How Businesses Can Get Found by Google, ChatGPT and AI visibility
SEO Is Changing
Discover B2B Vault, hosted by Allen Kopelman and sponsored by Nationwide Payment Systems. Explore business, payments, AI, sales, fintech, fraud, and entrepreneurship.
Presented by Allen Kopelman, CEO — Nationwide Payment Systems-Host of B2B Vault: The Biz2Biz Podcast
AI OVERVIEW
Search is no longer just about ranking on Google.
Business owners now have to consider how their companies appear when potential customers ask questions inside ChatGPT, Claude, Perplexity, Gemini and other large language models. That shift is creating new disciplines commonly called Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO).
On this episode of B2B Vault: The Biz-to-Biz Podcast, host Allen Kopelman speaks with Tyler Hochman of FORE Enterprise about how AI is changing search, what businesses can do to improve their visibility inside AI-generated answers, why FAQs and conversational content matter, and why companies still need to pay attention to the economics behind AI.
The big takeaway: businesses should not abandon traditional SEO. They should begin building an online presence that works for both traditional search engines and AI answer engines.
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From SEO to GEO: Business Search Is Changing Again
For years, businesses had a fairly straightforward digital marketing goal:
Get found on Google.
That led to an entire industry focused on search engine optimization, including:
Keywords
Backlinks
Blog content
Local SEO
Google Business Profiles
Technical SEO
Website authority
Those things still matter.
But the customer journey is changing.
Someone looking for a product, service or business may now skip a traditional Google search altogether and ask an AI platform a detailed question.
Instead of searching:
“payment processor for B2B business”
someone might ask:
“What payment processor would you recommend for a B2B company processing $500,000 per month that needs Level 3 processing, ACH and QuickBooks integration?”
That is a completely different type of search.
AI can interpret the entire question, research possible solutions and present a condensed recommendation without requiring the person to visit 10 different websites.
That is why businesses increasingly need to understand GEO, AEO and AI search visibility in addition to traditional SEO.
What Is Generative Engine Optimization?
Generative Engine Optimization, commonly called GEO, is the process of making your business and website easier for generative AI platforms to understand, reference and potentially recommend.
Answer Engine Optimization, or AEO, has a similar goal: creating content that clearly answers the questions people are asking.
Tyler explained that large language models consume information differently than a human browsing a website.
That creates an important shift.
Your website cannot simply look good.
It needs to contain enough accurate, structured and contextual information for an AI system to understand:
Who you are
What your company does
Who you serve
What problems you solve
What makes your company different
Where you operate
What products and services you offer
What questions customers commonly ask
That information can come from much more than the homepage.
Blogs, FAQs, articles, interviews, press mentions, podcasts, reviews, discussions and other online references can all contribute context.
Start by Asking AI About Your Own Business
One of Tyler's simplest suggestions is something virtually every business owner can do.
Open several AI platforms and start asking questions about your industry.
Don't only search your company name.
Ask questions the way an actual customer might.
For example:
“Who are the best companies for [your service]?”
“What company can help a business with [specific problem]?”
“What should I look for when choosing a [type of provider]?”
“What are alternatives to [major competitor]?”
Then change the prompts.
Ask the same basic question 10 or 20 different ways.
See which companies continue appearing.
If your competitors consistently appear and you don't, start examining why.
Allen and Tyler discussed treating this almost like A/B testing for AI search. Prompt different AI systems about your business, your competitors and your industry and look for patterns.
That is one of the major differences between traditional search and AI search: there can be an enormous number of ways a customer phrases the same buying question.
Don't Optimize for Only One AI Platform
Businesses also shouldn't assume ChatGPT, Claude, Gemini and Perplexity will produce identical answers.
They won't.
Different AI platforms may:
Reference different information
Interpret websites differently
Perform better at different tasks
Rank or recommend companies differently
Draw information from different sources
Tyler discussed how the best AI model can even depend on the specific use case. In work involving visual and audio information, for example, his team found Gemini particularly useful.
The same concept applies to marketing.
The world may be moving from optimizing primarily for one dominant search engine to thinking about several important answer engines.
That makes digital visibility more complicated—but it also creates opportunity.
FAQs May Be More Important Than Ever
We have been adding FAQs to a lot of the content we publish at Nationwide Payment Systems.
There is a reason.
FAQs closely resemble the way people interact with AI.
A customer asks:
“Can I accept ACH payments through an invoice?”
A webpage answers:
“Yes. Businesses can send invoices that allow customers to pay using ACH when the invoicing platform supports ACH payments.”
Question.
Answer.
That format is extremely easy for both humans and AI systems to understand.
Tyler pointed out that FAQs mimic natural conversation. When a webpage directly answers a question similar to the one someone is asking an AI system, the AI has highly relevant information it can use.
This is why businesses should consider adding useful FAQs to:
Product pages
Service pages
Industry pages
Blog posts
Landing pages
Knowledge centers
Don't create nonsense questions simply to stuff keywords onto a page.
Answer real questions customers actually ask.
Your Sales and Customer-Service Conversations Can Become Content
One of the more interesting ideas from this episode involved transcripts.
Businesses have thousands of real conversations with customers.
Salespeople answer questions.
Customer-service teams solve problems.
Business owners explain products.
Prospects raise objections.
Those conversations contain exactly the type of natural language that AI systems are designed to understand.
Tyler described an example of a company that transcribed customer-service calls and used that information as website content, creating a large amount of conversational material that AI could interpret.
You obviously need to remove confidential, private and customer-identifying information before publishing anything.
But the concept is powerful.
A business might turn common conversations into:
FAQs
Knowledge-based articles
Troubleshooting guides
Blog posts
Case studies
Sales guides
Product comparisons
Your customers may already be telling you what your next 100 pieces of content should be about.
