AI Search in Australia: What Brands Need to Know in 2026

For most of the internet era, online discovery followed a familiar pattern.

Someone had a question. They searched Google. Google returned a list of links. The customer opened a few, compared their options and decided where to go next. That journey is changing. People can now ask ChatGPT to recommend a protein powder for a sensitive stomach, ask Gemini to compare accounting platforms for a growing business, or use an AI-powered search experience to research the best dog food for a particular breed.

Instead of simply pointing people towards information, AI can help interpret the question, research the options and narrow them down. For brands, that creates a new question:

When a potential customer asks AI what to buy or who to use, are you part of the answer?

From finding information to making decisions

The significance of AI search is not that traditional search is disappearing. It isn't. Google remains enormously important, and Google itself says that the fundamentals of SEO continue to apply to its generative AI search experiences. What's changing is what can happen between a question and a decision.

Consider someone looking for a new protein supplement.

A traditional search might begin with:

The customer receives a page of results. They open articles, visit retailers, read product pages and compare brands.

Now consider the same person asking an AI assistant:

That is a much richer question. The AI can interpret the requirements, research relevant information, compare alternatives and return a much smaller set of options. The customer hasn't necessarily stopped searching. But part of the work involved in evaluating the market has been moved upstream.

That difference matters because brands can now be filtered into or out of consideration before a customer visits their website.

This is already happening

The scale of the shift is becoming difficult to ignore. OpenAI has built dedicated shopping experiences into ChatGPT that allow people to describe what they need, compare products and refine recommendations conversationally. OpenAI says hundreds of millions of people use ChatGPT to find, understand and compare products.

Google is moving in the same direction. AI Mode has surpassed one billion monthly users globally, while AI Overviews now reaches more than 2.5 billion monthly users. Google is also building conversational shopping and agentic commerce directly into Search and Gemini.

The resulting traffic is beginning to show up in commercial data.

Adobe Analytics found that traffic from generative AI tools to US retail websites increased 693% year on year during the 2025 holiday season. More importantly, those visitors were not simply curious browsers. By that period, AI-referred retail traffic was converting 31% better than other traffic sources in Adobe's dataset.

Earlier Adobe consumer research also found people using generative AI for product research, price comparison and tailored recommendations. Research-intensive purchases showed particularly strong adoption. Most of the large-scale public data still comes from the United States, so it would be a mistake to simply apply every percentage to Australian consumers.

But the underlying products are global, the behaviour is increasingly built into the world's largest search and AI platforms, and Australian brands are competing inside many of the same interfaces. The question for Australian marketers is no longer whether AI-generated answers exist. It's what happens to their brand inside them.

Visibility means something different when the result is an answer

Traditional search marketing has developed a mature set of measurements. Rankings. Impressions. Click-through rates. Organic sessions. Share of search. AI answers don't fit neatly into that model.

Imagine a customer asks:

An AI assistant might recommend four brands and explain why each could suit the customer's needs. For those four brands, appearing in the answer has value even if the customer doesn't immediately click anything. For every relevant brand that wasn't mentioned, there is a different problem.

They weren't simply ranked lower on a page.

Three questions brands should start asking

At InView, we think AI visibility begins with three fairly simple questions.

1. Are you being recommended?

When someone asks a relevant, unbranded question about your category, does your business appear? We call the frequency with which this happens your Recommendation Rate.

The number is useful because it turns something that can otherwise feel anecdotal into something measurable. Asking ChatGPT about your brand once tells you very little. Testing a consistent set of realistic buyer questions starts to reveal patterns.

2. Who is being recommended instead?

Visibility only becomes commercially meaningful when viewed in context. A 25% Recommendation Rate could be strong in one category and weak in another. If your closest competitors appear 8% of the time, you may be performing well. If they appear 60% of the time, the same score tells a very different story.

This is why competitor visibility matters. AI search doesn't just create a new place for your brand to appear. It creates another environment in which your competitors can become more visible than you.

3. How is your brand being represented?

Being mentioned is not always the same as being represented accurately. An AI system might misunderstand what you sell, associate you with the wrong market, overlook an important product, use outdated information or recommend you for some use cases while missing others entirely.

First: Do AI systems know you?

Then: Do they understand you well enough to recommend you at the right moment?

Why one ChatGPT search isn't enough

It is tempting to test AI visibility by opening ChatGPT, typing a few questions and seeing what happens. That's useful as a starting point. It isn't a measurement system. The wording of a question matters. The context provided by the user matters. Different AI platforms can use different models, retrieval systems and information sources. Results can also change as the underlying models and web evolve.

Google explicitly notes that its AI Mode and AI Overviews can use different models and techniques, which means the responses and links they surface can vary. ChatGPT shopping recommendations can also incorporate the user's query, conversational context, product metadata and third-party information.

There is no single permanent answer to "where does my brand rank in AI?" The more useful question is:

Across a consistent set of relevant buyer questions, what patterns emerge?

AI visibility isn't simply "SEO for ChatGPT"

A new collection of terms has emerged around this change: GEO, AEO, LLMO, AI SEO and others. There is also a temptation to treat AI visibility as an entirely new discipline with a completely new set of optimisation tricks. Google says its existing SEO fundamentals remain relevant to AI Overviews and AI Mode. It specifically recommends useful, reliable content, crawlability, internal linking, good page experience, accurate structured data and up-to-date merchant and business information. Google also says there is no special AI schema or machine-readable file required to appear in its generative search features.

OpenAI's own shopping documentation points to product metadata, merchant information, third-party content, price, reviews and other contextual information as inputs that can affect which products are surfaced. In other words, much of what makes a brand understandable and credible on the web still matters.

But the outcome we're trying to influence is different.

The brands with the most to gain

AI visibility won't matter equally to every business. The clearest early use cases are categories where customers naturally ask for recommendations, comparisons or advice before buying.

Think:

These questions contain context, trade-offs and intent. They are exactly the kinds of questions conversational AI is designed to handle well. And commercially, they matter because the person asking isn't merely looking for information. They're narrowing down what to buy.

What should marketers do now?

There is no reason to panic, abandon SEO or rebuild your entire marketing strategy around an acronym. There is a reason to start paying attention. First, understand whether AI systems can accurately identify your brand, products, category and positioning. Second, test the real questions customers might ask when they are researching your category.

Third, look beyond your own brand. Understand which competitors appear repeatedly and which questions they seem to own. Fourth, examine the information available across your website and the wider web. If your product positioning is unclear to a human reader, it is unlikely to become clearer when an AI system has to synthesise information from multiple sources.

Finally, establish a baseline. The useful question six months from now won't be whether AI search became more important. It will be whether your visibility improved while it did.