I get asked some version of “is Google finished?” at nearly every business event I speak at. So here’s what the research actually shows, where it’s thin, and what I’d do about it.

Are people really using both Google and AI?

Yes. Similarweb data for May 2026 shows 95 per cent of ChatGPT users worldwide also use Google. People aren’t switching. They’re adding a tool and using whichever one suits the question in front of them.

That matches what we see in practice. A new client told us recently they’d found us through a mate’s recommendation, checked us on Google, then asked ChatGPT whether we were any good. Both platforms, used in sequence, to make one decision.

If people still use Google, what’s actually changing?

How much they use it, and for what.

A Bocconi University study tracked US desktop households from late 2024 to mid-2025 and compared those with access to ChatGPT Search against those without. Households with access ran 9.4 per cent fewer traditional searches, and the gap grew over time, reaching 17 per cent after 20 weeks. Google’s reach barely moved: about half of households used it either way. Same audience, fewer searches.

The drop wasn’t even across topics. It was steepest for informational questions. Referrals to academic sites fell by about a third, reference sites by a quarter, and developer and news sites by smaller but still real amounts. People took their “explain this to me” questions to AI first.

Not every study points the same way. Research by Gholami and colleagues, using data from over 4,000 desktop users, found people who started using a chatbot consistently visited more websites, while their traditional search activity rose at first and then declined. The authors describe their search estimates as noisy. Adoption seems to go through phases, which is a good reason to be wary of any single snapshot.

What happens to clicks when Google answers the question itself?

They fall, and by a fair bit. In a seven-day experiment published in August 2026, researchers recruited 1,100 US Chrome users and routed a randomly assigned group’s searches into Google’s AI Mode. Click-throughs to external websites dropped by 18.8 percentage points. People ran fewer search sessions each day, though each session ran a little longer. About one in seven participants said they found it harder to get to the specific website they wanted.

Google tells a different story from its side. It reports record query volumes, 2.5 billion monthly users of AI Overviews and a billion for AI Mode in its first year, and says people who use its AI features search more. That may well be true. But Google hasn’t released the baseline or user-level data that would let anyone check it, so it’s a claim rather than a finding.

Your customers still use Google. More of them are getting the answer without ever visiting your website.

What can’t the research tell us yet?

Quite a lot, and it’s worth being straight about that before anyone rebuilds a marketing plan around one statistic.

The studies measure different things. Audience overlap, query volume, click-through rates and referral traffic each capture a different slice of behaviour, so they can all be accurate and still seem to disagree. A stable audience doesn’t mean stable engagement, and more queries doesn’t mean more clicks.

The overlap figure is weaker evidence than it looks. That 95 per cent of ChatGPT users also use Google tells you the audiences overlap. It doesn’t prove AI is only a supplement. Habit keeps plenty of people on Google even as they move particular kinds of questions elsewhere.

Cause and effect is hard to pin down. Search behaviour shifts for lots of reasons, and separating AI’s effect from everything else is difficult even in well-designed studies.

Nobody is tracking individuals across platforms over time. We can’t yet see how one person moves between Google, ChatGPT and a website to finish a real task, which is the thing a business most wants to know.

Much of the data is American, and some of it is from the platforms themselves. Australian behaviour is likely to be similar, but it hasn’t been measured the same way here.

And the ground is moving. Google is testing ads inside AI Mode, which could change both how satisfied people are and how often they click. The next round of earnings reports and peer-reviewed studies should make the picture clearer.

What should a business do while the picture settles?

Plan for both, because your customers are using both. In practice that means four things.

1. Keep the Google fundamentals strong. Google’s audience hasn’t shrunk, and the AI systems lean on the same signals: clear pages, accurate structured data and consistent business details.
2. Make your pages worth quoting. If informational questions are moving to AI first, the businesses that get named are the ones whose content answers those questions plainly. That’s the core of the GEO side of the work.
3. Stop judging content on clicks alone. A page that gets you named in an AI answer can do its job without a visit. Watch enquiries, phone calls and branded searches as well as sessions. We covered what you can and can’t measure in AI search in more detail.
4. Check where you stand. Ask ChatGPT, Perplexity and Google’s AI Mode the questions your customers ask, and see who gets named. It takes about half an hour, and our step-by-step guide walks you through it.

None of that depends on predicting which platform wins. It works whichever way the numbers go.

Frequently asked questions

Are people leaving Google for ChatGPT?

Mostly not. Similarweb data shows 95 per cent of ChatGPT users also use Google. What’s changing is how people use each one: some informational questions are moving to AI tools first, and people who get an AI answer click through to websites less often.

Is AI reducing Google searches?

For some people and some topics, yes. A Bocconi University study found US households with access to ChatGPT Search ran 9.4 per cent fewer traditional searches, rising to 17 per cent after 20 weeks, with the biggest drops for academic, reference and news questions. Google’s overall audience stayed about the same size.

Does Google’s AI Mode reduce clicks to websites?

The evidence says it does. In one experiment with 1,100 US users, AI Mode cut click-throughs to external websites by 18.8 percentage points. Google says its AI features increase search use overall, but it hasn’t released data that would let independent researchers verify that.

What should my business do about AI search?

Plan for both Google and AI tools, because your customers use both. Keep your Google fundamentals strong, make your content clear enough to be quoted in AI answers, measure enquiries and calls as well as clicks, and check regularly whether AI tools name your business for the questions your customers ask.

Want to know where you stand in both?

Our AI readiness review checks where your business appears across Google, ChatGPT, Perplexity and Google’s AI Mode, compares you with the businesses being named, and sets out what it would take to close the gap.

Or get in touch with the team. For the wider picture, our AI search optimisation guide is a good place to start.

Figures in this article are drawn from Similarweb’s 2026 audience data, a Bocconi University study of ChatGPT Search adoption, research by Gholami et al. (2026), an AI Mode field experiment by Wang et al. (August 2026) and Google’s May 2026 statements, as reported by Search Engine Journal.

By Brendan Brooks, Founder and Managing Director of HyperWeb. Brendan has spent 25 years watching search evolve and helping Australian businesses stay visible through every shift.

The post Are People Leaving Google for AI? What the Research Actually Says appeared first on HyperWeb.

What did our own testing show?

In our last spot-check across ChatGPT, Perplexity and Google’s AI Mode, using the kind of local service questions real customers ask. On Google’s AI Mode, the businesses being named tracked review counts closely. The ones that made the shortlist were consistently the ones with the deepest, most recent review profiles.

That makes sense, given AI Mode has Google’s own review data sitting right next to it. ChatGPT and Perplexity read more widely, which I’ll come back to.

I’ll be up front about the limitations. This is a spot-check, not a controlled study. AI answers vary between runs, and a deep review profile tends to travel with other things that help too: years in business, an active Google Business Profile, more mentions around the web. But when the same pattern holds across the categories we tested, it’s worth acting on.

Why do AI engines lean so heavily on reviews?

Think about the problem the engine is solving. Someone asks for a good electrician in Newcastle. There are dozens who could do the job, and the engine has to compress that down to a handful of names it’s prepared to put forward. It needs evidence, and reviews are the biggest body of independent, dated, plain-language evidence about a local business that exists anywhere.

Each part of a review profile tells the engine something different:

• Volume says plenty of real people have used you.
• Recency says you’re still trading and still doing good work, rather than coasting on a reputation from 2021.
• The review text supplies language the engine can match to a question.

That last one is the part most businesses haven’t clocked. As we explained in how AI assistants choose which local business to recommend, these engines break a question into a set of related searches and look for passages that answer them. A review that says “they rewired our 1950s house in Mayfield” contains a service, a property type and a suburb, written the way a customer talks. When the next person asks about rewiring an older home in Newcastle, that review is doing work your service page might not be.

A review that names the service and the suburb gives an AI engine something to match. Five stars and “great service” gives it almost nothing.

What does this change about asking for reviews?

For years the goal was the star rating. Get the average above 4.5, keep it there, move on. That still counts, because a poor average will keep you off a shortlist quickly. But the bigger lever now is what customers actually write.

A five-star review that says “great service, highly recommend” reassures a person. It gives an AI engine very little to work with. A review that says what you did and where gives the engine exact language to match against the next customer’s question.

