Infokus Marketing and AI Agency

Infokus research · 2026

Readable, not reputable

What the evidence actually shows about how AI assistants choose which businesses to recommend, and how much of the advice you are being given has never been measured.

Every figure here is traced to a named primary source and dated, and the sources are listed in full at the end. Where the research contradicts itself, we say so. Where the honest answer is that nobody knows yet, we say that too. Australian data used wherever it exists.

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01 Infokus research · 2026

Most of what you have been told about AI search has never been measured

There is a great deal of confident advice circulating about how to get your business recommended by ChatGPT, Perplexity and Google's AI. Very little of it is supported by evidence, and a surprising amount of it is supported by figures that do not trace back to any real study at all.

We went looking for the evidence. Every statistic we intended to use was checked against its original source, and roughly a third were discarded, either because no primary source existed at all or because the figure had been superseded and nobody had noticed. What follows is what survived that check.

This is not a report that will tell you AI search is about to replace everything you do. The honest picture is more interesting than that, and considerably more useful. Referral volume from AI platforms is still small. Influence is not. The gap between those two facts is where the opportunity sits.

Four findings that shaped this report

Select any card for the context behind the number.

02 The shift

Australians have already changed how they look for answers

Seventeen point four million Australians aged sixteen and over now use AI. That is seventy seven per cent of the adult population, and daily use has grown by one hundred and sixty per cent in a single year. This is not an emerging behaviour. It is the current one.

The number that matters most for your business is smaller and sharper. Twelve per cent of Australians now name an AI tool as their primary way of finding information online. Not one option among several. The first place they go.

What happens next is the part most businesses have not absorbed. When an AI summary appears at the top of a search, people stop clicking. Pew Research Center tracked real browsing behaviour rather than asking people what they thought they did, and found that users clicked a traditional search result on eight per cent of visits where an AI summary was present, against fifteen per cent where it was not. Roughly half the clicks, gone. Only one per cent clicked a link inside the summary itself.

The bigger picture

Put those together and you get the defining feature of this shift. Your business can be read, summarised and described to a potential client without that person ever visiting your website. You may be recommended, or passed over, in a conversation you never see and cannot measure in your analytics.

That is a genuine change in how reputation travels. It is also why measuring AI visibility by looking at your referral traffic will tell you almost nothing.

The honest counterweight

Traffic referred from AI platforms was still only about zero point two per cent of total site visits across 2025, converting at one point three per cent, which is below email. Anyone presenting AI referral as a channel with meaningful volume today is overselling it.

The case for acting now is not referral volume. It is that you are being described to buyers whether or not you have any say in it, and the businesses establishing readable, consistent signals now are the ones those descriptions will be built from later.

03 What actually gets cited

Ranking well on Google and being cited by AI are different problems

This is the finding that reframes everything, and it comes from two independent datasets that agree.

Ahrefs analysed fifteen thousand queries and found that only twelve per cent of the URLs cited by ChatGPT, Gemini and Copilot appeared in Google's top ten for the same prompt. Around eighty per cent of citations came from pages ranking outside Google's top one hundred entirely. BrightEdge, working from a completely different keyword panel, found that roughly seventeen per cent of Google AI Overview citations came from pages ranking in the organic top ten. Two methods, two datasets, the same conclusion.

Where the research disagrees

A separate study by Kurt Fischman found the apparent opposite: that pages ranking first in Google were cited in forty three per cent of the queries they appeared in, falling to five per cent by position seven. Ranking, it concluded, dominated citation behaviour.

Both findings are true, because they measure opposite directions of the same relationship. Ahrefs asks what share of AI citations rank top ten, and the answer is low because AI draws from a very wide pool. Fischman asks what share of top ranked pages get cited, and the answer is high because ranking well is a strong individual predictor. The useful synthesis is that ranking improves your odds considerably, but it is neither necessary nor sufficient. Anyone quoting only one of these numbers is telling you half a story.

So what does correlate

Ahrefs measured seventy five thousand brands against their visibility in AI answers. The pattern is consistent and it is not the one most marketing plans are built around.

What correlates with being visible in AI answers

Spearman correlation with AI brand visibility across 75,000 brands. Higher is stronger.

