There will be a time, not far off, when we wax poetic about the way we used to search Google back in the day.
I remember life before Google. Search still existed, in the form of an index in the back of the encyclopedias my mother bought me while she did the grocery shop at Grand Union. At least 15 books made up the set. When I had to write about the state bird of Maine, I found the volume with M to Mc on the binding, flipped to the index, found the page number for Maine, and read it.
With consumers turning to AI for their online searches, we may be waxing sooner than we anticipated. Traditional search engine optimization (SEO), dominant for the past 20-plus years, is still the big cheese on campus. But for how long?
ChatGPT, Perplexity, and Google AI Overviews answer a question directly instead of serving a list of sites to visit. That streamlined path is called zero-click search: the customer gets the answer without clicking through to any site. When a product or service is involved, the business AI cites in that answer lands the customer. That is the rise of answer engine optimization (AEO).
Answer engine optimization is the practice of structuring the content on a website so AI tools, voice assistants, and search summaries can read, trust, and cite it as the answer to a question. Local AEO adds geo-targeted signals, with a Google Business Profile as the anchor, so AI links a customer’s request to a local business it already understands and trusts. The goal is to have your business quoted directly in the answer.
Adding keywords, secondary keywords, long-tail phrases, and a basic Google Business Profile is no longer enough to put your business on customer screens. Google Search now folds in intent and semantic understanding on top of the AI answers, and local searches are hyper-competitive and personalized. AI systems, including the summary at the top of most results, weigh customer experience and business credibility over the exact words on your page.
The rise of the answer engine
Consider a customer searching for a plumber near me. Traditional results are built from keyword matching: the request returns providers based on the keywords on their sites. That still accounts for a large share of searches. But the share of people asking AI for “a reliable, highly rated plumber in Seaside Heights who handles emergencies” is rising fast.
Those customers also convert at a much higher rate. Semrush’s June 2025 research found AI-referred visitors convert at roughly 4.4 times the rate of traditional organic search visitors.2 A business cited in an AI answer wins the sale far more often than one sitting in a list of blue links.
Where the AI answer shows up depends on the question. It appears far more often on question-shaped searches than on a bare “plumber near me.”1
Where the AI answer shows up
AI Overview against the local map pack, by query type. Whitespark, 540 local queries.
| Local-intent: “plumber in Seaside Heights” | |
|---|---|
| AI Overview appears | |
| Local pack appears | |
| Informational: “how to fix low water pressure” | |
| AI Overview appears | |
| Local pack appears | |
| Hybrid: “best emergency plumber for burst pipes in Seaside Heights” | |
| AI Overview appears | |
| Local pack appears | |
AI answers a question by pulling from several sources into one conversational reply. Pew Research found customers click a traditional link on 8% of visits when an AI summary is present, against 15% when it is not.3 The behavior is already mainstream: 45% of consumers now use AI to find local businesses, up from 6% a year earlier,4 and 68% of US Google searches already end without a click.5 Being cited by the answer engine now matters more than ranking third on a page of links.
What AI reads, and how
AI does not read your whole page. It chunks your content, stores each chunk as a mathematical vector, and, when a customer asks a question, pulls the chunks whose meaning sits closest to that question. So the content has to be built for extraction. Five principles carry most of the work:
- Direct, extractable answers. After a clear question-based heading, put a short summary that answers it. That is what AI lifts into a citation.
- Plain, everyday language. Mirror how people actually talk and type into a chatbot or a voice assistant.
- Structured data. Schema markup is machine-readable metadata, such as FAQ and How-To tags, that tells AI what your content is and how it connects.
- Authority and E-E-A-T. AI favors experience, expertise, authoritativeness, and trustworthiness: research, credible authors, and positive mentions across places like Reddit and industry sites.
- Fresh content and depth. Current, comprehensive topic clusters signal ongoing relevance. Keyword stuffing does not.
The technical foundation matters as much as the words. Pages that load slowly get skipped by AI crawlers.6 Worse, AI systems from Anthropic, OpenAI, and Perplexity do not reliably render JavaScript, and they do not read text locked inside images or PDFs.7 A restaurant whose menu is a photo of the physical menu has no menu in the AI’s database. Your site needs to load fast, be mobile-first, and serve clean HTML the crawlers can parse.
Entity authority: the thing AI actually trusts
AI does not match strings of text. It uses entity-based understanding: it maps the distinct things in the world, your business, its people, its services, and draws connections between them. Think of it as the highlighted route on a map app. You want a complete, unbroken line from point A to point B. What you do not want is a route that jumps onto a highway, disappears, and reappears miles later on a back road.
If your website says you are closed Saturdays but your Google Business Profile says you open at 9:00 AM, you have put a gap in the route. AI reads the contradiction as ambiguity, and ambiguity makes your business less safe to cite. You build that trust on three fronts. BrightLocal’s 200,000-search study found business websites account for 42% of AI citations, with directories carrying most of the rest.8
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Consistency
Your name, address, and phone number, matching exactly across directories, your website, and your Google Business Profile. One contradiction is one reason to leave you out.
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Reputation
Reviews and customer sentiment, which AI parses to judge whether your business is worth recommending as the answer.
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Earned media
Mentions in local news, community blogs, and regional directories that let AI cross-check your credibility against sources it did not get from you.
The playbook
Four steps, in order:
- Shift to Q&A content. Build FAQ pages with clean FAQ Schema that answer the specific questions local customers ask before they book.
- Write for conversational intent. Rewrite service pages to answer Who, What, Where, When, and Why plus the city. That phrasing targets the hybrid query class where AI Overviews appear about 97% of the time.
- Build sentiment across platforms. Go past your Google Business Profile: Yelp, Nextdoor, and the community forums like Reddit that AI models pull from.
- Add advanced schema. LocalBusiness, Service, Review, and GeoCoordinates markup feeds structured data straight to the crawlers.
The takeaway
Local AEO builds your business into a trusted, verified entity that AI answer engines choose to cite. Traditional SEO still matters and will for a while yet, but the businesses that structure their site for the answer engine now build a lead that widens every quarter their competitors wait.
Check your site’s AI visibility for free (no email needed), then draft your first AEO-focused FAQ page.
References
- Whitespark. (2025, May). Case study: The prevalence of AI Overviews in local search (540 queries). Whitespark. https://whitespark.ca/blog/case-study-the-prevalence-of-ai-overviews-in-local-search/
- Semrush. (2025, June). We studied the impact of AI search on SEO traffic. Semrush. https://www.semrush.com/blog/ai-search-seo-traffic-study/
- Pew Research Center. (2025, July 22). Google users are less likely to click on links when an AI summary appears in the results. Pew Research Center. https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/
- Murphy, R. (2026, March 10). Nearly half of consumers are asking AI for business recommendations. BrightLocal. https://www.brightlocal.com/research/lcrs-ai-trust/
- Fishkin, R. (2024). Zero-click search: What still works. SparkToro. https://sparktoro.com/blog/zero-click-search-what-still-works/
- SubscribePR. (2025). Does page speed matter for AI search? SubscribePR. https://subscribepr.com/blog/does-page-speed-matter-for-ai-search/
- SubscribePR. (2025). Do PDFs rank in AI search? SubscribePR. https://subscribepr.com/blog/do-pdfs-rank-in-ai-search/
- BrightLocal. (2026). Local AI visibility study. BrightLocal. https://www.brightlocal.com/research/local-ai-visibility-study/
Further reading
- Linehan, L., & Guan, X. (2026, May 11). We tracked 1,885 pages adding schema. AI citations barely moved. Ahrefs. https://ahrefs.com/blog/schema-ai-citations/