The trick is asking for that without coaching people into copy that reads as fake. Scripted reviews all sound the same, to people and to machines. Here’s the approach we suggest to clients:

1. Ask soon after the job. While the work is fresh and the customer is still pleased, not weeks later on an invoice footer.
2. Make it one tap. Send the direct link to your Google review form, not a link to your profile that makes them hunt for the button.
3. Give a prompt, not a script. Something like: “If you’ve got a minute, we’d really appreciate a Google review. Mentioning what we did and roughly where you are helps other people nearby find us.” That’s enough. They’ll write it in their own words, which is the whole point.
4. Ask everyone. Don’t only ask the customers you’re sure were happy. Google’s policies don’t allow selectively asking for positive reviews, and a profile that’s nothing but glowing looks less credible.
5. Reply, briefly and personally. A reply shows the business is active. If it naturally mentions the job, it adds context, as long as it doesn’t read like it was written for a search engine.

Do reviews on other sites matter for AI search?

Yes, and this is where ChatGPT and Perplexity part ways with Google’s AI. Google reviews carry the most weight on Google’s own surfaces. ChatGPT and Perplexity draw on a wider spread of sources: industry review sites, directories, local forums and social platforms.

In practice that means three things. Know which review platforms matter in your industry, whether that’s a trades marketplace, a health booking platform or a hospitality site. Keep a genuine presence on two or three of them, not just Google. And make sure your business details are identical on every one. The same name, address, phone number and service description everywhere is how an engine works out that reviews on four different sites are all about the same business. It’s the same consistency point we made in why ChatGPT recommends your competitors and not you, and it applies to reviews as much as listings.

Are reviews enough on their own?

No. Reviews are one signal among several, and a great review profile attached to a website the engines can’t read will still lose. The engine needs to fetch your site, understand what you do and confirm the details match. If your services are buried in images, your contact details are inconsistent or your pages never answer a question plainly, reviews alone won’t carry you onto the shortlist.

And don’t buy or incentivise reviews. Offering a discount or a gift for a review is against Google’s guidelines, and fake or misleading reviews can breach the Australian Consumer Law, which the ACCC does enforce. Google already removes reviews it judges to be fake and can restrict profiles that attract them. The real risk is being filtered out entirely, and in a shortlist of three that’s the same as not existing.

In a shortlist of three, being filtered out is the same as not existing.

The good news is that the legitimate version is simple and cheap. Do good work, ask every customer, and make it easy for them to say what you did and where.

Frequently asked questions

Do Google reviews affect whether AI recommends my business?

Yes. AI answers name a handful of businesses rather than showing a list, and review volume, recency and content are part of how they choose. In our own testing, Google’s AI results for local services closely followed review depth. Reviews are one signal among several, so a strong profile works best alongside a clear, readable website and consistent business details.

How many reviews does my business need?

There’s no magic number, because it’s relative. AI engines compare you with the other businesses they could name for the same question. Check the review counts of whoever is currently being recommended for your key queries; that’s your benchmark. Recency matters too, so a steady flow of new reviews beats a big batch from a few years ago.

Do reviews on sites other than Google matter for AI search?

Yes. ChatGPT and Perplexity draw on multiple sources, including industry review sites and directories. Google reviews carry the most weight for Google’s AI, but a footprint across several platforms with consistent business details helps everywhere.

What should I ask customers to say in a review?

Nothing scripted. Ask them to mention what you did and where. A review that says the service and the suburb in plain words gives AI engines exact language to match against what future customers ask. Never offer incentives for reviews, and ask every customer rather than only the ones you know were happy.

Want to know where you stand?

If you’d like to know whether AI engines are naming your business, and why or why not, our AI readiness review covers exactly this: where you appear across ChatGPT, Perplexity and Google’s AI, how your reviews and listings compare with the businesses being named, and what it would take to close the gap. It’s one half of what we described in the two questions business owners keep asking about AI.

Prefer to start on your own? Our guide to checking where you really stand in AI search takes about 30 minutes. Or get in touch with the team and we’ll take a look together.

By Brendan Brooks, Founder and Managing Director of HyperWeb. Brendan has spent 25 years watching search evolve and helping Australian businesses stay visible through every shift.

The post Do Google Reviews Still Matter Now AI Answers the Question? appeared first on HyperWeb.

Here’s what sits in each bucket, and how you’d check your own position on either.

Why do businesses on page 1 of Google get no mention in ChatGPT?

I showed two rooms the same thing in the last month, a Newcastle Business Club lunch and a digital bootcamp out at Tocal. Take a business sitting on page 1 of Google. Ask ChatGPT the question that business’s customers would actually ask. Watch it name three other businesses and never mention them.

The room goes quiet at that point. Most people in it have never checked.

The reason is structural. Google ranks pages and hands you a list to choose from. AI engines assemble an answer, which means they have to decide who to name and who to leave out. They can only name businesses they can find, understand and trust, and those three things come from how your site is built, whether your business details are consistent everywhere they appear, and whether you’re mentioned credibly beyond your own website. Ranking well helps. It isn’t the same job. We pulled apart the five common reasons a business gets skipped in why ChatGPT recommends your competitors and not you.

The useful part for a business owner is that this is measurable. Ask the engines the questions your customers ask, logged out so you’re seeing what a stranger sees, and note who gets named. That’s your baseline, and it takes about half an hour. We wrote the method up in how to check where you really stand if you’d rather run it yourself.

Google ranks pages and hands you a list. AI engines assemble an answer, which means they have to decide who to name and who to leave out.

Where could AI do real work inside your business?

The second bucket emerges differently, organically. More and more clients are realising that AI capabilities can solve a pain point in their systems and processes. It usually starts with something specific: the admin that eats a day a week, the quoting process that lives across three spreadsheets and one person’s memory, or the software subscription that costs thousands a year and does maybe a third of what the business actually needs.

Those are good starting points, because they’re specific and they already have a cost attached. Vague AI ambitions go nowhere. A named process that wastes a named amount of time is something you can put a number against and either fix or leave alone on purpose.

Three questions are worth asking about any process you’re considering. How often does it happen? How much of it is judgment and how much is moving information from one place to another? And what would getting that time back actually be worth? Work that’s high frequency and low judgment is where AI earns its keep first. Work that needs someone to weigh things up stays with a person, ideally with better information in front of them. We’ve written up the full process in could AI replace the software you’re paying for.

Can a bespoke application replace expensive off-the-shelf software?

Often, yes. It’s also the question the fewest people think to ask.

Off-the-shelf software is built for the average of thousands of businesses. You pay for the whole product, use the slice that fits, and bend your own process around the parts that don’t. Per seat, per month, indefinitely.

A bespoke application works the other way around. It’s built around how you actually operate, it does the things you need and nothing else, and you own it.

It isn’t automatically the right answer. If the off-the-shelf product fits and the price is fair, keep it. The test is the gap between what you’re paying for and what you actually use, plus how much of your process you’ve had to distort to suit the tool. When that gap is wide and the subscription is well into five figures a year, it’s worth costing the alternative properly. AI has moved that maths, because building software specific to one business is meaningfully cheaper than it was three years ago.

What does an AI readiness review cover?

Two halves, matching the two buckets.

Where you appear to your customers:

• How your business is named across ChatGPT, Perplexity and Google’s AI, on the questions your customers actually ask
• Who’s being named instead, and what they’re doing that you aren’t
• The technical reasons you’re being skipped: content structure, schema markup, crawler access, and whether your business details are consistent across the web
• What to fix first, and what can wait

Where AI could do the work:

• A look at your systems and processes, and where the repeat work actually sits
• What your current software costs measured against how much of it you use
• Where a bespoke application would pay for itself, and where it plainly wouldn’t
• A short list of what’s worth starting now against what’s better left for twelve months

You get a written summary either way. Some businesses take that list and hand it to their own people, and that’s a perfectly good outcome.

What have we learned running this on ourselves?

We’ve spent the last three years doing this to our own business first, riding the heavy wave of AI change and trying to stay just under the lip. Plenty of what we tried didn’t stick.

Two things have remained consistent. The first is that the tools change every few months, so the useful skill isn’t picking the right tool, it’s being able to swap tools without rebuilding how your business runs. The second is that the businesses getting real value started with a problem, not with the technology. The ones who started with the technology mostly ended up with a subscription and a story.

We’ve started doing the same for clients, and we’re set up to help more.

Frequently asked questions

What is an AI readiness review?

It’s an assessment of two things: how visible your business is in AI search across ChatGPT, Perplexity and Google’s AI, and where AI could do useful work inside your systems and processes. The first half looks at why you are or aren’t being named when customers ask AI engines for a business like yours. The second half looks at repeat work, current software costs, and whether a bespoke application would serve you better than an off-the-shelf subscription. You get a written summary with what’s worth fixing first.

