When buying committee members ask AI tools like Google’s AI Mode about potential vendors, each answer names a select number of brands. And you’re far more likely to be considered if your brand is one of them.
B2B answer engine optimization (AEO) is how your brand earns a place in those AI-generated answers.
In this guide, we’ll cover exactly what B2B AEO is, why it matters now, and how to implement it.
What is B2B answer engine optimization?
B2B answer engine optimization is the process of using marketing practices to increase how often your brand appears in the AI-generated answers your prospective buyers see.
Some marketers also call this practice B2B generative engine optimization (GEO), though the terms are used interchangeably in most contexts.
How is AEO different for B2B brands?
AEO is different for B2B brands because it involves multiple stakeholders asking different questions, long buying cycles, and answers that draw heavily on practitioner communities and business review platforms.
Different stakeholders ask different questions
Different buying committee stakeholders ask different questions based on their roles, which means your brand needs to appear in the AI answers for a wide range of questions.
For example, we asked ChatGPT about the best customer relationship management (CRM) system for a mid-market company in two ways. One prompt focused on security and compliance the way a security reviewer would. The other focused on affordability the way a finance lead would.
The security-focused answer led with Salesforce and Microsoft Dynamics 365. The affordability-focused answer ranked Zoho CRM first and positioned Salesforce as the expensive enterprise option. Freshsales and Pipedrive appeared only in the affordability-focused answer.
Buying cycles last for months
B2B buying cycles last for months, so your brand needs to keep accurately appearing in AI answers for as long as buyers are researching.
B2B buyers spend an average of 10.1 months on a purchase, but the shortlist forms almost immediately, according to a 6sense report from 2025. The months that come after are spent validating that shortlist. And large language models (LLMs) are a key part of that long research process.
AI answers draw heavily on specific third-party sources
AI answers about B2B vendors rely heavily on business review platforms, third-party comparison content, and practitioner communities, so your AEO work has to extend to platforms you don't own.
Our AI visibility study shows review platforms like G2 rank among the most-cited sources in digital technology categories.
Here are some of the third-party sources AI uses to find information about B2B vendors:
- Business review platforms: Your profiles and category pages on G2, Capterra, TrustRadius, Clutch, and GoodFirms
- Third-party comparison content: "Best [category] providers” roundups, “[brand] alternatives” lists, and “[brand A] vs. [brand B]” comparisons published by trade publications and mainstream media sites.
- Practitioner communities: Subreddits and industry forums where buyers discuss options with peers
Why does B2B AEO matter right now?
B2B AEO matters right now because buying committees already use AI to research vendors, which means your ability to be shortlisted depends on appearing in AI-generated answers with accurate information.
In our survey of 600+ U.S. B2B professionals, 92% of those who use AI say it shapes their vendor shortlist. And 54% of those AI users are final decision-makers.
Simply being named isn't enough, though. If an AI answer says your business doesn’t offer something it actually does, such as a service you launched recently, buyers may rule you out without ever contacting you.
How to do B2B answer engine optimization
Here’s how to do answer engine optimization for your B2B business, step by step:
Map questions by buying-committee role, not just by keyword
Map separate question sets for each buying committee member role to optimize your content for the full breadth of relevant questions prospects ask about your offering.
Most B2B buying committees include some mix of these roles:
- Technical evaluator: This committee member assesses whether your offering fits the organization's technical requirements, including processes the team already uses, compatibility with the system equipment, and what implementation involves
- Security and compliance reviewer: This member checks whether your offering meets the organization's security and regulatory obligations, such as certifications like SOC 2 or ISO, how you handle customer data, and who can access that data
- Legal reviewer: This member reviews contract terms, liability, and data processing agreements before anything gets signed
- Finance lead: This member evaluates pricing, total cost, and expected return on investment (ROI)
- Procurement manager: This member negotiates terms and assesses vendor stability, service-level commitments, and renewal conditions
- End user: This member judges whether your offering works for their day-to-day needs, including ease of use, and fit with existing workflows
To find out who sits on the committees buying from you, ask your sales team who joined the calls on your last 10 closed deals. That gives you real roles to map questions to.
Next, find the prompts these buyers enter into AI tools. Enter a broad topic that represents what committee members would ask about your business category into Semrush's Prompt Research tool.
Click the “Prompts” tab to see the individual prompts. Use the “Filter by topic” search bar to narrow the list by terms a given role would use, like “security” or “pricing.” Then, build a working list of every prompt relevant to your business category.
Click "View full response" in any row to see how different AI platforms answer it, which brands they mention and which sources they cite.
Then group your prompt list by role. Add all the relevant prompts you found to a spreadsheet and sort them by which stakeholder would ask each one. An AI assistant like Claude can make a first pass at the sorting, but review it yourself for accuracy.
Structure your website content for AI extraction
Structure content in a way that makes it easy for AI to extract, which increases the odds of your content being used in AI-generated answers.
Use the same AEO fundamentals that apply to any brand to create content that AI can easily quote:
- Phrase subheadings as questions. A subheading worded the way buyers phrase their prompts makes it easier for AI systems to match a prompt to your section.
