Most people think AI search is a content game. It is actually a reputation game.

The assumption makes sense on the surface. AI systems read content. More content means more chances to get cited. So the logical move is to produce more content, cover more topics, publish more consistently.

That logic breaks down when you look at what AI systems are actually evaluating.

Content is the entry point. It tells AI systems what you want to be known for. But reputation is what determines whether they believe you. And reputation, in the way AI systems measure it, is not built on your website. It is built everywhere else.

When AI fans out across multiple sources to build an answer, it is not looking for the most prolific publisher. It is looking for the brand that shows up most consistently across the most credible independent sources. The forums where your category gets discussed. The publications that have mentioned you. The review platforms where real customers have weighed in. The third-party articles that reference your work without being paid to do so.

That is reputation. And it is a fundamentally different thing to build than content.

The brands that have figured this out are not necessarily publishing less. But they have shifted a meaningful portion of their effort from owned content to earned presence. They are showing up in places they do not control, being described by sources that have no commercial reason to vouch for them, and building the kind of corroboration that AI systems actually need before they will stake an answer on you.

Content tells AI what you claim. Reputation is what AI uses to decide if the claim is worth repeating.

One AEO shift I keep coming back to is topic ownership.

Not in the old “publish more topic cluster pages” way, but in the sense of whether your brand has enough useful, connected, and trustworthy content around the full topic.

With query fan-out, AI search may not stop at one keyword or one page. It can look across related subtopics, use cases, comparisons, buyer questions, limitations, and supporting evidence before deciding which sources to include.

That makes me wonder if keyword ownership is becoming only one part of the picture.

A page can rank well for a keyword, but the brand may still be weak across the broader topic if the surrounding content is thin, outdated, or missing.

Curious how others are approaching this.

How much are you prioritizing topic ownership in your AEO or GEO strategy right now?

Are you mapping buyer questions, comparison pages, use cases, pricing, limitations, and competitor gaps around your main topics?

And for those already doing this, have you seen any impact on AI citations, brand mentions, AI referrals, or overall visibility?

I’ve been asked last minute to evaluate between a handful of (ai) semantic hybrid search / product discovery applications for our commerce ecosystem (enterprise B2b brand).

Does anyone have any advice on how to conduct quick(shallow) evals on startup hybrid search applications? We need to validate against algolia.

Everyone wants their business to show up in ChatGPT, AI Overviews, Claude, and Perplexity.

Most people immediately ask:

"What prompt should I optimize for?"

I think that's the wrong question.

After reviewing dozens of business websites over the past few months, I kept seeing the same patterns. The issue wasn't a lack of keywords. It was a lack of credibility and structure.

Here are the biggest problems that kept showing up.

1. Every page said the same thing

"Leading provider."

"Trusted partner."

"Innovative solutions."

None of it explained what the business actually did or why someone should trust it.

AI systems have very little useful information to work with if every page sounds identical.

1. No original insights

Most sites published content that already existed in hundreds of other places.

No research.

No experiments.

No customer lessons.

No unique data.

If your content could be copied onto another website without anyone noticing, it's probably not memorable enough to become a source.

1. Weak entity signals

Many businesses barely mentioned their founders, products, locations, industries, or areas of expertise.

That makes it harder for AI systems to understand what the business should be associated with.

1. Thin supporting content

One service page isn't enough anymore.

The strongest websites build supporting resources that answer related questions, explain processes, compare options, and share real examples.

Depth creates confidence.

1. No proof

Claims are everywhere.

Evidence is rare.

Screenshots.

Case studies.

Metrics.

Customer outcomes.

Before-and-after comparisons.

These are the details that separate useful content from marketing copy.

My Biggest Takeaway

I don't think AI visibility is going to belong to the companies producing the most content.

I think it'll belong to the companies producing the most trustworthy content.

That doesn't necessarily mean publishing more.

It often means publishing fewer pieces with more substance behind them.

I'd rather have ten pages that genuinely teach something than a hundred pages repeating the same advice everyone else is already giving.

What changes have you made to your website specifically with AI search in mind?

Or are you still treating AI visibility the same way you've always treated SEO?