Isn’t AI search visibility just SEO with a new name?

They overlap heavily, and good SEO work makes AI visibility easier. The difference is the finish line. Google shows a list of links and lets the customer choose. An AI engine assembles a single answer and names a handful of businesses, so being one of the options is a different result from ranking well. Content structure, schema markup, consistent business information and crawler access all matter more when there’s only room for three names.

How do I know if a custom application is worth building instead of paying a subscription?

Compare what you’re paying for against what you actually use, and count how much of your own process you’ve reshaped to suit the software. If you use most of the product and it fits how you work, stay where you are. If you’re paying well into five figures a year for a fraction of the features, working around the gaps manually, and adding staff time to make it fit, it’s worth costing a bespoke build properly. Building software around one business is cheaper than it was three years ago, which has changed where that line sits.

Is my business too small for any of this?

No. The AI search side matters more for small businesses, not less, because an AI answer names three businesses where a Google results page shows ten. On the process side, the starting point isn’t a large project. It’s usually one repetitive task that eats a predictable amount of time each week. Small businesses often see the value faster because there are fewer people and systems to change.

Want to know where your business stands?

HyperWeb has been building websites and digital strategy for Newcastle and Hunter businesses since 2000, and both halves of this are now part of that work. If you’d like to know where you stand on either front, being found or getting the work done, book an AI readiness review below or get in touch with the team.

If you’d rather read first, our working guide to GEO and AEO covers the search side in full, and our AI and application integration page covers the build side.

The post AI Readiness: The Two Questions Business Owners Keep Asking appeared first on HyperWeb.

Ask ChatGPT for a plumber or a physio yourself and you’ll see why that last step matters. You don’t get ten blue links. You get three names, maybe five, a line on each, and a reason to pick one. Being findable used to mean ranking. Now it also means being picked, by a system you can’t log into and can only partly measure.

Here’s what’s actually happening under the bonnet, what Google will and won’t tell you about it, and the work that still moves the needle. If you want the companion piece on why you might be missing from those answers entirely, we covered that in why ChatGPT recommends your competitors and not you.

How does AI search actually pick which businesses to mention?

Two techniques do most of the work: retrieval augmented generation and query fan-out. Neither is as complicated as it sounds.

Retrieval augmented generation (RAG) means the model doesn’t answer from memory alone. It fetches live pages from the search index first, reads them, then writes an answer grounded in what it found. This is why your website content matters as much as your general reputation. If there’s nothing fetchable that answers the question well, you can’t be part of the answer.

Query fan-out is the other half. Instead of running the one question you typed, the system breaks it into a set of related sub-queries and runs them all at once. Ask for “a good physio in Newcastle for a running injury” and behind the scenes it’s likely searching for physios in Newcastle, sports physiotherapy, running injury treatment, opening hours and reviews, plus a few angles you’d never have thought to type. It then assembles one answer from the best of all of that.
So you’re not competing for the one query any more, you’re competing across a dozen questions you never saw. There’s a number worth sitting with here. When Whitespark tested 540 local queries across six industries this year, Google’s AI answers showed up on only 15 per cent of the direct “physio near me” style searches. On hybrid questions, the ones that carry a buying decision inside them, “should I see a physio for this knee or wait it out”, they showed up 97 per cent of the time. Your customers are meeting the AI answer while they’re still deciding whether to buy, not just who from.

The practical upshot is that narrow keyword optimisation matters less than it used to. Covering your topic properly, in the language a real customer would use, matters a lot more. That’s the core of the GEO side of the work, and it’s a slower build than chasing a single phrase.

Why do listings and reviews still do the heavy lifting?

Because the retrieval step has to find something it trusts.

An AI assistant naming a business is making a small reputational bet on your behalf. It favours businesses it can describe confidently: the ones where the name, address, phone number, hours, categories and service description line up everywhere it looks. Where those details are inconsistent, the system plays safe and names someone clearer. We go into that in more depth in entity SEO.

Reviews are the other half of it, and not only for the star rating. Review text is retrievable content written in customer language, describing what you actually do and how well you do it. Volume, recency and specificity all count. A steady trickle of recent, detailed reviews is worth more here than a pile of three-word ratings from 2021.

It’s unglamorous work. It’s also the highest-return thing most local businesses can do, and it costs nothing but attention.

Can you actually measure any of this?

Partly. This is the uncomfortable bit, and anyone selling you a clean dashboard is overselling.

Google’s reporting on AI features will show you impressions and clicks for links surfaced there. That’s useful, and it’s more than we had a year ago. But it’s aggregate. You don’t see which question triggered you, you don’t see who else got named alongside you, and you certainly don’t see the answers where you weren’t mentioned at all. It also only covers Google. Nothing in it tells you what ChatGPT, Perplexity or Copilot said about your industry this morning.

So most businesses fall back on two workarounds.

Fixed query monitoring. Pick twenty or thirty questions your customers actually ask, run them across the major assistants on a set schedule, and record whether you get named and who else does. It’s crude, but it’s honest. The catch is that answers vary between sessions, accounts and locations, so you’re sampling rather than measuring. Run them logged out, and run them consistently, or the comparison is worthless.

Referral traffic analysis. Filter your analytics for referrals from the AI platforms. Real signal, but it undercounts badly, because plenty of people read the answer, form a view, and arrive later through a branded search or a direct phone call. In our experience being named in an AI answer shows up as a phone call more often than a session.
Neither method is a reporting suite. Treat both as directional, watch the trend rather than the number, and don’t make big decisions off a single week.

What does Google actually recommend you do?

Google’s own guidance for being eligible in AI features is refreshingly unromantic. Three things:

• Put your key business information in text on the page, not locked inside an image, a PDF or a video with no transcript.
• Keep your structured data accurate and matched to what’s actually visible on the page.
• Keep crawling permissions open, so the systems that want to read you can.

Two things Google says it does not do, since both are being sold to local businesses right now: it ignores llms.txt and similar files, and it does not need your content chopped into special AI-sized chunks. Plain, well-structured pages are the whole brief. One caveat from the same guidance that lands squarely on the build side of our work: sites that render their content through JavaScript are, in Google’s words, generally more complex to work with. If your key information only exists after a script runs, you’re making the reader work harder than it needs to. We’ve inherited sites like that, and the fix is usually a rebuild decision, not a content one.

Nothing exotic. It’s the same fundamentals that have made sites findable for two decades, pointed at a new kind of reader. We wrote up the local application of that in local SEO and structured data.

Why has accessibility become an AI readiness issue?

This is the bit most businesses haven’t clocked yet, and it’s the one I’d put money on mattering more over the next couple of years.

AI browser agents that carry out tasks, booking an appointment or filling in an enquiry form, often read a page through its accessibility tree. That’s the structured representation browsers build for screen readers. It’s the same map, used by a different reader.

Which means the accessibility work you might have parked as a compliance chore now determines whether an agent can complete a booking on your site. Unlabelled buttons, form fields without labels, fake buttons built out of divs, custom widgets with no ARIA: a screen reader user struggles with all of it, and so does the agent. If the agent can’t work out which control submits the form, it moves on to a competitor whose site it can read.

Building an accessible site and building an agent-ready site turn out to be the same job. That’s a rare thing in this business, one piece of work that pays off twice.

Where should you start?

In this order, because the early items are cheap and the later ones compound:

1. Get your business information identical and in plain text everywhere: website, Google Business Profile, directories.
2. Check your structured data is accurate and reflects what’s on the page.
3. Confirm nothing in your robots file, firewall or security plugin is blocking the crawlers you want.
4. Fix accessibility on your conversion paths first: enquiry forms, booking flows, contact details.
5. Keep reviews recent and encourage detail, not just stars.
6. Set a baseline with twenty or thirty fixed queries, then re-check quarterly.

None of that is a trick, and none of it is beyond a small business. The businesses doing this work now, while most are still deciding whether AI search is real, are the ones that’ll be named for the next few years.

We see the gap most weeks. When we ran the check for one long-standing Newcastle manufacturer, holding page 1 Google positions for their core product terms for years, Perplexity answered their customers’ buying question by naming eight of their competitors. They weren’t on the list. Their listings were inconsistent, their site described products rather than answering questions, and nobody had ever asked the engines about them. Every one of those is on the list above.

Figures in this article are drawn from Google’s published guidance on AI features, Whitespark’s 2026 local query analysis and Uberall’s quick-service benchmark, as reported by Search Engine Journal.

Frequently asked questions

How do AI assistants decide which local businesses to recommend?