00.20.40.60.8
Source: Ahrefs, December 2025, 75,000 brands filtered to Domain Rating above 40. Where the study reported a range across platforms we have plotted the lower bound. Backlink count is shown as negligible because the study reported it as minimal without publishing a coefficient, so no number is plotted. Correlation is not causation, and the Domain Rating filter means these findings describe established brands rather than firms starting from zero. Ahrefs sells a brand mention tracking product, which is worth holding in mind when reading a result that favours brand mentions.

Being described elsewhere on the internet correlates far more strongly with AI visibility than any link based measure. Backlinks, the currency of twenty years of search optimisation, sit close to negligible.

For a professional services firm this is unusually good news, because being described elsewhere is something you can genuinely influence. Podcasts, industry publications, association directories, partner sites, conference listings, credible profiles with your name attached. That is the work.

The businesses being recommended are not necessarily the best ones. They are the readable ones.

04 Why one answer proves nothing

Ask the same question twice and you get a different answer

This is the part of AI visibility that almost nobody discusses honestly, and it is the reason most AI ranking tools are selling you false precision.

Research published in June 2026 measured how much the citation sets overlap when the identical query is run repeatedly on the same platform. On Gemini, the median overlap sat between zero point two nine and zero point three one. In plain terms, two runs of the same question share under a third of their cited sources. On OpenAI's search product it ran between zero point three three and zero point four. Perplexity, the most stable of the three, managed zero point five.

"best commercial lawyer Newcastle"

An illustration of the pattern the research describes. Three runs, same question, same platform, same day. Letters represent distinct cited sources, and the highlighted one is the only source present in every run.

Run 1
source Asource Bsource Csource D
Run 2
source Asource Esource Fsource G
Run 3
source Asource Dsource Fsource H
1 of 8 distinct sources appeared in all three runs. A single test would have reported whichever run you happened to make as "the" answer.

The instability is not confined to individual queries. Semrush tracked citation sources across two hundred and thirty thousand prompts over thirteen weeks and watched Reddit's share of ChatGPT citations fall from close to sixty per cent to around ten per cent in roughly six weeks. Wikipedia fell from fifty five per cent to under twenty in the same window.

Two independent bodies of evidence, one academic in style and one commercial in scale, both showing severe instability. Any tool that hands you a single AI visibility score from a single test is reporting noise with a decimal point on it.

Being straight about our own method

We run every query three times per platform and report frequency rather than a single result. Cited in two of three runs, not simply cited. That is materially more reliable than one test and it is how we score every client.

It is not statistical certainty, and we will not claim it is. The same research that exposes single run measurement as unreliable also indicates that full stability needs far more observations than any agency could run by hand. Three runs reduces noise. It does not eliminate it. We report the variance rather than hiding it, which is the part that actually matters.

What we measure instead of a single number

Because citation presence is volatile, we do not lead with it. We build the picture from four layers, most stable first, so that a quiet quarter on the volatile layer never obscures the work that is genuinely moving.

Layers one and two are almost entirely within our control and carry no noise. Layer three is the one everyone wants and the one that moves unpredictably. Layer four is the only one that pays the bills, and it is the hardest to attribute, which is precisely why we ask every new client whether they used an AI tool while researching us.

05 The trade-offs

Three tensions nobody selling this work wants to put in writing

Every approach to AI visibility involves a trade-off. Being clear about them is the difference between a strategy and a wish.

"How do we get ChatGPT to recommend us?"

"Can a machine read who we are, what we do and why we are credible, consistently enough to describe us accurately when someone asks?"

The second question has an answer you can actually work towards, and the work holds its value regardless of which platform is ascendant next year. The first question invites you to chase a system that changes weekly.

06 The readiness diagnostic

Six questions that tell you how readable your business currently is

This is not a visibility test. It cannot tell you whether AI mentions you, and any tool claiming to do that from six questions is not being straight with you.

What it does measure is structural readiness: whether the signals AI systems rely on are present, consistent and attributable. Readiness is the part you control, and it is the part that has to be right before any measurement is worth taking.

Answer honestly. Nothing is stored or sent anywhere.

Interactive · 2 minutes

0 of 6 answered

07 What to do next

Three starting points, depending on where you actually are

There is no single sequence that suits every business, and a generic checklist would be the same unmeasured advice this report set out to correct. Choose the description that fits you now.

08 Where this goes

The advantage will belong to the businesses that can prove it

Three things about the next eighteen months look reasonably safe to say.

