Can AI agents fill out demo request forms?

Some agents can fill in forms when the user allows it, but most buyers use agents for research, not for contacting vendors. The agent's job is usually to build a shortlist. If your site requires a demo request just to see pricing or basic features, the agent will often report those facts as unavailable rather than submitting a form on the buyer's behalf.

Should I block AI agents from my website?

For public marketing pages, blocking agents mostly removes you from comparisons buyers ask them to run. Protect private areas, accounts and gated assets with authentication, as you would for any visitor. For public pricing, features and security summaries, being readable is an advantage. Check your CDN's bot settings, since some block automated browsers by default.

Do AI agents read structured data or schema markup?

Agents read whatever is on the page, and some may use structured data where it exists, but there's no evidence that schema determines how agents compare vendors. Ahrefs' 2026 test found no citation lift from schema in ChatGPT. Use standard markup as hygiene, and put the facts that matter in visible text and HTML tables.

How is ChatGPT shopping relevant to B2B companies?

ChatGPT's shopping features are aimed mainly at consumer products, but they show where discovery is heading: the assistant compares options and presents a shortlist with prices and specs. B2B buyers are using agents for the same kind of comparison. The lesson for B2B is to publish comparable facts, such as prices, plans and specifications, in a form any assistant can read.

Will AI agents replace B2B sales conversations?

Not for complex purchases. Agents shorten the research phase, so buyers may arrive at a sales call with a shortlist already built and fewer basic questions. That shifts sales conversations toward fit, implementation and negotiation. Vendors that make research easy are more likely to be on the shortlist that reaches that conversation.

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SEO & AI search

How ChatGPT Shopping and Agent Mode Change B2B Product Discovery

AI agents and product discovery: how ChatGPT agent mode researches B2B vendors, and what your pricing and features pages need so an agent can finish the job.

By Mehdi HassanOct 29, 20269 min read

The short answer

AI agents change product discovery by doing the research for the buyer: they visit vendor sites, read pricing and feature pages, compare options and report back a shortlist. For B2B companies, that means your pricing, features, integrations and security facts must be readable as plain text, in predictable places, or the agent will report what it could find about your competitors instead.

Key takeaways

Agents browse your site like a fast, literal researcher. If a fact isn't in readable text, it doesn't exist to them.
Pricing is the page agents need most. Hidden or contact-only pricing gets reported as unknown.
Put features, integrations, limits and security answers on predictable, linked pages in HTML tables.
Forrester found 94% of business buyers used generative AI in their last purchase. Agents extend that habit.
Agent-friendly pages are just clear pages. Google says no special AI formats are needed.

Part of How to Get Your Brand Recommended by ChatGPT

How do AI agents change B2B product discovery?

AI agents change product discovery by moving the research step from the buyer to software. Instead of reading ten vendor sites, a buyer can ask ChatGPT's agent mode or a similar tool to "find three onboarding tools for a 20-person SaaS team under $500 a month, compare their integrations and summarize the security terms." The agent searches, opens each site, clicks through pricing and docs, and returns a comparison.

That's a step beyond AI search answers. A search answer quotes what it finds in an index. An agent actually navigates your site, so it can be stopped by the same things that frustrate human buyers: pricing behind a form, features hidden in tabs, a cookie wall or a page that only renders after scripts run. Buyers already lean on AI heavily; Forrester found 94% of business buyers used generative AI in their last purchase. This guide is part of our hub on getting your brand recommended by ChatGPT, and focuses on what agents need from your site.

What is agentic search, and how is it different from AI search answers?

Agentic search is when an AI system takes several actions on the web to complete a task, rather than answering from one search. It plans steps, visits pages, follows links, reads tables and sometimes fills in forms, then reports a result. AI search answers retrieve and summarize. Agents retrieve, navigate and decide.

	AI search answer	AI agent task
What the user asks	A question	A task with criteria
What the AI does	Searches and summarizes sources	Searches, opens sites, clicks, reads, compares
How deep it goes on your site	Usually one page	Several pages: pricing, features, docs, security
What it returns	An answer with citations	A shortlist, comparison or recommendation
What stops it	Content it can't index	Content it can't reach, read or interpret

For a B2B vendor, the difference is depth. An agent comparing three vendors will look for the same facts on each site, often in the same order. If your competitor answers in a clear pricing table and you answer "contact sales," the comparison will say so.

What does an AI agent need from your pricing page?

An AI agent needs your pricing page to state prices, plan names, what each plan includes and the main limits, in readable text or an HTML table. Pricing is usually the first fact a buyer's task asks for, because budget is the first filter. A page that hides it doesn't stop the agent. It just records you as unknown or expensive.

Prices or a pricing model in text: "$49 per seat per month" or "from $500 a month, billed annually." Not inside an image or a slider that only works with a mouse.
Plan contents in a table: rows for the features and limits buyers compare, such as seats, usage, integrations, support and SSO.
Billing terms: monthly or annual, minimum term, free trial, cancellation.
Enterprise path: if the top tier is custom, say what triggers it and what it typically adds.
A visible updated date, so agents and buyers know the numbers are current.

The conversion data supports the same work for human visitors. TripleDart's 2026 study of 28 B2B SaaS companies found pricing comparison posts converted at 1.5%, one of only two blog formats that produced leads. Clear pricing serves agents and buyers alike.

What does an agent need from features, integrations and security pages?

An agent needs features, integrations and security answers on predictable, linked pages, stated as specific facts. Tasks usually include criteria like "integrates with HubSpot," "SOC 2 compliant" or "supports SSO." The agent will look for a yes or no. Marketing language without the fact reads as a no.

