There is a lot of confusion about what AI search actually changes for websites.
On one side, you have people saying SEO is dead. On the other, you have people saying nothing has really changed and AI is just a new flavour of the same search engines. Both are wrong in useful ways. Understanding where each is wrong makes it easier to know what to do about your own website.
For franchisors and multi-location businesses, this matters because the decisions you make about content, structure, and visibility are the ones that determine whether your locations get cited by AI or skipped over. The fundamentals still matter. The bar is just higher.
What “AI search” actually means
AI search is not a single thing. It is a collection of different systems that use AI to answer questions rather than just list links. These include:
- Google’s AI Overviews, which sit at the top of many search results
- ChatGPT, Claude, and similar conversational AI tools
- Perplexity and other AI-first answer engines
- Shopping and assistant features built into Bing, Apple Intelligence, and others
- AI features inside specific platforms like Pinterest, Instagram, and Amazon
Each of these works a bit differently. What they have in common is that they summarize information for the user instead of just presenting a list of pages. Some cite their sources. Some do not. Most are pulling from the open web using some combination of search indexing, structured data, and direct content parsing.
In practice, this means your website can now show up in three different ways: in traditional search results, inside AI-generated answers, and cited alongside AI answers as a source. Each one has slightly different requirements, but the same website can serve all three.
What AI systems actually look for
AI answer engines are not mysterious. They are trying to do something very specific. They want to answer the user’s question accurately, with confidence, and with sources they can defend citing.
That shapes what they look for on a website:
- Clear, specific content that directly addresses a real question. Generic marketing copy is hard to cite.
- Structure that makes extraction easy. Headings, well-formed paragraphs, lists, tables, and clear topical focus per page.
- Signals that the content is legitimate. Author information, publication dates, site authority, and technical correctness.
- Entity clarity. The AI needs to understand what the page is about, what the business does, where it operates, and who it serves.
- Structured data where it helps. Schema markup for things like local businesses, FAQs, products, and services.
None of that is new. These are the same qualities that have always helped a page rank well in traditional search. The difference is that AI systems reward them more directly and punish the absence of them more harshly. A vague page that used to rank on the strength of domain authority or keyword matching now struggles because the AI has nothing specific to extract.
AI did not invent the rules. It just stopped rewarding the shortcuts.
What this means for SEO
SEO is not dead. The work just got more honest.
The tactics that relied on gaming signals (keyword stuffing, thin affiliate content, generic location pages, AI-generated filler) are becoming less effective, not more. The tactics that relied on actually being helpful and credible are becoming more effective.
For most businesses, that means the same SEO priorities that worked before still work. But they need to be executed better:
- Content has to be genuinely useful, not just keyword-targeted
- Page structure has to help both humans and machines navigate
- Technical SEO (schema, site speed, clean URLs, internal linking) now affects AI visibility as much as traditional ranking
- Authority still matters, but authority now includes how often the site is cited by AI as a trusted source
The result is that businesses that invested in real quality are pulling ahead. Businesses that relied on volume-based or shortcut SEO are falling behind faster than before.
What multi-location websites need to do
For franchisors and multi-location businesses, this shift lands hardest on location pages. Each location page is effectively its own candidate for AI citation. If the page is thin, duplicated, or unclear, AI will not use it. If it is specific, well-structured, and credible, it has a real shot.
The work is:
- Give every location page enough substance to stand on its own as a citable source
- Use website copywriting that reflects real local operation and local context
- Add LocalBusiness schema, FAQ schema, and other structured data that helps AI understand each location
- Build internal linking between services, locations, and supporting content so AI can see how the site connects
- Align the content on each page with what appears in the corresponding Google Business Profile
This is not a separate discipline from the web development and web design work that multi-location websites have always needed. It is the same work, with a higher standard and a new audience reading it.
Common questions about AI search, SEO, and visibility
Q. Is AI search replacing SEO?
No. AI search is a new layer on top of traditional search, not a replacement. The same fundamentals (clear content, strong page structure, technical health, and legitimate authority) continue to drive both traditional rankings and AI citations. AI has raised the standard for these fundamentals, not eliminated them.
Q. How do AI search engines decide what to cite?
AI systems cite sources that have something specific and credible to say. They favour pages with clear content, well-structured information, verifiable signals of authority, and structured data that helps them understand what the page is about. Thin or generic pages are rarely cited, regardless of how well they rank in traditional search.
Q. Do I still need SEO if I am trying to be visible in AI search?
Yes. Most of what makes a page visible in AI search is the same work that makes it visible in traditional search. Schema, clean URLs, site structure, internal linking, and quality content all contribute to both. You do not need separate strategies. You need to execute the fundamentals to a higher standard.
Q. What changes for multi-location websites specifically?
AI treats each location page as its own potential source. If one location page is rich and specific and another is a near-duplicate, AI will cite the first and skip the second. That means every location page now has to meet the same quality bar, not just the flagship. The consistency of your network is now a visibility factor.
Q. What is the single most important thing to get right?
Specificity. AI systems are built to avoid citing vague sources. A page with clear, specific information about a real business in a real place will outperform a generic page that used to rank well on keyword matching or domain authority alone.
Read the full picture
This post covers one piece of a broader shift. The full overview of what is changing in AI and marketing, and what multi-location businesses should be doing about their websites, is in our pillar piece: How AI Is Changing Marketing and What Your Website Needs to Do Now.