They fetch live pages from a search index and write an answer grounded in what they find, a technique called retrieval augmented generation. Most also use query fan-out, breaking your single question into several related searches and assembling one answer from all of them. Businesses that get named are the ones with consistent listing information, content that answers real questions in plain text, accurate structured data and open crawling permissions. AI answers appear far more often on questions that contain a buying decision than on simple “near me” searches, so answering those questions on your site matters most.

Can I track whether my business appears in AI search results?

Only partly. Google’s reporting on AI features shows aggregate impressions and clicks for your links, but not which query triggered them, who else was named, or what happened outside Google. The practical alternatives are running a fixed set of customer questions across the major assistants on a schedule and recording the results, and filtering your analytics for AI platform referrals. Both are directional rather than exact.

Does website accessibility affect AI visibility?

Increasingly, yes. AI agents that complete tasks on websites, such as making a booking or submitting an enquiry, often read pages through the accessibility tree that browsers build for screen readers. Unlabelled buttons, missing form labels and custom controls without ARIA make a site hard for both screen reader users and AI agents. Fixing accessibility on your conversion paths improves both at once.

Is optimising for AI recommendations different from local SEO?

They overlap heavily. Consistent business information, genuine reviews, accurate structured data and crawlable content serve both. The differences are in emphasis: AI answers reward content that covers a topic thoroughly in natural language rather than content built around a single keyword, and they put more weight on being describable as a clear, consistent business entity.

Want to know where you actually stand?

HyperWeb has been building websites and digital strategies for Newcastle and Hunter businesses since 2000, and getting our clients named in AI answers is now part of that work. If you’d like us to check where your business currently sits in AI search and what it would take to shift it, get in touch with the team. For the wider picture, our guide to getting found in AI search is a good place to start.

The post How AI Assistants Decide Which Local Business to Recommend appeared first on HyperWeb.

More of your customers are starting with AI than you think. Instead of Googling “web designer near me” and scanning a page of results, they ask ChatGPT, Perplexity or Google’s AI Mode a full question and take the shortlist it gives them. If your business isn’t on that shortlist, you’re losing the enquiry before you ever knew it existed. We’ve watched it happen to businesses that have ranked on Google’s first page for years: they ask an AI engine the question their customers ask, and it recommends a handful of competitors without ever mentioning them. This is the same shift we wrote about in our working guide to GEO and AEO, looked at from the angle that matters most to a business owner: why am I not there, and what do I do about it?

How does AI search decide who to mention?

It helps to understand what’s happening under the hood, because it explains every fix that follows.

An AI engine answers a question in two steps. First it draws on what it absorbed during training, a broad sense of which businesses are known and credible in a field. Then, for anything current, it fetches live pages from the web, reads them, and lifts the parts that answer the question. To be named, you need to either be a brand the model already recognises, or have a page it can fetch and understand well enough to quote. Ideally both.

That’s the whole game. Everything below is about making your business one of the brands the model knows, and your pages the ones it can lift a clean answer from.

What are the real reasons your business is invisible?

In our experience there are five, and most businesses have more than one.

1. Your content doesn’t answer questions directly. AI engines lift short, self-contained answers. A page that buries its point under five paragraphs of preamble, or never states the answer plainly, gives the engine nothing to quote. Pages that lead with a clear answer and back it up get cited. If your content reads like a brochure rather than an answer, it’ll be skipped.

2. Your business isn’t a clear entity. AI engines build a picture of who you are from your name, address, phone number and description as they appear across your website, Google Business Profile, LinkedIn, directories and data aggregators. When those details are inconsistent, or barely present, the engine can’t form a confident picture of your business, so it plays safe and names someone clearer. We go deeper on this in entity SEO, but the short version is: be the same business everywhere, in exact detail.

3. You have little or no schema markup. Schema is structured data that spells out, in a format machines read directly, what your page is and which sentence answers which question. Most businesses treat it as an optional plugin setting. AI engines and search engines use it to confirm what they’re looking at. Without it, you’re asking the machine to guess. Our piece on schema markup covers what actually matters here.

4. You’re accidentally blocking the AI crawlers. AI engines send their own bots to read your site: GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and others. If your site blocks them, whether by choice or by a setting nobody remembers changing, you remove yourself from AI answers entirely. It’s worth checking, and we explain the decision in GPTBot and your website.

5. You haven’t earned enough authority. AI engines lean toward businesses that appear credibly and repeatedly across the web: mentions, links, reviews, coverage. If your business barely shows up beyond its own website, the model has little reason to trust you over a competitor who’s cited everywhere. This is the slowest to fix, but it compounds.

How do you check where you actually stand?

Before fixing anything, find out how invisible you really are. Ask ChatGPT, Perplexity and Google’s AI Mode the questions your customers would ask: “best [your service] in [your town]”, “who should I hire to [do the thing you do]”. See whether you’re named, and who’s named instead. We wrote a full method for this in how to check where you really stand. Do it logged out, so you’re seeing what a stranger sees, not a result skewed by your own history.

We run this check on our own business, and it keeps us honest. One recent morning we asked three engines the same simple question, who are the best web developers in Newcastle. ChatGPT put us first. Perplexity and Google’s AI Mode didn’t mention us at all, even though we’ve ranked on Google’s first page for our own services for years. Same question, same day, three completely different answers. That’s the nature of these engines: being named by one is no guarantee with the next, and the answers shift over time, which is why one check is a snapshot, not a scoreboard.

Whatever comes back is your baseline. If competitors are named and you’re not, the five reasons above are your checklist.

How do you fix it?

The work sorts into quick wins and slow burns. Do the quick ones first.

Fix your business information everywhere. Make your name, address and phone number identical across your website, Google Business Profile and every directory you can find. It’s unglamorous, and it’s the single highest-return thing most local businesses can do, because it feeds the entity picture directly.

Rewrite your key pages to answer questions. On the pages that matter, lead with a direct answer, then support it. Add an FAQ section that answers the real questions customers ask. This helps human readers and gives AI engines clean passages to lift.

Add proper schema markup. Organization, LocalBusiness, Service and FAQPage schema on the relevant pages. It’s technical work, but it’s a one-time setup that keeps paying off.

Confirm the AI bots can reach you. Check your robots file and any security or firewall settings aren’t quietly blocking the AI crawlers you want reading your site.

Build authority over time. Publish genuinely useful content on your topic, earn mentions and reviews, and get listed where your industry gets listed. This is the long game, and it’s the difference between being occasionally fetched and being a brand the model knows.

Why is this a technical job, not a magic trick?

Plenty of people are already selling “get your business into ChatGPT” as if it were a switch. It’s not. Appearing in AI search is the product of clean structure, consistent data, real schema, open access for the right crawlers, and earned authority. That’s disciplined web and content work, which is exactly what a good web team does. If a service promises instant AI visibility with no changes to your site, it’s selling you something that doesn’t exist.

None of this is beyond a small business. It’s the same fundamentals that have always made a site findable, pointed at a new reader. The businesses that do it now, while most are still working it out, are the ones AI engines will name for the next few years.

Frequently asked questions

Why does ChatGPT recommend my competitors but not me?

Usually because your competitors are easier for the AI to find, understand and trust. Their business information is consistent across the web, their pages answer questions in a liftable way, they have schema markup, they allow the AI crawlers, and they’re mentioned in more places. Any one of those gaps can be enough for the engine to name them and skip you. The fixes are the same disciplined web and content work that makes any site findable.

How do I get my business to show up in AI search?

Start by making your business information identical everywhere (website, Google Business Profile, directories), rewrite your key pages to answer real customer questions directly, add proper schema markup, confirm you’re not blocking the AI crawlers, and build authority over time through useful content and mentions. Check your starting point first by asking AI engines the questions your customers would ask, logged out.

Is appearing in AI search different from ranking on Google?

They overlap heavily. AI engines draw on much of the same web Google indexes and reward the same signals: clear content, consistent business data, strong schema and real authority. The difference is the finish line. Google shows a list of links; AI search lifts an answer and names a source. Work that improves one generally improves the other.

Can I pay to be included in ChatGPT or AI answers?

No. There’s no paid placement in the organic answers ChatGPT, Perplexity or Google’s AI Mode generate. Being named is earned through the visibility, structure and authority of your business online. Anyone promising guaranteed paid inclusion in AI answers is misrepresenting how these engines work.

Want a straight answer on where you stand?

