Your Customers Are Asking AI About Businesses Like Yours

A 58-year-old business owner in Bethesda expects to sell her company within five years and has $4 million invested. She wants a nearby adviser who will not push proprietary products. A few years ago, she might have typed “financial adviser Bethesda” into Google and started opening tabs. Today she can give ChatGPT, Gemini, Perplexity or Google’s AI features the entire situation and ask which firms she should consider.

That is the practical change behind SEO, AEO, GEO and the growing pile of acronyms surrounding AI search. Customers have another way to research what to buy, who to hire and which companies deserve a place on the shortlist. I think the opportunity is real. I also think some of the panic has gotten a little theatrical.

Search is not dead. It got another front door.

Every new technology arrives with an obituary for the one before it. Television, email, retail, offices and SEO have all survived their own funerals. AI will change how people research, but customers did not suddenly stop asking friends, reading reviews, noticing ads, visiting websites or using Google because somebody invented GEO.

The behavior has changed enough to matter. In a 2025 analysis of nearly 69,000 Google searches, Pew Research Center found that users clicked a traditional search result on 8% of visits when an AI summary appeared, compared with 15% when one did not. They clicked a source inside the summary about 1% of the time. A company can now influence a decision without receiving the first click because a prospect may ask a long question, compare options and form an opinion before showing up anywhere in the company’s analytics.

That does not make traditional search irrelevant. It makes discovery harder to observe. Local visibility, reviews, referrals, paid media, social, email and the website still shape the decision. AI simply gives the customer another entrance. If your strategy discussion begins with a 40-minute debate over whether to call the work SEO, AEO or GEO, there is a decent chance the customer has already moved on.

AI has little patience for vague marketing. Neither do customers.

Companies have spent years sanding the specificity off their websites. They offer innovative solutions, put customers first and deliver exceptional results. Pricing becomes “contact us.” Expertise becomes “solutions.” Detailed case studies become a strip of logos under a headline about trust.

That language never helped customers very much. It helps even less when a system must determine whether a company fits a precise request. Consider two contractors. One promises “high-quality construction solutions tailored to every client’s unique needs.” The other explains the projects it specializes in, the area it serves, the work it will not take, its experience with historic properties, how insurance reconstruction works, typical timelines and what happens after the first call.

The second contractor has not discovered a secret GEO tactic. It has explained the business. That sounds obvious, but a surprising number of companies want sophisticated AI visibility before the internet can determine what they actually do.

Google’s guidance is similarly unglamorous: make pages crawlable, put important information in accessible text, keep business information current, use internal links sensibly and make structured data match what people can see. Google says businesses do not need special AI schema or a new AI file to appear in its AI search experiences. This will disappoint anyone hoping to sell a mysterious new technical requirement, but it should reassure everyone else.

The best content brief may already exist in your sales notes.

Keywords describe topics. Customers describe situations. A homeowner is not thinking about “restoration content.” A flood ruined the basement, the adjuster has left and the family needs to know who can put the house back together. A CEO is not thinking about “fractional CMO services.” Revenue has flattened, three agencies are pulling in different directions and nobody owns the whole problem.

AI makes it easier for customers to describe those circumstances in full. Businesses should pay close attention to the same language on calls, in emails and during sales meetings. Suppose a home services company receives 80 inquiries in a week. Some prospects misunderstand the service, some have unrealistic budgets, others need the work sooner than the company can deliver, and several strong prospects ask the same question before agreeing to an estimate.

Most organizations reduce all of that intelligence to a few CRM statuses: won, lost, unqualified, follow up. Then everyone meets the following quarter to brainstorm content ideas. The useful ideas were sitting in the sales notes the entire time.

Those conversations can improve service pages, FAQs, comparisons, case studies, videos, email nurture, advertising, sales materials and follow-up. They also give search engines and AI systems the context they need to understand when the business is relevant. Before asking what content to publish for AI, I would ask a simpler question: What are our customers repeatedly trying to figure out?

Your website cannot nominate itself as an independent authority.

Your website is not the only place describing your company. AI systems may encounter reviews, publications, directories, videos, trade associations, partners and community discussions while assembling an answer. Pew found Wikipedia, YouTube and Reddit among the sources that appeared frequently in Google’s AI summaries. The exact mix changes by industry and question, but the larger point does not: authority does not live on your domain alone.

A company can call itself experienced. A detailed case study demonstrates experience. It can call itself trusted. Thoughtful customer reviews provide evidence. It can claim industry expertise. Original research, named experts, useful analysis and credible third-party recognition make that expertise easier to verify.

This is where search, public relations, reputation, partnerships and content stop pretending to be separate disciplines. If the website describes the business one way, executives describe it another way and third-party profiles still use positioning from 2019, the company has created several competing versions of itself. The answer is not robotic repetition. It is enough factual consistency for customers, search engines and AI systems to recognize the same company wherever they encounter it.

The recommendation only earns you the next test.

Imagine a prospect spending ten minutes explaining a complicated problem to an AI assistant. They discuss budget, compare approaches, rule out alternatives and ask for firms worth considering. The assistant mentions yours. The prospect clicks through and finds a homepage that says, “Transforming tomorrow through innovative solutions.”