- Lead each section with an answer. Make the first sentence a direct answer to the subheading above to clearly indicate that the section addresses what the subheading asks.
- Give each heading one job. If a section covers something its heading doesn't ask about, move that content under its own heading. A section labeled "Which certifications do you hold?" should list your certifications. Where you store customer data belongs under a heading of its own.
- Keep each section self-contained. Write each section so it stands on its own without needing context from elsewhere. And repeat the product or feature name instead of referring back with “it’” or “this.”
Build your brand in places where AI tools actually look
Build your brand in places where AI tools actually look to increase the odds of appearing in AI-generated answers. Here’s how:
Keep your review profiles current
Keep your review profiles current and complete to ensure AI systems can easily and accurately pull details from them.
Which platforms matter depends on your category. Software vendors should focus on G2, Capterra, and TrustRadius. Agencies and service firms should focus on Clutch and GoodFirms. Manufacturers and industrial suppliers should focus on directories like ThomasNet.
Also, aim to get reviews from across the buying committee. Ask your customer success team to request reviews from the security, finance, and IT contacts at recently onboarded accounts.
Brief the analysts covering your category
Brief the analysts who cover your category to ensure inclusion in future content that AI systems can read.
For example, a Gartner vendor briefing is free and doesn't require a subscription. Register once, submit the briefing form, and Gartner routes your request to the analysts covering your market. Forrester offers the same kind of free briefing through its own analyst briefing request form.
Published analyst reports usually sit behind a paywall, but any public content informed by them can be read and interpreted by AI systems.
Build a presence in buyer communities
Build a presence in the communities where buyers compare vendors, because those discussions are among the sources AI draws on when answering questions about your category.
Find the subreddits, industry forums, and Slack or Discord groups in your niche, and have the experts on your team answer questions using their own names and job titles.
Catch and correct inaccurate AI descriptions of your offering
Catching and correcting inaccurate AI descriptions of your offering minimizes the chances of stakeholders ruling you out based on something that isn’t true.
Find out how AI platforms portray you using Semrush’s Perception report. Scroll to “Key Sentiment Drivers” and study the “Areas for Improvement” panel.
Sort what you find into two lists:
- Inaccurate: These details could include a pricing tier that changed, like an integration you now support or a feature you shipped last quarter. They’re correctable with current facts.
- Unfavorable but fair: A steep learning curve or a capability a specialist tool has that you don’t. These only shift when you publish evidence that outweighs them or when you change the offering itself.
Next, build on the above lists by noting the sources behind each description. Click the "Sentiments" filter in the “AI Feature Descriptions” table and set it to 0%–7% to surface the descriptions AI systems frame least favorably.
Click the number in the "Answers" column on any row to see the AI responses that produced the description, the platforms they came from, and a "Sources" list with the URLs behind them.
Add the URLs informing your areas for improvement to the two lists you sorted earlier.
For inaccurate descriptions, work to correct the information. If the inaccurate content is something you control, update it yourself. For third-party content you don't control, contact the publisher to ask for a correction.
For accurate but unfavorable descriptions, aim to publish content that addresses the weakness, such as documentation that shortens a steep learning curve or a customer success story from a team that raised the same objection.
As you work to address inaccuracies and unfavorable information about your brand, periodically visit the “Favorable Sentiment” chart in the Perception report to see your sentiment trend over time.
Sentiment moves slowly, so measure this in quarters rather than weeks.
How to measure B2B AEO success
There are two ways to measure whether your brand is appearing in AI responses:
Track manually
You can manually track AI visibility by periodically asking AI tools the questions each buying committee stakeholder would ask, then logging whether your brand appears and how it's described.
Reuse the stakeholder question sets you identified during the mapping step. Do this across your priority AI tools in logged-out sessions on a fixed schedule. And note whether you appeared, how prominently, and whether the description was accurate.
Just know that manual tracking comes with real limitations. Different users (and even the same users during different sessions) get different answers to the same prompt. And checking manually doesn't reach the number of prompts, platforms, and stakeholder roles you need to cover to draw a reliable conclusion.
Use an AI visibility tool
Semrush’s Visibility Overview report tracks brand mentions, citations, and cited pages at scale, so you can see how your AI visibility is moving.
Enter your domain to see an AI Visibility score out of 100 that summarizes your overall standing in your niche, alongside your mentions, citations, and cited pages. The "Distribution by LLM" panel underneath breaks those numbers down by AI platform.
Scroll to "Topics & Sources" and click "Cited Pages" to see the URLs on your website earning citations.
Expand a row in the table to see the specific prompts that yield AI answers citing the page. This list can help you clearly see which committee members your content addresses and which ones it doesn’t.
If you need to track AI visibility across multiple brands or multiple markets, try Semrush’s Enterprise AIO solution — it’s designed for companies that have more complex needs and require greater scale.
Make B2B AEO an ongoing practice
Buying committees are already using AI to build and validate their shortlists across a multi-month buying cycle, so B2B AEO is work you repeat rather than finish.
That means it’s crucial to know how to identify what those buyers are asking, how to improve your odds of showing up in AI answers, and how to track your results.
The AI Visibility Toolkit helps you do all of that and more.