HyperWeb has built websites and digital strategies for Newcastle and Hunter businesses since 2000, and getting our clients found in AI search is now part of that work. If you’d like us to check where your business currently stands in AI search and what it’d take to fix it, get in touch with the team. For the full picture, our guide to GEO and AEO is the place to start.

The post Why ChatGPT Recommends Your Competitors and Not You appeared first on HyperWeb.

Why isn’t page 1 on Google enough anymore?

Search has split. Google is still enormous, but it’s no longer the only place your customers ask buying questions. They’re asking ChatGPT which accountant to use, asking Perplexity to compare suppliers, and getting AI Mode summaries before they ever see your listing.

Here’s the part most businesses miss: Google’s own guidance about how to appear in AI results covers only Google’s surfaces. ChatGPT, Perplexity and Copilot run their own retrieval systems with their own signals, and none of them owe your Google ranking anything. We unpacked that distinction properly in our post on the fine print behind Google’s GEO and AEO claims, so I won’t re-argue it here. The short version: your Google position tells you how Google sees you. It tells you nothing about the engines Google doesn’t own.

That gap is measurable, and measuring it is the point of this post.

How do I check where I stand in AI search?

You don’t need software or a subscription for a first pass. You need about 30 minutes and a bit of honesty. Here’s the process I use.

1. Write down 5 to 10 questions your customers actually ask. Phrase them as real questions, not keywords. “Who’s the best physio in Newcastle for sports injuries” is a question. “Physio Newcastle” is a keyword, and it’s not how people talk to AI. Pull these from sales calls, enquiry emails and the things prospects say in first meetings.
2. Ask each question in ChatGPT, Perplexity and Google’s AI Mode. Use a fresh or logged-out session where you can, because your history colours what you’re shown. And ask each question twice: these engines don’t give identical answers between runs, so a single response is an anecdote, not a reading.
3. Record three things per answer. Which businesses get named. Whether yours is one of them. And which sources the engine cites, because those citations tell you what it trusts.
4. Ask the engines about your business by name. “What does [your business] do?” “Where is [your business] located?” Check what comes back for accuracy: services, location, positioning. This is your entity check, and it’s often where the surprises are. If an AI engine describes you incorrectly, it’s working from stale or thin information, and that’s fixable.
5. Compare all of it against your Google rankings for the same intents. This comparison is where the story emerges, and it’s what the next section is about.

Keep it all in a simple spreadsheet: question, engine, businesses named, you (yes or no), sources cited. That sheet becomes your baseline for next quarter.

I ran this exact check for one of our clients while writing this post: a Newcastle manufacturer holding page 1 Google positions, including several top 3 spots, for their core product terms. I asked Perplexity the same buying question their customers ask. It named eight local competitors. They weren’t one of them. Page 1 on Google, invisible in AI, and until you run the check, you simply don’t know.

What do the results mean?

Every business lands in one of four boxes.

Visible in both. You rank on Google and AI engines name you. Strong position. Your job is to protect it, keep publishing, and keep your entity signals clean.

Visible on Google, invisible in AI. This is the gap most businesses find when they run the check, and the good news is it’s the fixable one. Your Google standing proves you’re a legitimate, established player. What’s missing is usually the kind of content and corroboration AI engines lean on, and both can be built deliberately.

Visible in AI, weak on Google. Rarer, but it happens, typically when a business has strong third-party mentions or genuinely original content that AI engines pick up before traditional rankings catch up. Worth understanding what’s driving it so you can keep it.

Invisible in both. That’s a different and more basic problem, and it usually points to foundations: site structure, content depth, or an online presence that’s thinner than the business deserves. Fix the fundamentals first, then re-run the check.

Your Google position tells you how Google sees you. It tells you nothing about the engines Google doesn’t own.

What actually gets you cited?

Three things move the needle, and none of them are tricks.

Original, expertise-driven content that answers real questions. AI engines reward pages that answer first and elaborate second, which is exactly what a well-built FAQ section or answer-first article does. If your site says the same generic things as everyone else’s, there’s no reason for an engine to cite you. We covered how to build content engines actually want to quote in GEO in practice: making your content citable.

Clear entity signals. Consistent name, address and phone details everywhere they appear, proper schema markup, and a real named author with genuine credentials behind your content. Engines are trying to work out who you are and whether to trust you. Make it easy.

Third-party corroboration. AI engines lean heavily on what others say about you: mentions, reviews, citations and links from sources they already trust. It’s the modern version of reputation, and we’ve written about why backlinks and mentions matter more in AI search, not less.

None of this is fast, which is exactly why checking now matters. The businesses building these signals today are the ones AI engines will be naming in twelve months. The full playbook, what to build and in what order, is in our AI search optimisation guide, which we keep current as the engines change.

A few honest caveats

Anyone selling you a guaranteed AI ranking is selling something they don’t control, so let’s be straight about the limits of this check. AI answers are non-deterministic: ask the same question twice and you’ll often get different names. What you’re taking is a snapshot, not running a rank tracker. Personalisation muddies logged-in results, which is why fresh sessions matter. And the sensible cadence is quarterly, not weekly. Obsessing over run-to-run variation will drive you mad and tell you nothing. The trend across quarters is the signal.

We also ran the check on ourselves, and the results make the point better than any theory. Ask ChatGPT for the best web developers in Newcastle and HyperWeb comes back first, named best overall. Ask Perplexity the identical question and we’re not named at all. Same business, same day, different engines, different answers. That’s why you check more than one engine, and why the quarterly trend matters more than any single run.

Frequently asked questions

How do I check if my business shows up in ChatGPT?

Write down 5 to 10 real questions your customers ask, phrased as questions rather than keywords, and ask them in ChatGPT using a logged-out or fresh session. Note which businesses get named, whether yours appears, and which sources are cited. Then ask ChatGPT about your business by name and check the answer for accuracy. Ask each question twice, because answers vary between runs. The whole exercise takes about 30 minutes and gives you a baseline you can re-check quarterly.

Why does my business rank on Google but not appear in AI answers?

Because they’re different systems. Google’s rankings reflect Google’s signals, while ChatGPT, Perplexity and Copilot run their own retrieval with their own preferences. AI engines favour original content that directly answers questions, clear entity signals like consistent business details and schema, and third-party corroboration such as mentions and citations from trusted sources. A site can satisfy Google’s criteria while offering AI engines little to quote or verify. The gap is common, and it’s fixable with deliberate work on those three areas.

Can I pay to appear in AI search results?

You can’t buy a mention in the answers themselves. Some engines are introducing advertising formats around their answers, sponsored questions and placements, but the organic recommendation your customers trust isn’t for sale. Visibility in AI answers is earned through citable content, clear entity signals and third-party corroboration. Be wary of anyone offering guaranteed placement or guaranteed AI rankings, because they’re promising control over systems nobody outside those companies controls. What a good agency can do is build the signals that make engines far more likely to name you.

How often should I check my AI search visibility?

Quarterly is the right cadence for most businesses. AI answers vary between individual runs, so weekly checking mostly measures noise rather than progress. A quarterly snapshot, using the same set of questions each time, shows you the trend that matters: whether you’re being named more often, whether the engines describe your business accurately, and whether your content is starting to appear in citations. Keep your results in a simple spreadsheet so each check builds on the last.

Want the full picture, not just the snapshot?

This 30-minute check is a genuinely useful first look, and I’d encourage every business owner to run it. If what you find raises questions, we can run the full version properly: a structured visibility audit across Google and the engines Google doesn’t own, mapped against your competitors, with a clear plan for closing whatever gap turns up. It starts with a conversation, not a contract. Get in touch and we’ll take a look together, or read more about how we approach search visibility as a whole.

By Brendan Brooks, Founder and Managing Director of HyperWeb. Brendan has spent 25 years watching search evolve and helping Australian businesses stay visible through every shift.

The post Page 1 on Google, Invisible in ChatGPT: How to Check Where You Really Stand appeared first on HyperWeb.

The short version: traditional SEO got you onto a page of results. GEO and AEO are about getting cited inside an answer. Different end product, different optimisation, same underlying goal of being the source customers find before they decide.

What GEO and AEO actually mean

GEO stands for Generative Engine Optimisation, the discipline of optimising your content so generative AI engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) treat your business as a trustworthy source and quote you in their answers.

AEO stands for Answer Engine Optimisation, the broader discipline of structuring your content so that any answer engine, whether AI-generated or featured-snippet-style, can lift a clean, attributable answer straight from your page.