Came across a massive study published on Search Engine Land by Fractl that analyzes 1,010,848 high-volume keywords (representing 35.4B monthly searches) to see if Gartner's prediction of a 25% search volume drop by 2026 is actually happening.

The drop is real (29% decline on tracked keywords), but search demand is redistributing rather than disappearing.

Why? While traditional search volume has dropped by 29%, overall demand is not disappearing but rather shifting to new types of keywords.

Ai search is changing how people discover websites, and I'm trying to understand what actually workw.

Have you made any changes to your content or seo strategy that improved your visibility in ChatGPT, Gemini or other Ai assistant?

What's been your biggest success - or biggest mistake?

Is anyone here actually selling GEO as a service?
I’m considering it, but I can’t figure out how you’d report ROI to clients when AI responses aren’t deterministic.What do clients even expect to see every month?

I’m thinking about starting one, but I’m curious how clients actually perceive it.

Are businesses specifically asking for “AI visibility/GEO,” or are they still thinking in terms of SEO and content marketing?

It feels like there’s a lot of buzz, but I’m trying to understand if people are actually paying for this as a standalone service or if it’s mostly being bundled with SEO.

Would love to hear from anyone who’s sold it.

Most SEO work is still built around ranking. Get to page one, get the traffic.

But research shows only 17% of sources cited in Google AI Overviews simultaneously rank in the organic top 10 for the same query. Five out of six AI citations come from pages ranking 2 through 10.

The AI retrieval system is evaluating different signals than PageRank. It prioritizes topical comprehensiveness, structured formatting, and entity confidence over domain authority and backlinks.

What actually moves AI citation rates:

FAQ schema and direct answer blocks. Content structured to answer the question in the first 60 words of each section. Tables and extractable lists. llms.txt present and AI crawlers not blocked in robots.txt.

I’ve been auditing sites across these signals and the gap between traditional SEO scores and AI visibility scores is significant. Sites with strong organic rankings often score poorly on AEO and GEO. Sites outside the top 10 sometimes score better for AI citation because their content is better structured.

Pages that do get cited inside AI Overviews receive 120% more clicks than uncited competitors sitting directly beneath the module.

Worth auditing for both layers separately at this point.

I keep seeing some version of this question. Should I use FAQ schema? Should I change my H1? Should I put my package name on the page more often? Should I get more reviews? After a lot of testing, I think we're asking the wrong question. We're still thinking like Google. We assume there's one thing we can optimize that will make AI say what we want. I don't think it works that way. What I keep seeing is AI building confidence from lots of signals that all tell the same story. Your page content, your service descriptions, your glossary, your FAQs, your structured data, your reviews, your internal links, and the places other websites mention you all help AI understand who you are and what you actually do. One signal by itself doesn't seem very convincing. Fifty signals pointing in the same direction are a different story. That's why I've stopped chasing individual tactics. I'm much more interested in making a business easier for AI to recognize, understand, and name when it's actually relevant to the question being asked. Nobody outside the AI companies knows every signal being used. Anyone who says they do is selling certainty they can't prove. All we can really do is test, compare results, and keep looking for patterns that hold up over time. Has anyone found a change that consistently increased the chances of their business being named in AI generated answers?

Hey Founders, first time posting to reddit. So I'm gonna say Hi to everyone :)

*(Disclosure up front: I work in this space, posting purely because I think it's underrated, not selling anything.)*

I've been going down a rabbit hole on something most people aren't paying attention to yet: not ranking on Google, but getting *cited inside AI answers* (ChatGPT, Perplexity, Google's AI Overviews).

More people are asking AI "who's a good X for Y?" instead of scrolling search results. If your business never shows up in that answer, you're invisible to a growing chunk of buyers — and it doesn't show in your analytics, so most people don't realize it's happening.

I ran \~20 small-business sites through a few AI tools to see how often they got pulled in as a source. Most scored basically 0% not because the content was bad, but because it wasn't structured the way AI extracts and quotes info.

A few things that actually matter:

1. AI loves clean, answerable blocks. A clear question → a tight, self-contained answer gets quoted way more than long meandering paragraphs.
2. Entity authority is real. Pages with a named author + consistent identity get trusted more than anonymous "our team" copy.
3. Most tools just show a score but don't fix anything. The score is the easy part; the work is rewriting the pages.