Page	Facts an agent looks for	Format that works
Features	What the product does, plan availability, limits	Headed sections with one feature each, plus a comparison table
Integrations	Named tools, depth of integration, plan required	A list or table of named integrations, each with its own page if important
Security and trust	Certifications, data location, retention, AI training use	A trust page with direct answers and linked documents
Use cases	Who it's for, team size, industry	One page per use case with a clear first sentence
Comparisons	How you differ from named alternatives	Honest comparison pages with tables and a verdict

For AI products in particular, explaining what the product actually does, in plain language, is the hardest and most important part. Explaining AI products on your website covers how to write it. A dedicated FAQ on each key page also helps, because agents and assistants can lift a direct question-and-answer pair; see FAQ sections that get cited.

How do you make a website easy for AI agents to navigate?

Make your site easy for agents by making it easy for a fast, literal human: predictable navigation, clear link text, content in HTML, no walls in the way. There's no special agent format to adopt. Google's own guidance for its AI features calls llms.txt, AI-specific markup and content chunking unnecessary, and the same principle applies to agents.

Use predictable URLs and navigation
Link Pricing, Features, Integrations, Security and Docs from the main navigation or footer, with those exact words. Agents follow labels.
Server-render key content
Make sure pricing, features and security facts are in the HTML the server sends, not loaded later by scripts or behind click-to-expand tabs.
Remove walls on public facts
Don't gate pricing, feature lists or security summaries behind forms. Gate the detailed documents if you must, but publish the summary.
Keep consent banners light
A cookie banner that covers the whole page and needs several clicks can block an agent's view of the content. Use a compliant banner that doesn't hide the page.
Write descriptive link text
"See SOC 2 report summary" tells an agent where to go. "Learn more" doesn't.
Test with an agent yourself
Give an agent a realistic buyer task that includes your company and read its report. Every "couldn't find" is a fix.

For example, suppose an agent compares three vendors for a buyer

For example, suppose a buyer asks an agent: "Compare three customer feedback tools for a 50-person SaaS company. I need Slack and Jira integrations, SSO, and a budget under $1,000 a month."

The agent visits three hypothetical vendors. Vendor A has a pricing table with seat limits, an integrations page listing Slack and Jira, and a security page that says SSO is on the Business plan. Vendor B lists integrations but says "contact us" for pricing. Vendor C has everything, but the pricing loads inside a script-driven widget the agent can't read.

The agent's report recommends Vendor A, notes Vendor B's pricing as unknown, and says it couldn't verify Vendor C's price. Vendor C may be the best product. It lost the comparison anyway. This is an illustration, not a real test.

Should you design for AI agents or for human buyers?

Design for human buyers and make every fact agent-readable, because the two goals rarely conflict. The changes agents need, clear pricing, plain facts, predictable navigation and readable HTML, are the same changes that help a busy human evaluating vendors at speed. The design work is in presenting dense facts clearly, not in building a separate experience for machines.

Pros

Transparent pricing and specs help agents and shortlist-building buyers
Predictable page structure reduces friction for everyone
Readable HTML also improves SEO and AI search citations
Fewer forms in front of public facts can lift trust with human buyers

Cons

Publishing pricing gives sales less room to frame price on the call
Detailed comparison and security pages take real effort to keep current
Agent behavior is still changing, so some testing has to be repeated

If your team is also designing a product where agents act for users, the interface questions are different; agentic UX covers that side. For tracking buyers who research with agents and then arrive later, B2B attribution when buyers research in ChatGPT explains what analytics will and won't show.

What should B2B teams do first to prepare for AI agents?

Start with the facts an agent is most likely to be asked for: price, plan contents, integrations and security. Audit those four on your own site, then test with an agent, then fix what it couldn't find.

Publish pricing, or a clear pricing model, in an HTML table with plan contents and limits.
List integrations by name on one linked page.
Publish a security and trust summary with direct answers.
Check that all of the above render without JavaScript and aren't behind forms or heavy banners.
Run three realistic buyer tasks through an agent and fix every gap it reports.
If a rebuild is needed to get there, plan it carefully; what coding agents can and can't do in a migration is a useful reality check.

Frequently asked questions

Can AI agents fill out demo request forms?: Some agents can fill in forms when the user allows it, but most buyers use agents for research, not for contacting vendors. The agent's job is usually to build a shortlist. If your site requires a demo request just to see pricing or basic features, the agent will often report those facts as unavailable rather than submitting a form on the buyer's behalf.
Should I block AI agents from my website?: For public marketing pages, blocking agents mostly removes you from comparisons buyers ask them to run. Protect private areas, accounts and gated assets with authentication, as you would for any visitor. For public pricing, features and security summaries, being readable is an advantage. Check your CDN's bot settings, since some block automated browsers by default.
Do AI agents read structured data or schema markup?: Agents read whatever is on the page, and some may use structured data where it exists, but there's no evidence that schema determines how agents compare vendors. Ahrefs' 2026 test found no citation lift from schema in ChatGPT. Use standard markup as hygiene, and put the facts that matter in visible text and HTML tables.
How is ChatGPT shopping relevant to B2B companies?: ChatGPT's shopping features are aimed mainly at consumer products, but they show where discovery is heading: the assistant compares options and presents a shortlist with prices and specs. B2B buyers are using agents for the same kind of comparison. The lesson for B2B is to publish comparable facts, such as prices, plans and specifications, in a form any assistant can read.
Will AI agents replace B2B sales conversations?: Not for complex purchases. Agents shorten the research phase, so buyers may arrive at a sales call with a shortlist already built and fewer basic questions. That shifts sales conversations toward fit, implementation and negotiation. Vendors that make research easy are more likely to be on the shortlist that reaches that conversation.

Mehdi Hassan · CEO & Design Director

Copywriter, designer and developer, and founder of Designify Studio. Over five years, 60+ projects across 14+ industries, for startups that have raised $300M+.

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