The two overlap considerably. AEO is closer to a refinement of classical SEO with answer-shaped content and structured data. GEO is more about being the brand a model has internalised as authoritative on a topic. We treat them as a single optimisation discipline at HyperWeb, with shared technical foundations and slightly different content emphases.

For the deeper definitional read, our piece on AEO vs GEO and why your SEO strategy needs both in 2026 goes line by line through where the two diverge and where they converge.

What changes when AI is in the loop

Three things change when a real person’s first stop is an AI engine instead of a Google results page.

First, the search query changes shape. A traditional Google search is short and keyword-heavy. An AI search is closer to a conversation. People type questions the way they would ask a colleague, with context attached. Optimising for keywords still matters, but the unit of optimisation moves up to the question.

Second, the unit of success changes. On a search results page, you wanted to be in the top three results. In an AI answer, you want to be cited as the source. Sometimes the user clicks through to read more. Sometimes they do not, which is the much-discussed zero-click problem. We have written about how that pattern is reshaping search in The Zero-Click Future of Search.

Third, the model has to know who you are before it can cite you. Traditional SEO assumes a fresh crawl. AI search assumes a model that has already absorbed the web at training time, then refreshes itself with current sources at answer time. Being in the model’s working understanding of your industry matters as much as the technical visibility of any single page. That is the entity layer of SEO, which we cover in Entity SEO: how search engines figured out what you actually are, not just what you say.

How HyperWeb approaches AI search optimisation

Our working framework comes down to five practical disciplines.

One: write content that answers questions cleanly. AI engines lift short, attributable passages. Posts that bury the answer under five paragraphs of preamble get skipped. Posts that lead with a clear answer and back it up get cited. Our piece on making your content citable covers what we tell clients about structure and tone.

Two: ship serious schema markup. Structured data is how machines confirm what a page is about and which sentence is the answer to which question. Most businesses still treat schema as an optional Yoast tickbox. We treat it as core infrastructure, especially FAQPage, Article, Organization and Service. The case is laid out in the structured data strategy most businesses are still ignoring.

Three: build the entity layer. Consistent business information across your website, Google Business Profile, Wikidata, LinkedIn and the major data aggregators tells AI engines who you are and where you operate. A consistent entity beats a louder one. Our entity SEO post above goes into the detail.

Four: decide which bots are allowed in. GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Googlebot and the rest each crawl your site under different terms. Letting them in is what makes citation possible. Blocking them removes you from AI answers entirely. We cover the strategic decision in GPTBot and your website: a strategic decision for the AI age.

Five: align your wider content strategy with how buyers actually search. The B2B awareness landscape has shifted from search-then-discover to ask-then-shortlist. We have written about what that means for content strategy in The B2B awareness landscape has changed and on the same shift from a customer-behaviour angle in Your next B2B customer won’t Google you, they’ll ask ChatGPT.

Where to read more

This page sits at the top of our AI search content cluster. The supporting articles below go into specific corners of the discipline.

To check where you stand today, run the 30-minute self-audit in Page 1 on Google, Invisible in ChatGPT. It is the fastest way to turn this guide from theory into a to-do list.

If you are new to GEO and AEO, start with How to get found in the AI and LLM farm for the broad overview, then read AEO vs GEO to understand where the disciplines diverge.

For the technical foundations, read Schema Markup: the structured data strategy most businesses are still ignoring and Entity SEO. These two together cover most of the technical work that makes citation possible.

For the strategic shift, read The Zero-Click Future of Search, Your next B2B customer won’t Google you, and The B2B awareness landscape has changed. These three describe how buyer behaviour has moved and what that does to your content strategy.

For tactical writing, read GEO in Practice: how to make your content citable.

For the bot access decision, read GPTBot and your website.

For the current state of the platform politics, our most recent piece is Google claims authority over GEO and AEO. Read the fine print.

Frequently asked questions

What is the difference between SEO, AEO and GEO?

SEO optimises your site to rank in a list of search results. AEO optimises your content so it can be lifted as a clean answer by any answer engine, including AI Overviews and featured snippets. GEO optimises your business and content so generative AI engines like ChatGPT, Claude and Perplexity treat you as a trusted source and cite you in their answers. The three are layered, not competing. A modern strategy uses all three.

Do I still need traditional SEO if I am optimising for AI search?

Yes. AI engines pull heavily from the same web that Google indexes. Pages that rank well in Google are also more likely to be retrieved as citation sources by ChatGPT, Perplexity and Gemini. The technical SEO foundations (clean site architecture, fast pages, working schema, internal linking) underpin both. AI search is a layer on top of strong SEO, not a replacement for it.

How long does it take for an AI engine to start citing my content?

For Perplexity and ChatGPT search, which fetch live web content at answer time, the lag is short. Once a page is indexed and ranking well for the relevant question, citation can follow within days. For the deeper model-level recognition (a model treating your brand as a known authority on a topic), the timeline is longer and depends on how often your name appears in authoritative sources over months. Both are accelerated by the same fundamentals: clear content, strong schema, a coherent entity, and external mentions in places the models trust.

Does HyperWeb offer GEO and AEO as a service?

Yes. We work with businesses to audit current visibility in AI search, fix the technical foundations (schema, entity consistency, bot access), and shape content so it is structured for citation. Our approach pairs traditional SEO with the AI-specific layers, since the two reinforce each other. Get in touch with the team for a conversation about your business.

Want to talk through how this applies to your business?

HyperWeb has been building digital strategies for businesses in Newcastle, the Hunter Region and beyond since 2000. AI search is a serious shift, but the work to be found in it is not magical. It is disciplined SEO, considered content, real schema, and a coherent picture of who you are as a business.

If you would like to talk through how this applies to your business, get in touch with the team. For our AI-application work more broadly, see our AI application integration service.

By Brendan Brooks, Founder and Managing Director of HyperWeb. Brendan has spent 25 years helping businesses turn their websites into working parts of the business.

The post AI Search Optimisation: HyperWeb’s Working Guide to GEO and AEO appeared first on HyperWeb.

This article is part of our AI search series. The full picture, with all ten pieces in reading order, is in HyperWeb’s working guide to GEO and AEO.

Google has just made one of its boldest claims in years, and it did it quietly, in a help document rather than a headline. The updated guidance on Google Search Central positions Google as the single authoritative source of truth for SEO best practice, and it extends that claim to cover AI search optimisation as well: AEO and GEO included.

For anyone selling AI search as a brand-new dark art, this is an uncomfortable read. For those like us who have argued from the start that good AI visibility is built on strong fundamentals and clear strategy, it is closer to a quiet endorsement. The interesting part is not what Google claimed. It is the line it could not cross.

What Google actually said

Stripped of the diplomatic language, the guidance lands on four points that every marketing leader should understand.

First, no one can guarantee you a ranking. Third-party tools do not have access to Google’s internal ranking data, so no tool or service can promise performance, and Google does not endorse any of them. Second, treat bold claims with suspicion and check recommendations against the official documentation. Third, keep control of your own Search Console access, because that is where the data actually comes from Google rather than from an intermediary. Fourth, and this is the part that matters most for us, the same logic applies to AI optimisation. Google explicitly names AEO and GEO and asserts that its own advice is the benchmark against which any AI search tactic should be measured.

In other words, Google has drawn a clean line between third-party opinion and its own guidelines, then nominated itself as the referee.

Google has drawn a clean line between third-party opinion and its own guidelines, then nominated itself as the referee.

Where we agree with Google

Plenty of this is fair, and about time. The market has been flooded with AI search “hacks” sold at a premium: special files to feed the bots, content chopped into machine-readable fragments, schema applied like a magic spell, and manufactured mentions designed to trick a language model into trusting you. Google has named most of these as unnecessary for its own AI features, and so it should. They were always a distraction from the work that compounds.

This is the same message we have been giving clients since AI search became an important topic. Generative engines are built on the same indexed web and the same quality systems that have always rewarded expertise, originality and trust. If your content earns visibility the hard way, it tends to earn citations the same way. We unpacked the foundations of this in our guide to getting found across SEO, AEO and GEO, and the practical side of making your content the source AI reaches for in GEO in Practice. Neither relied on tricks, because tricks were never the point.

It also rhymes with the direction Google has been travelling for a while. When the September 2023 Perspective update shifted the emphasis further towards genuine expertise and user satisfaction, the smart response was never to chase the algorithm. It was to deserve the visibility. We wrote about that shift in our breakdown of the Perspective update, and this latest guidance sits comfortably on top of it.

The fine print Google could not write

Here is the line Google could not cross, and it is the whole game.