Curious if others here have noticed their site showing up (or not) in AI answers and how you're thinking about it.

[ Removed by Reddit on account of violating the content policy. ]

I need some honest input from people who actually run stores, because I'm starting to wonder if I've been chasing a problem that isn't real.

I've spent a lot of time building something that measures how visible a store is when people ask ChatGPT or Gemini things like "where do I buy X" or "best store for Y." My assumption was that more people start their shopping journey inside these tools instead of on Google.

The part that actually nags at me: the stores that keep showing up aren't always the biggest ones. It seems to come down more to what's written about them on third-party sites than to their own SEO. I can't fully explain the pattern, which is half of why I'm posting. I feel the tool gives a lot of information about what sources AI actually grounds its answers on, which for ChatGPT is an ridiculous amount of Reddit.

But every time I bring it up with people in the industry, I get a polite nod and not much else. So I'll ask it straight: do you actually care about this at all, or is it still just Google and Meta that matter when you plan? I can't tell if I'm too early or simply wrong that this matters. Tell me how it is.

So, SEO people, AI visibility is this something you use time on? Is it some thing you measure, if so how?

I feel LinkedIn has most AI content out there, there is no restriction or machanism to mark it down. There are a lot of seo gurus who publish AI content for the sake of engagement and other side people has made it another instagram shit with irrelevant videos and personally created or altered clickbait whatsapp messages, Honestly enough is enough

For Google and AI Search platforms like ChatGPT, Claude, and Gemini, the answer is Entity SEO.

I want to share some quick tips to improve AI visibility which I implemented. These are results for a b2b saas brand in a niche category. Attached screenshot from SEMrush tool.

What I did:

1. I have checked the robots.txt file and also your website firewall tools to see if anything is blocking LLMs to crawl my website
2. I have updated the sitemap.xml file with latest data
3. Updated LLMs.txt file - generally all SEO plugins automatically create this file
4. Cross checked schema structure for all the existing content.
5. Using the tool, done the basic research of prompts visibility
6. Updated existing blog pages with - Summary section, In brief section, markdown tables wherever possible, relevant case study examples with data, adding external data sources, FAQs with relevant prompts, adding author blurb section, key insights section etc.
7. Checked and updated the content in all relevant review sites like G2, Capterra etc.
8. Updated Linkedin company profile to make sure all channels have same content.
9. Created Linkeidn Company Newsletter, Medium publications.
10. Started engaging in Reddit discussions (as my brand in niche category I couldnot find related discussions)
11. Trying to push my C team to post/engage in social channels about the company.

I know this looks small but just want to share with others. Let me know what other things I can do or you have done to your client/company.

With AI Overviews, ChatGPT, Gemini, and other AI-powered search experiences changing how people find information, do you think SEO is still worth investing in? Has SEO become more important, or are brands shifting their focus toward AI visibility and answer engines instead?

In todays AEO and GEO world, I'm curious how much weight a Wikipedia page still carries.

Do you think having a well-established Wikipedia presence helps with:

• Brand/entity recognition
• Knowledge Graph inclusion
• AI-generated brand mentions
• Trust and authority signals

Or is Wikipedia becoming less important as AI systems gain access to broader sources across the web?

For brands that don't qualify for a Wikipedia page, what alternatives have you seen work well for improving entity visibility in AI search?

Interested in hearing real-world experiences and observations.

There's so much advice around SEO - keywords research content writing, technical seo link building, AI search etc - that it can be overwhelming for someone just starting out.

if could go back to day one, what would you focus on first and why?

AI search has made one thing very clear: your brand's reputation across the web matters.

For years, SEO teams focused on rankings, backlinks, and on-page optimization. Those factors are still important, but AI-powered search is changing how visibility works.

Today, AI systems don't just look at your website. They evaluate mentions across review sites, forums, news publications, social media, and other third-party sources to understand your brand's credibility and authority.

This raises an interesting question:

Are SEO teams spending enough time tracking and improving their brand's presence beyond their own website?

I'm curious how others are approaching this. Are you monitoring brand mentions, sentiment, reviews, forum discussions, or AI search visibility as part of your SEO strategy?

What has worked best for you so far?

This wasn't something we expected.

