B2B software buyers now use AI chatbots less to learn what a category is and more to compare and validate vendors. In G2’s research among software buyers, comparing vendor strengths and weaknesses is the number one reason to use a chatbot, ahead of basic product research, vendor identification and use case validation. They use chatbots to compare vendors, check fit for a use case, narrow a shortlist and prepare RFP questions. For your content strategy, that points to pages that are clear, comparable and easy to verify. Think comparisons, use-case pages, open pricing details and third-party proof. G2 sees AI collapsing the top-of-funnel discovery stage while extending deeper into middle and bottom-of-funnel actions.
Below you’ll see where AI chatbots enter B2B buyer research, which content formats support each stage, and why this differs from consumer product discovery.
At which stages do B2B buyers turn to AI chatbots?
The change is fast. In an August survey of more than 1,000 B2B software buyers, G2 found that 87% say AI chatbots are changing the way they research. Half said they now start the buying journey in an AI chatbot instead of Google Search. That was a 71% jump compared with a G2 survey conducted just four months earlier.
ChatGPT was the favorite, chosen by 47% of buyers. That is nearly three times any other LLM. G2 reports the trend is even stronger in enterprise organizations.
One caveat. These numbers come from software buyers. If you sell B2B services, the direction is likely similar, but the exact percentages were not measured for your market.
Comparison comes first, not orientation
The most useful insight is why buyers open a chatbot. According to G2’s 2026 AI Search Insight Report, comparing vendor strengths and weaknesses is the number one reason for using AI chatbots in software research. It ranks ahead of basic product research, vendor identification and use case validation.
G2 puts it bluntly: buyers aren’t asking chatbots to orient them in a new category. They already know what they’re looking for.
The stages where chatbots show up
The G2 report lists the research tasks buyers bring to AI chatbots. Grouped into the three stages of vendor selection, they look like this:
| Stage | What buyers ask the chatbot to do |
|---|---|
| Shortlisting | Identify vendors worth considering, narrow options to a shortlist |
| Comparison | Compare vendor strengths and weaknesses, understand pricing and packaging options |
| Validation | Validate specific use cases, validate an initial recommendation, draft RFP questions based on business need |
G2 describes it this way: AI is collapsing the top-of-funnel discovery stage while extending deeper into middle and bottom-of-funnel actions. The chatbot is no longer just a search box. It’s a research assistant that sits in on the shortlist meeting.
What content supports B2B vendor research with AI chatbots?
Buyers who research software with AI hold vendors to a higher standard. G2 says they expect clear documentation, crisp positioning, credible reviews and third-party validation. Treat these as recommended content types: G2 describes what buyers expect, not which pages a chatbot actually selects as a source. If your site offers none of them, buyers have little to verify your fit with.
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Research from TrustRadius points the same way. TrustRadius advises vendors to answer later-stage buying questions with use case-specific content and detailed pricing information. Its warning is clear: vendors who gatekeep product information, such as case studies, lose out to competitors who give frictionless access to key details.
The same TrustRadius piece reports that buyers who used AI Overviews clicked the source links 90% of the time. So being cited for a category-level term can give you visibility your competition doesn’t have. It quotes an analysis of more than 300,000 B2B resources in which ungated content outperformed gated content by 26%.
Match the format to the stage
- Shortlisting: category pages and clear positioning that state who you serve, which problem you solve and what makes you different. One sentence a chatbot can lift beats three paragraphs of slogans.
- Comparison: honest “you vs. alternative” pages, feature and approach comparisons, and pricing pages written for AI chatbot answers. See how to write comparison pages for AI citations for the structure.
- Validation: use-case pages per industry or team, open case studies, documentation, and FAQ content that answers the questions a buyer would put in an RFP.
Don’t know which questions your buyers actually ask? Start with how to find the questions customers ask AI chatbots. Build your stage map from real prompts, not guesses.
How B2B vendor research differs from consumer product discovery
Consumer product discovery and B2B vendor research look similar on the surface. Both involve someone asking an AI what to buy. The buying logic is different.
For shopping, Google’s Merchant Center classifies conversational queries into three shopping stages: discovery, where users explore general product options; evaluation, where they compare options or seek specifications; and ready to buy, close to a transaction. That model fits a single shopper moving toward checkout.
B2B vendor research works differently:
| Consumer product discovery | B2B vendor research | |
|---|---|---|
| Starting point | Exploring general product options | Buyers already know the category (per G2) |
| Main AI task | Find and compare products, check specs and reviews | Compare vendors, validate fit, prepare RFP questions |
| Content that carries weight | Product pages, specifications, customer reviews | Positioning, documentation, use-case proof, pricing and packaging, third-party validation |
| End point | A transaction | A shortlist that goes into a sales conversation |
The last row matters most. G2 advises sales teams to assume the buyer has already done the research, and may even have seen an AI-generated competitor comparison. Your content is part of the sales pitch before anyone from your team is in the room.
Selling to consumers? That playbook is covered in how to get products recommended by ChatGPT and Gemini.
How ChatGPT, Gemini and Perplexity find your B2B content
Great comparison pages only help if the chatbot can find them. Each engine picks sources in its own way:
- ChatGPT uses Bing as its underlying index for search-driven answers. Around 87% of its citations come from Bing-visible sites. Rank well in Google but get ignored by Bing, and you can stay invisible to ChatGPT. For software companies, a Bing indexing checklist for SaaS sites is a smart first check.
- Gemini is closely tied to Google Search. Strong Google rankings make it more likely Gemini knows and cites your brand.
- Perplexity favors authoritative domains, pages that answer questions directly, and brands with recent coverage. Freshness carries weight.
Want the full picture? Read how AI chatbots choose sources for answers. New to the discipline behind all of this? Start with what generative engine optimization (GEO) is.
A practical checklist for B2B vendor research content
Use this list to audit your site against how B2B buyers research with AI chatbots:
- State your positioning in one clear sentence on your homepage and category pages: who you serve, what you do, how you differ.
- Publish honest comparison pages against the alternatives buyers actually consider. Include where you are not the best fit.
- Make pricing and packaging understandable, even if you can’t publish exact prices. Explain what drives the price and what each package includes.
- Build use-case pages per industry, team or problem, so a chatbot can validate fit for a specific buyer.
- Ungate your proof. The analysis quoted by TrustRadius found that ungated content outperformed gated content, and TrustRadius warns that vendors who gatekeep product information such as case studies lose out to competitors who provide frictionless access to key details.
- Earn third-party validation through reviews and mentions on independent platforms. G2 names credible reviews and third-party validation as buyer expectations.
- Stay consistent everywhere. G2 argues the best-supported, most consistently represented vendor in a category gains a compounding advantage in every AI comparison.
That compounding effect is the real point. Authority built across the shortlisting, comparison and validation stages keeps working for you, while a competitor without it keeps losing comparisons it never knew it was in. Claim that position before they do.
Ready to build this content without hiring an SEO team? See how Authora works, or browse more AI visibility guides in Authora Insights.