Google’s guidance covers Google Search. Full stop. It speaks for AI Overviews and AI Mode because those are Google’s own surfaces, drawing from Google’s own index. It does not, and cannot, speak for ChatGPT, Perplexity, Copilot or the growing field of answer engines that run on entirely different retrieval systems. Those platforms decide what to surface and cite using their own logic, their own data sources and their own ranking signals.

So when Google says GEO is “just SEO,” that is true on Google’s turf and only on Google’s turf. The moment your customer opens ChatGPT instead of a Google tab, you have stepped outside the boundary of everything Google just published. The tactics it rejects for its own results may carry real weight elsewhere. Visibility across the full set of AI engines is a separate, deliberate, platform-specific exercise, and no amount of Google documentation changes that.

When Google says GEO is “just SEO,” that is true on Google’s turf and only on Google’s turf.

This is exactly why the strategic framing matters more than the tactical one. GEO done properly was never a set of tricks for gaming AI Overviews. It was always two things working together: strong fundamentals that satisfy Google, and a clear plan for being understood, trusted and cited across engines that Google does not own. Google has just validated the first half and stayed silent on the second. The silence is the opportunity.

What this means for your business

If you are a CEO or marketing director trying to decide what to do with this, the brief is refreshingly simple, even if the execution is not.

Stop paying for guarantees, because no one can honestly make them. Keep your useful tools, but weigh their advice against the primary source and hold your own Search Console keys. Pour your real budget into the things that compound regardless of platform: content only your business could have produced, drawn from genuine client work and hard-won expertise, supported by sound technical foundations and a visible track record of authority. Then build a deliberate strategy for the engines Google cannot speak for, because that is where the next wave of discovery is already happening.

One practical edge worth naming: the questions your customers actually ask AI tools about your industry are observable, if you instrument for them. Embedded conversational agents on your own site, such as our HyperAI integration, give you a first-party log of the real queries your visitors are trying to resolve, alongside the topics, framings and objections they bring with them. That data is significantly more useful than guessing at AI search behaviour from outside.

Google wanted the last word on AI search. It got the last word on its own platform. The conversation about everything else is still wide open, and that is exactly where we can help you win.

Frequently asked questions

Did Google say GEO and AEO are dead?

No. Google said that on its own surfaces, optimising for AI features is not a separate discipline from SEO, and that the same fundamentals apply. It did not say generative engine optimisation has no value. The work of earning visibility across answer engines Google does not own still matters and still needs a deliberate strategy.

Does Google’s guidance cover ChatGPT, Perplexity and Copilot?

No. It covers Google Search only, including AI Overviews and AI Mode. Other engines use different retrieval systems, so multi-engine visibility remains a separate, platform-specific consideration.

Should we stop using third-party SEO tools?

No. The point is narrower. No tool has access to Google’s internal ranking data, so none can guarantee a ranking, and bold guarantees deserve caution. Good tools remain useful for research, diagnostics and measurement. Weigh their recommendations against Google’s documentation and keep control of your Search Console access.

What should businesses actually do in response?

Focus on the fundamentals that compound: original, genuinely useful content, demonstrated expertise and authority, sound technical foundations, and a clear plan for being cited across the full set of AI engines. Verify advice against primary sources, and be sceptical of anyone selling AI search as a brand-new rulebook.

Trying to work out where your business stands across Google’s AI results and the wider field of answer engines? We can help you separate the fundamentals that compound from the tactics that do not. Get in touch for a GEO and AI Search Audit and we will give you a prioritised plan to get the visibility your business deserves.

The post Google Claims Authority Over GEO and AEO. Read the Fine Print appeared first on HyperWeb.

If your last serious thinking about backlinks happened during the era of directory submissions and guest post networks, you are working from an outdated playbook. The fundamentals are the same. The signals, the scrutiny and the stakes are not.

This article unpacks where backlinks fit into modern SEO, how they influence AI-driven search platforms, and what a defensible link strategy looks like in 2026.

What backlinks are, and why they still carry weight

A backlink is simply a hyperlink from one website to yours. In SEO terms, it functions as a vote of confidence: another site has decided your content is worth referencing, and search engines treat that endorsement as a signal of authority and trustworthiness.

This logic has powered Google’s PageRank algorithm since the beginning, and while the algorithm has grown vastly more sophisticated, the underlying principle holds. Sites that earn links from credible, relevant sources tend to rank higher, attract more organic traffic, and establish stronger market positions over time.

What has shifted is the tolerance for shortcuts. Early SEO rewarded volume, and a generation of practitioners built sites with thousands of low-quality links from directories, comment sections and link farms. Those tactics now actively harm sites rather than help them. Google’s spam policies, manual actions and the disavow tool have made low-quality link building a liability, not an asset.

Quality over quantity is no longer a slogan

Modern search engines evaluate links on a long list of dimensions, including the authority of the linking domain, the topical relevance of the page, the position of the link within the content, the anchor text used, and the overall pattern of your backlink profile.

“Ten genuinely earned links from respected sources will outperform a thousand from sites no one trusts, every single time.”

A backlink from a recognised industry publication, an established business association, or a credible university carries weight that no scaled outreach campaign can replicate. The numbers game is over, and the reputation game has replaced it.

This has practical implications for how you spend time and budget. Pursuing links should look less like a numbers game and more like a public relations function: targeted, relationship-driven, and built around content worth referencing.

How backlinks influence AI search and GEO

The most significant shift in the past two years is the rise of AI-driven search, and with it, the emergence of Generative Engine Optimisation (GEO) as a discipline alongside traditional SEO.

Platforms like ChatGPT, Perplexity, Google’s AI Overviews and Gemini do not simply return ten blue links. They synthesise answers, cite sources, and decide which brands and websites get mentioned in those answers. The criteria they use overlap heavily with traditional SEO signals, and backlinks remain one of the strongest of those signals.

Three frameworks are worth understanding here:

• Generative Engine Optimisation (GEO): Optimising content so it gets cited and surfaced by AI systems that generate written answers.
• Large Language Model Optimisation (LLMO): Structuring information so large language models can accurately understand, retrieve and represent your brand.
• Answer Engine Optimisation (AEO): Designing content to directly answer the questions users ask, in formats AI tools can lift cleanly.

Across all three, backlinks function as a credibility filter. When an AI system is deciding whether to cite your brand or a competitor’s, the breadth and quality of sites linking to you contributes to that judgment.

“A backlink is no longer just a vote for your page. It is a signal that travels through Google, ChatGPT, Perplexity, Gemini and every AI system trying to decide who deserves to be cited.”

This also reinforces Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness), which has been progressively elevated in recent algorithm updates. Backlinks are one of the clearest external proofs of authoritativeness a website can demonstrate.

Dofollow, nofollow, and what a healthy link profile looks like

Not every link passes SEO authority. A dofollow link tells search engines to follow the link and pass ranking signal to the destination. A nofollow link tells them not to. For years, many marketers chased dofollow links exclusively and dismissed nofollow links as worthless.

That thinking is dated. A natural backlink profile contains both. Nofollow links from major news sites, social platforms and respected publications still drive referral traffic, build brand visibility, and contribute to the overall pattern of mentions that search engines and AI tools use to assess your brand presence. Profiles that are 100% dofollow look unnatural, and unnatural patterns invite scrutiny.

The other dimension worth attention is anchor text, which is the clickable text inside the hyperlink. Well-chosen anchors help search engines understand context. Over-optimised, repetitive, exact-match anchors look manipulative. Variety, including branded anchors, partial matches, and natural phrasing, signals legitimacy.

Monitoring your backlink profile

You cannot manage what you do not measure. Regular monitoring of your backlink profile is essential for protecting the gains you have made and identifying opportunities to grow.

The questions you want to be able to answer at any given time:

• Which sites link to us, and how authoritative are they?
• What anchor text is being used, and does the pattern look natural?
• Are we gaining or losing links over time?
• Have any toxic or spammy domains started linking to us, and do we need to disavow them?
• Which of our content pieces attract the most links, and why?

Tools like Ahrefs, Semrush, Majestic and Google Search Console all provide pieces of this picture. The work is not in running the report. It is in interpreting it, acting on it, and making it part of an ongoing rhythm rather than a one-off audit.

How to build backlinks that actually earn authority

The single most reliable way to attract quality backlinks is to publish content that other people in your industry want to reference. That sounds obvious, and it is also where most link building strategies fall apart, because the content itself is interchangeable with what competitors are publishing.