The platform mix will keep moving. ChatGPT's share of generative AI web traffic fell from roughly seventy six per cent to fifty three per cent in twelve months while Gemini rose from under nine to around twenty seven. Any strategy built around optimising for one assistant is already dated.

Assistants will cite more, not less. The share of ChatGPT responses containing citations rose from one point six per cent to six point eight per cent across a single year. Professional services remains the least cited sector at under four per cent, which is inconvenient and worth knowing before you read a thin result as a failure. The direction of travel is clear enough.

And measurement will become the differentiator. As more businesses invest in this, the question stops being whether you did the work and becomes whether you can show what changed. That requires a baseline taken before the work started, the same queries run the same way every quarter, and the discipline to report the quarters that went sideways as plainly as the ones that went well.

The firms that do well here will not be the ones that chased the most citations. They will be the ones who knew what they were building, and could prove what moved.

Everything in this report will need revisiting. The research is young, some of the best studies are preprints, and several of the figures here will be superseded within the year. We will update it when they are, and we will say what changed.

Find out what AI actually says about you

The AI Visibility Audit runs ten queries built from your services, location and brand across Perplexity, ChatGPT, Google AI Overviews and Microsoft Copilot. Three passes each, one hundred and twenty scored observations, every result screenshotted. Then the part a dashboard cannot do: a teardown of who is being cited instead of you, and specifically what they have that you do not.

$990 plus GST, fixed. Credited in full against the Advertise to AI program if you proceed within thirty days.

Infokus Marketing and AI Agency

Sources

Every figure in this report traces to the source listed below, with the date of the data rather than the date of publication where the two differ. Figures we could not verify to a primary source were excluded, including several that circulate widely.

  1. Telsyte, Australian Digital Consumer Study, June 2026. Fieldwork April to May 2026, n=2,023, aged 16 and over. telsyte.com.au
  2. Pew Research Center, Google users are less likely to click on links when an AI summary appears, July 2025. Observed browsing data, March 2025, n=900 US adults, 68,879 searches. pewresearch.org
  3. Ahrefs, AI search overlap study, August 2025, updated May 2026. 15,000 long-tail queries. ahrefs.com
  4. BrightEdge, AI Overviews one year on, February 2026. Enterprise keyword panel across nine verticals. brightedge.com
  5. K. Fischman, Determinants of AI citation behaviour, SSRN preprint, April 2026. 730 citations across 75 commercial queries. Not peer reviewed. ssrn.com
  6. Ahrefs, AI brand visibility correlations, December 2025. 75,000 brands, Domain Rating above 40. ahrefs.com
  7. Ahrefs, Does schema markup increase AI citations?, May 2026, updated June 2026. 1,885 treated pages against 4,000 matched controls. ahrefs.com
  8. R. Sielinski, Quantifying Uncertainty in AI Visibility, arXiv:2603.08924, June 2026. Preprint, author affiliated with an AI visibility vendor. arxiv.org
  9. R. Sielinski, From Stochastic to Stable, arXiv:2607.10341, July 2026. Preprint. arxiv.org
  10. Semrush, Most cited domains in AI, November 2025. 230,000 prompts, 100 million citations, 13 weeks. semrush.com
  11. Semrush, AI Visibility Index, June 2026. 126 million US prompts, January to April 2026. semrush.com
  12. Similarweb, Generative AI statistics, July 2026. Data June 2025 to May 2026, panel based, web visits only. similarweb.com
  13. Contentsquare, 2026 Digital Experience Benchmark, April 2026. 99 billion sessions across 6,500 sites. contentsquare.com
  14. Seer Interactive, AI Overviews and CTR, November 2025. 3,119 informational queries across 42 organisations. searchengineland.com
  15. National AI Centre and Fifth Quadrant, SME AI Pulse, May 2026. Australian Government, minimum 400 SME decision makers per wave. ai.gov.au
  16. HTTP Archive, Web Almanac 2024, Structured Data, November 2024. Automated crawl census. No 2025 or 2026 edition of this chapter exists. almanac.httparchive.org
  17. SparkToro and Similarweb, Zero-click search analysis, June 2026. US data, January to April 2026. sparktoro.com

Infokus Marketing. Prepared August 2026. This report will be revised as the underlying research is updated or superseded.