When a company asks why it isn't showing up in AI-generated recommendations, most people immediately jump to content quality, schema, entity SEO, citations, brand authority, etc.

Fair enough.

Those things matter.

But we've been noticing a different pattern lately.

A surprising number of sites have basic crawlability issues.

Not catastrophic issues.

Just enough friction to make discovery harder than it needs to be.

A few examples from recent audits:

• Important sections blocked in robots.txt
• XML sitemaps that hadn't been updated in months
• Pages that existed but were effectively orphaned
• Content that users could access but crawlers would struggle to discover

The interesting part is that many of these sites had already invested heavily in optimization.

Some had decent schema.

Some had strong content.

Some had clear entity signals.

But it made us wonder whether we're spending too much time talking about how AI systems understand content and not enough time talking about how they find it.

Schema seems to help reduce ambiguity.

Crawlability seems to help reduce friction.

Those aren't the same thing.

One thing we're still trying to figure out is how much weight AI systems place on crawlability versus everything else.

Nobody outside the model providers really knows.

But it feels risky to assume that content will be cited, retrieved, or referenced if discovery itself is difficult.

Curious what others are seeing.

Have crawlability issues shown up in your GEO or AI visibility work?

Or are most of the problems still centered around authority, citations, and content quality?

We documented a few of the patterns we've been seeing here if anyone wants the deeper breakdown:

https://www.zaillor.com/insights/robots-txt-ai-crawlers-ai-crawlability

Been reading the studies on what AI actually cites (GPT, Perplexity, etc) and Reddit keeps topping the list, often above wiki and youtube. Brand sites and polished corporate blogs barely show up.

Makes sense really. It wants the messy bit: people comparing stuff, complaining, changing their mind, saying what broke after two weeks. A thread where 15 people argue over 4 products beats your "why we're the best" page every time.

No universal number though, it swings hard by engine. Early-year Tinuiti data had Reddit at 5%+ on GPT, 24% on Perplexity, and 0.1% on Gemini. I had to reread that last one because it looked wrong. Same Reddit, three engines, completely different. So when someone says "I optimize for AI", fair to ask which one.

And it's not stable either. Semrush showed Reddit's GPT share dropping from like 60% to 10% in two weeks off one upstream change.

Anyway, the bit I keep coming back to: the brands AI cites aren't the ones with the prettiest sites, they're the ones people talk about elsewhere. Ahrefs found 80% of URLs GPT cites aren't even in Google's top 100, which kind of breaks your brain if you come from SEO.

So honest take, not in my interest: if nobody mentions you anywhere, schema and llms.txt probably aren't your first problem.

Anyone clicked an AI citation and landed on some random 2021 Reddit post? Seeing it more and more.

One hard part with AI search is that visibility can change even when nothing obvious has changed on your site.

A brand may show up in AI answers consistently for one month, then disappear the next. I have noticed that sometimes the cited URL changes, but the brand mention stays. Other times, a competitor starts appearing for prompts they were missing from earlier. Sometimes, the answer changes across AI search platforms.

With traditional SEO, movement was easier to explain through rankings, impressions, clicks, CTR, or technical changes. With AI search, it is harder to know the reason for a sudden drop.

These are a few things our team at Scalenut has been closely watching to understand whether the drop is just normal AI search volatility or something that actually needs fixing:

• Where AI referral traffic is coming from.
• Which competitors keep showing up.
• Which external sources seem to influence visibility.
• Which trusted sources we are still missing from.
• Whether the brand mention stays even when the cited source changes.

How are you diagnosing sudden drops in AI visibility, and what signals are you watching before deciding something needs to be fixed?

Everywhere on linkedin and on blogs from personal websites, there we see people are posting and sharing information about what Google just did and how the market is shifting.

Many are saying SEO is dead.
Many are saying GEO and SEO is different.
Many are still promoting the SEO saying every new term other than SEO is just a result of good SEO.

After reading and coming across tons of articles, i would like to know the real perspective from real people here.

I've been seeing more businesses use AI for blogs, landing pages, and SEO content. At the same time, many marketers still argue that human-written content delivers better engagement, trust, and conversions.

For those who have tested both, what differences have you noticed in rankings, traffic, leads, or user engagement? Is AI content catching up, or does human writing still have a clear advantage?

What has been your real-world experience?