Tactics that consistently work in 2026:

• Original research and proprietary data. Industry surveys, benchmarking studies, and original analysis are link magnets because they give other writers something to cite.
• Genuinely useful frameworks and tools. Calculators, templates, and decision frameworks tend to attract links from sites teaching the same topic.
• Personalised outreach to relevant publishers. Mass cold email campaigns are dead. Targeted, well-researched outreach to a small number of relevant editors and writers still works.
• Broken link reclamation. Finding broken links on authoritative sites and offering your equivalent content as a replacement is one of the cleanest, most reciprocal forms of link building.
• Expert commentary platforms. Services like Featured, Qwoted, SourceBottle and HARO connect journalists with expert sources. Thoughtful responses earn citations in real publications.
• Digital PR. The line between SEO and PR has effectively disappeared. Earned media coverage drives the strongest backlinks available, and the brand benefits compound.

What unites all of these is that link building is not a campaign. It is a by-product of being genuinely useful, genuinely visible, and genuinely connected in your industry.

“Link building is not a campaign. It is a by-product of being genuinely useful, genuinely visible, and genuinely connected in your industry.”

Competitive backlink analysis

One of the highest-leverage uses of backlink tools is studying your competitors. If a respected industry site links to three of your direct competitors but not to you, that is a clear opportunity. The site has already demonstrated willingness to link to businesses like yours. The question is what content or angle would earn that link.

Competitive backlink analysis typically reveals patterns: industry directories you should be listed in, publications that cover your category, partner sites that link out generously, and content topics that consistently attract citations. Each of those patterns becomes a structured outreach plan rather than a guess.

The long view

Backlinks are not a quick win. They are an investment in long-term authority, and that investment compounds. A site that has spent five years steadily earning quality links is enormously difficult for a competitor to dislodge in six months, regardless of budget.

This is also why backlinks remain such a strong signal for AI search platforms. They are slow to fake, slow to manipulate at scale, and slow to lose. In an environment where AI tools are increasingly deciding which brands to cite and which to ignore, backlinks function as one of the more durable forms of digital reputation a business can build.

For business leaders, the strategic question is not whether to invest in backlinks. It is whether your current approach is building real authority, or whether it is generating activity without compounding value. The two look similar from the inside. Only one of them shows up in your rankings, your AI citations, and your pipeline.

Where to from here

If you have not audited your backlink profile in the last twelve months, start there. Understand what you have, what is helping, and what might be hurting. From that foundation, the question of how to build new authority becomes much easier to answer.

If you would like to talk through how backlinks fit into a broader SEO and GEO strategy for your business, we are always happy to have that conversation. Get in touch and we can map out where the real opportunities sit for you.

Frequently asked questions

Do backlinks still matter for SEO in 2026?

Yes. Backlinks remain one of the strongest signals search engines and AI platforms use to evaluate authority and trustworthiness. The criteria have become more sophisticated, with quality, relevance and naturalness mattering far more than volume, but the underlying importance of backlinks has not diminished.

How do backlinks affect AI search platforms like ChatGPT and Perplexity?

AI search platforms use backlinks as part of how they assess content authority and decide which sources to cite. A site with strong, relevant backlinks is more likely to be referenced in AI-generated answers than one without, even if the on-page content is similar.

What is the difference between dofollow and nofollow links?

Dofollow links pass SEO authority from the linking site to your site, directly contributing to rankings. Nofollow links do not pass authority, but they still drive referral traffic, build brand visibility, and contribute to a natural-looking backlink profile. A healthy profile contains both.

Are low-quality backlinks dangerous?

They can be. Links from spammy, irrelevant or manipulated sites can trigger algorithmic devaluation or, in serious cases, manual penalties. Regular monitoring and the use of Google’s disavow tool can mitigate the risk. Avoiding paid link schemes and link farms in the first place is the better strategy.

How long does backlink building take to show results?

Backlinks are a long-term investment. Some impact can be seen within a few months for newly earned high-authority links, but the compounding benefits typically build over twelve to twenty-four months as authority accumulates and search engines re-evaluate the site’s standing.

What is the most effective way to build backlinks?

The most effective approach combines genuinely useful content, original research or data, targeted outreach to relevant publications, digital PR, broken link reclamation, and expert commentary platforms. Quick-fix tactics like buying links or mass directory submissions consistently underperform and carry real risk.

The post Backlinks in 2026: Why Link Authority Still Wins in AI Search appeared first on HyperWeb.

This article is part of our AI search series. The full picture, with all ten pieces in reading order, is in HyperWeb’s working guide to GEO and AEO.

For most of the past two decades, B2B brand awareness followed a predictable formula: run ads, attend trade shows, get your sales team on the phone. It worked, not because it was elegant, but because buyers didn’t have many other options. Your visibility was largely controlled by your budget.

That era is over.

Today’s B2B buyers do their research long before they talk to anyone. They build shortlists, form strong opinions, and often know who they want to work with before a conversation starts. By the time your sales team gets a call, you may already be in, or already out.

“The first voice they hear isn’t yours anymore. It’s an AI.”

Here’s what most B2B marketers are still underestimating: AI-powered answer engines have become the first stop in the research process. When a procurement manager asks an AI tool what the best approach to a problem looks like, they’re not getting ten blue links. They’re getting a synthesised answer drawn from content the AI considers credible and authoritative.

“If your expertise isn’t structured in a way those systems can extract and cite, you don’t exist in that moment.”

This is why Generative Engine Optimisation (GEO) matters so much right now. GEO means optimising your content and authority to be discovered and cited by AI systems, not just traditional search engines. It is not a replacement for good SEO. It is the next layer. And the businesses that get ahead of it now will have a real advantage over those still optimising purely for traditional search rankings.

Trust has moved from brands to people.

Corporate brand content, the polished case studies and branded whitepapers, carries less weight than it used to. What buyers trust are peer recommendations and domain experts they have come to respect through genuine engagement.

We are not talking about influencers with massive audiences. We are talking about practitioners with smaller, highly engaged followings: people on LinkedIn, in Slack communities, in industry forums, whose opinions are trusted precisely because they are specific and grounded.

“The brand becomes the facilitator of trusted conversations, not just the one pushing content.”

The brands getting this right are not just broadcasting their own messaging. They are amplifying voices their buyers already trust. As we explored in Why B2B Marketing Works Better When You Treat Buyers Like People, companies don’t make purchasing decisions. People do. The brand becomes the facilitator of trusted conversations, not just the one pushing content.

Authenticity isn’t soft. It’s measurable.

Buyers are sophisticated. They can identify generic AI-generated content. They notice when something feels promotional rather than genuinely useful. They disengage.

What builds trust and converts awareness into real pipeline is content that demonstrates actual expertise and doesn’t oversell. Counterintuitively, being transparent about how content was created, including disclosing AI use, enhances credibility rather than undermining it. Buyers want to work with people who are straight with them.

This principle sits at the heart of our approach to AI and application integration: technology in service of genuine value, not as a shortcut around it.

What this actually looks like in practice.

Optimise for GEO, not just search rankings. Create content that directly answers the questions your buyers are asking, structured clearly, with your expertise genuinely extractable by AI systems. Our post on making your content citable walks through exactly how to do this.

Build credibility through practitioner voices. Identify the domain experts your buyers already respect and find authentic ways to collaborate with them. This connects directly to how you approach your digital content and marketing strategy. The goal is authority, not volume.

Participate in the communities where your buyers actually spend time. LinkedIn groups, industry Slack channels, professional forums. The question isn’t whether to be there. It’s whether you’re contributing something useful or just pushing promotional content. One earns trust. The other erodes it.

Measure what actually matters. Reach and impression counts tell you very little. What matters is engagement quality, referral from trusted sources, and whether your content is showing up in AI-generated responses. If you’re not tracking those, you’re flying blind. Our SEO services now incorporate GEO performance as a core metric, so you can see the full picture.

The bottom line.

“Most of your competitors haven’t made this transition yet. That’s the opportunity.”

The brands that win B2B awareness over the next few years won’t be the ones with the biggest budgets. They’ll be the ones who show up with genuine authority at the moments buyers are researching, recommended by voices buyers trust, participating in the right conversations rather than broadcasting at people who’ve learned to tune them out.

Most of your competitors haven’t made this transition yet. That’s the opportunity.

If you want to understand where your business sits in this landscape, we’re happy to walk you through what building genuine authority looks like in your sector, starting with a free GEO audit. Get in touch.

The post The B2B Awareness Landscape Has Changed. Is Your Strategy Keeping Up? appeared first on HyperWeb.