A customer who provided extraordinary context has landed in corporate Mad Libs. The AI mention did its job, but the website immediately made the customer start over. That is why the handoff matters as much as the recommendation.

Someone arriving from an AI-assisted journey still needs confirmation. Does this company solve this kind of problem? Does it work with people like me? Is the expected investment plausible? Is there relevant proof? What happens next? The transition should feel like the same conversation because search, conversion and customer experience all meet at that moment.

The path is straightforward, even if the attribution is not.

1. Situation: A customer describes the full problem in natural language.

2. Discovery: Search and AI systems compare available options and evidence.

3. Verification: Reviews, profiles, case studies, video and third-party sources support or weaken the recommendation.

4. Confirmation: The website helps the customer recognize the problem, understand the offer and see proof.

5. Decision: A clear next step turns confidence into a conversation, visit or purchase.

A weak link anywhere in that path can cost the opportunity. More content will not fix unclear positioning. Better rankings will not fix a vague website. An AI mention will not fix missing proof, and a beautiful dashboard will not fix a sales team that takes four days to return the call.

You probably do not need 100 AI-generated articles.

Generative AI has made average content extraordinarily cheap, and the world is responding by producing an extraordinary amount of it. I do not think the advantage belongs to the company that can publish the most competent articles about topics everyone else has already covered. That contest ends with a lot of content and very little reason to care who wrote it.

The better opportunity is to identify what the business knows that others cannot easily reproduce. What patterns has the sales team seen across hundreds of conversations? What proprietary data can the company aggregate? Which common assumptions fail in practice? Which questions can your experts answer with unusual specificity?

That knowledge can become research, benchmarks, tools, calculators, detailed case studies, useful comparisons and videos. AI can help find patterns in transcripts, organize research and accelerate production. It should help the company extract more value from what it knows, not manufacture more things for the company to say.

Measure whether any of this creates better business.

Search visibility, conversion rates, qualified opportunities, acquisition cost and revenue still matter. Businesses with meaningful AI exposure should also monitor whether they appear in relevant answers, which sources influence those answers, what the systems get right or wrong and how referred visitors behave.

Attribution will remain imperfect. Someone may discover a company in an AI conversation, search the brand later and call directly. Somebody will eventually put an impressive AI share-of-voice chart into a quarterly deck, and that chart may still have no meaningful connection to revenue.

The standard should remain stubbornly practical. Does the work help the right customers find the company, understand it, trust it and take the next step? If the answer is yes, the work is useful. If the answer is no, renaming the dashboard will not rescue it.

What should a smaller business actually do?

A regional professional services firm, contractor or healthcare practice does not need the AI infrastructure of a global retailer. It does need customers and machines to understand what it sells, who it serves, where it operates, why it is credible and what someone should do next. I would start with the fundamentals:

• Clarify thin or vague service pages.

• Answer the questions customers repeatedly ask.

• Publish proof for important claims.

• Keep local listings and third-party profiles accurate.

• Strengthen reviews, partnerships, community visibility and earned media.

• Make the website fast, accessible and easy to act on.

• Add advanced monitoring only when the fundamentals justify it.

A smaller business should earn the complexity. If the service pages say almost nothing, the case studies contain no details and the local profiles disagree about what the company does, an enterprise AI monitoring platform is probably not the next best investment. Sometimes the advanced strategy is to fix the obvious things everyone has learned to ignore.

Questions business leaders are asking

Is SEO dead because of AI?

No. AI changes how some research begins and may reduce clicks for some queries. The technical and editorial fundamentals of SEO still help search engines and AI systems understand a business, which makes reports of its death feel slightly premature.

What are AEO and GEO?

Answer engine optimization and generative engine optimization describe efforts to make information easier for answer engines and generative AI systems to understand, cite and recommend. In practice, much of the work overlaps with strong SEO, useful content, clear entity information, credible evidence and a good public reputation.

Do we need special schema or an llms.txt file?

Google does not require special AI schema or an AI-specific file for its AI features. Use accurate structured data when it helps describe visible page content, and keep normal crawlability and indexing fundamentals in order.

How should we measure AI search?

Monitor relevant mentions, source citations, factual accuracy, referred behavior and branded demand. Then tie those observations back to qualified opportunities, customer acquisition cost and revenue, where marketing measurements eventually have to live.

Should we publish more content?

Publish more useful evidence, not more volume. Prioritize original expertise, customer questions, case studies, comparisons, data and clear explanations that help someone make a decision.

The practical response is less dramatic than the headlines.

AI is changing how people discover companies, gather information and narrow their choices. Businesses should take that seriously. They should also resist the urge to turn every new interface into a reason to abandon everything they already know about customers, evidence and good marketing.

Understand what customers are trying to accomplish. Answer the questions they actually ask. Make the business unusually easy to understand. Publish evidence worth finding, keep the facts consistent across the places customers research and make the next step easy.

The platforms and acronyms will keep changing. Customers will still want to know whether you understand their problem, whether they can trust you and whether choosing you makes sense. AI may change where that evaluation begins, but the business still has to earn the decision. See how OutSwarm approaches SEO, AEO and GEO →