cares about, and return the top ones and recommendation reasons.
The key is in the third step. Instead of posting the entire page of your page to the user, the AI agent only extracts the facts it is "certain" about. It would rather leave the information blank than fill it in for you if it cannot catch it, or if it catches it but is not sure about it. You think it's smart to hide the price behind "Contact Us for a Quote," but to the agent that's just an empty column, and an empty column on a comparison chart often means you're out.
The real impact on B2B: The short list gets shorter and you’re not on it
In the past, when buyers searched by themselves, they would open more than a dozen pages and slowly flip through them. Even if you were ranked on the second page, there was still a chance of being clicked. AI agents don’t work like this. What it outputs is a list that has been narrowed down to three to five companies, with reasons for recommendation. The list is the new first impression, and often the only impression, because buyers rarely come back and ask, "Do you have any other homes?"
What makes it even trickier is that the entire process is not transparent to you. Traditionally, you can also estimate your visibility from search rankings, clicks, and inquiry volume; AI agent screening occurs within a conversation, leaving no traffic or records. Your inquiry volume is quietly declining, but you can't find the reason, because the problem lies in a link that you can't see at all.
Why your carefully optimized pages are being skipped by AI agents
Your page looks great to people, but may be a blur to agents. Some of the most common points lost:
- The price is hidden behind the "contact business": the agent cannot capture the numbers, and the comparison table is blank, making it difficult to be recommended.
- Specifications are written in pictures or PDFs: If a beautiful specification sheet is just a picture and cannot be captured in the text layer, it means it has not been written.
- Key facts are scattered across the pages: integration checklist on one page, compliance on another, SLAs on another, and it’s difficult for an agent to piece together your full picture in a single crawl.
- Only adjectives, no facts: "Industry-leading" and "high performance" are meaningless to the agent. What it wants is verifiable and specific values such as "99.9% SLA" and "supports 40 integrations."
Make the AI agent want to put you on the shortlist
The direction is actually not mysterious, it is just to write the facts you want to be compared in such a way that the machine can cleanly extract them.
- Make the price public, at least give a range and pricing logic: even if it's just "starting from NT$X, priced based on seats", it's far better than a blank slate.
- Write spec sheets in plain text, not images: let functionality, integration, and compliance be presented in readable text, and add structured markup (schema) if necessary.
- Pair each claim with a specific number or fact: Replace "very secure" with "supports SAML SSO via SOC 2 Type II."
- Create a fact page that can be read in one go: Group the most commonly compared fields on the same page and let agents capture your full picture in one go.
The AI agent will not pronounce your adjectives. It will only put the facts that can be read and verified in the comparison table; the parts that cannot be grasped are equivalent to non-existence for it.— Tenten GEO Consulting Team
First figure out how the AI agent describes you now
Before you start changing the page, do one thing first: use the purchasing prompt that real buyers will use, and ask the major AI engines to see if it mentions you, where it ranks you, and whether it is correct. This is exactly what we are chasing with Brand Radar, continuously measuring your visibility and description accuracy in AI answers, turning "you in the eyes of agents" into a visible indicator. Most customers will be surprised when they see the results for the first time: there is often a big gap between the agent’s perception of themselves and what the official website wants to convey.
The AI agent's price comparison and screening won't wait for you to be ready. It runs today and makes judgments based only on what it can read now. Instead of guessing where you missed it, it’s better to spread out the gaps and see. If you want to know how mainstream AI engines currently compare you with competing products and under what conditions you have been ignored, you can book a 30-minute GEO diagnosis and we will run it for you using your real purchasing situation.