Give AI More Context About Your Company
Traditional advertising frequently relies on a short marketing statement.
We're the best.
Save money.
Great service.
Those statements aren't particularly useful to an AI system trying to understand your business.
Context is much more valuable.
Explain things such as:
How long the business has operated
Industries served
Specialized expertise
Products offered
Integrations supported
Geographic coverage
Problems solved
Leadership experience
Media appearances
Awards or recognition
Customer use cases
Frequently asked questions
The goal isn't to endlessly repeat your company name.
The goal is to create a rich, accurate digital footprint that helps both people and machines understand what the company actually does.
Structured Data and AI-Friendly Information
Allen and Tyler also discussed structured information and what was referred to during the conversation as "invisible" context for AI.
The better approach is to think about this as structured data and machine-readable context.
Schema markup can provide search engines and other systems with explicit information about:
An organization
A person
A product
A service
An article
A podcast
FAQs
Reviews
Events
The visible page should still provide useful information to the customer.
Structured data can then provide additional machine-readable context behind that content.
For businesses pursuing AI visibility, this is an area worth paying considerably more attention to.
Reddit, Forums and the Rest of the Internet Matter Too
Another interesting part of the AI-search conversation is the influence of third-party content.
People often research companies on Reddit, forums, and review sites and social media before making a purchase.
AI systems can also encounter information about companies outside their websites.
Allen pointed out that Reddit can be particularly useful when researching a company because users often share experiences that won't appear in corporate marketing materials.
That presents businesses with both an opportunity and a warning.
You cannot completely control what the internet says about your company.
Your reputation increasingly becomes part of the data environment surrounding your brand.
That makes good service, legitimate reviews, thought leadership and authentic third-party mentions increasingly important.
The Economics of AI Matter
The conversation went beyond AI marketing.
There is another issue businesses need to understand:
AI isn't free.
AI applications can consume enormous numbers of tokens, and API usage can become expensive as systems scale.
Tyler explained that broad general-purpose models aren't necessarily optimized for every specific business problem. His company has worked on more specialized and private LLM approaches designed in part to improve efficiency and address issues such as security and token consumption.
This creates a question every company has to answer:
What is the ROI?
Having an impressive AI application isn't enough.
If a business spends $20,000 developing an automation and then thousands of dollars every month operating it, that system needs to produce measurable value.
AI should ultimately:
Reduce labor
Increase sales
Improve service
Speed up workflows
Reduce errors
Produce better information
Generate measurable operational efficiency
Otherwise, it's an expensive science project.
Where AI Automation Makes Sense Today
Not every AI system needs complete autonomy.
Tyler discussed a practical middle ground.
For example, an AI system can:
Read an incoming email.
Determine what the customer needs.
Draft the response.
Leave the message for a human to review.
Let the human press Send.
The same principle can be used for financial workflows.
AI may help:
Generate invoices
Send payment reminders
Identify unpaid invoices
Confirm communications
Categorize information
Prepare follow-ups
without necessarily giving an autonomous agent unrestricted access to company finances.
That type of human-in-the-loop approach may be where many businesses get the most immediate value from AI.
Agentic Commerce Is Coming—but Trust Will Matter
Another major topic was agentic commerce.
The idea is that AI agents won't simply recommend products.
Eventually, they may perform transactions.
An AI agent might:
Find a product
Compare prices
Choose a vendor
Place an order
Receive an invoice
Initiate payment
Reconcile the transaction
For B2B companies, which has enormous implications.
But Allen raised an important question during the episode:
How comfortable will businesses be handing financial authority over to AI?
That transition is likely to happen gradually.
There is a big difference between allowing AI to remind a customer that an invoice is overdue and allowing AI to autonomously move money out of a business bank account.
The companies building these systems will have to solve issues involving security, authorization, controls and trust.
We're Still in the Experimentation Phase
There is a lot of pressure right now for businesses to have an "AI strategy."
That can make business owners feel like they're already behind.
They're not.
Tyler believes we're still very much in the experimentation stage. His advice was essentially to start trying things, study the results and learn while the market is still developing.
I agree.
You don't need to rebuild your entire company around AI tomorrow.
Start with one problem.
Test one process.
Measure the result.
Then improve it.
That approach is much more valuable than chasing every new AI tool that shows up on LinkedIn.
5 Things Business Owners Should Do Right Now
Based on our conversation, here are five practical actions businesses can begin taking immediately.
-
Search for Your Own Business Using AI
Ask ChatGPT, Claude, Gemini and Perplexity questions that your prospective customers might ask.
See whether your company appears.
Then see who does.
-
Improve the Context Around Your Business
Make sure your website clearly explains who you are, what you do, who you serve and why someone would choose you.
-
Add Real FAQs
Collect actual questions from customers and answer them clearly on relevant website pages.
-
Use Structured Data
Add appropriate schema markup so machines can better interpret your organization, content, products, services, articles and FAQs.
-
Keep Publishing Useful Content
Blogs aren't dead.
Neither are podcasts, videos, interviews, case studies or guides.
In an AI-driven search environment, having more high-quality information about what you actually know and do may become more valuable, not less.
What This Means for Business Owners
I've watched internet marketing change several times since Nationwide Payment Systems started in 2001.
There were the Yellow Pages.
Then search engines.
Then Google dominated search.
Social media changed how businesses reach customers.
Video became important.
And now AI is changing how people search again.
Every transition creates confusion.
It also creates opportunity.
Businesses that begin understanding SEO + AEO + GEO + AI search now may have an advantage while most competitors are still trying to figure out what those acronyms mean.
You don't need to predict exactly what search will look like five years from now.
You need to make sure that wherever your next customer goes looking for an answer, your business has given that platform enough accurate information to understand why you may be the answer.
