Qantas Asked the Better AI Search Question
Qantas shows why AI search is not just about visibility. The customer still chooses based on trust.
Every brand is about to ask the same anxious question.
How do we show up in ChatGPT?
It is understandable. Customers are using AI tools such as ChatGPT, Perplexity, Gemini, Claude, and Copilot to search, compare, summarise and shortlist. The industry will argue over labels like AEO, GEO and AI search. I’m going to use AI search here because it is the clearest description of the business problem.
AI is becoming a new discovery layer.
That means brands need to understand how they appear in AI-generated answers. But at Adobe Summit Sydney, Qantas made the more useful point.
The better question is not how to get mentioned by an AI tool. The better question is what the human behind the prompt is actually trying to decide.
That difference changes the whole conversation.
Visibility is not preference
The first wave of AI search advice will sound familiar. Track your mentions. Measure your citations. Optimise your content. Understand which prompts surface your brand. Make sure the model knows who you are.
Some of that will matter.
But showing up in an AI answer is not the same as being chosen. It is closer to making the consideration set. That is still useful, but it is not the whole game.
If a customer asks an AI assistant for a shortlist of airlines, insurers, universities, consultants, accounting platforms, CRM tools or project management software, a brand would rather be in the answer than outside it.
But the AI answer is not the customer.
The model may summarise the market. It may point the customer in a direction. It may collapse several searches into one answer. But the human still has to decide whether to trust what they have been given.
That is where the AI search story gets more interesting.
Qantas asked the better question
Gerrit Walters, Head of Design, Digital Experience & Performance for Qantas said the wrong question is to ask how to get mentioned more in AI Search. That is an inside-out question. It starts with the brand’s anxiety rather than the customer’s job.
The better move is to think about the person asking the question.
What are they trying to do? What would make their day easier? What evidence would help them decide? What would make them doubt the first answer? What else would they check before buying?
That is the part most AI search commentary is going to miss.
A customer does not suddenly stop being a customer because an AI tool helped them search. They still compare. They still check reviews. They still ask whether the brand is reliable, risky, premium, cheap, useful, credible or likely to disappoint them.
The AI answer may change the path.
It does not remove the human judgment at the end of it.
The brand moves into the context layer
Traditional digital marketing has spent years managing the content a brand publishes. Website pages. Landing pages. SEO copy. Product feeds. Campaigns. Social posts. Reviews, where the brand can influence them. Help content, where the brand remembers to maintain it.
AI search changes that because the answer is not just a link to your content. It is a synthesis of the context around your brand.
That context may include your website, reviews, forums, product documentation, press coverage, comparison pages, social posts, customer complaints, third-party rankings, creator commentary and whatever else the model can retrieve or infer.
That means the marketing job shifts.
It is no longer just about managing the message. It is about managing the evidence environment around the brand.
That is a much harder task. It is also a more honest one.
Google made brands compete for clicks.
AI search makes brands compete for confidence.
AI search needs a measurement layer
There will be a rush to understand how brands appear in AI-generated answers.
Some of that work will be useful. Brands should know whether they are showing up, what the answer says, where the model appears to be pulling evidence from, and whether the information is accurate.
Adobe is clearly building for this market, with Brand Visibility, LLM Optimizer and Semrush now part of the picture. The important next step is connecting that visibility back to commercial outcomes.
For Qantas, that means not just whether the brand appears in an AI answer, but whether that journey eventually helps someone book a flight, hotel or holiday, and whether the signal flows into the systems that measure the outcome.
That is where the category gets serious.
Until then, the usual caution applies. Mentions are not revenue. Citations are not trust. Share of AI answer is not the same as customer preference.
The CMO question is not whether the brand appears in ChatGPT. The CMO question is whether AI-mediated discovery changes commercial outcomes.
Does it drive qualified traffic? Does it improve conversion? Does it shift consideration? Does it reduce acquisition cost? Does it help existing customers make better decisions? Does it surface the brand accurately when the stakes are high?
Without that link back to the business, AI search visibility risks becoming another dashboard for marketing anxiety.
Executives should expect to hear a lot more about this category. They should also ask harder questions before treating it as a strategy.
The old fundamentals get more valuable
The interesting thing about the Qantas framing is that it does not make old brand work irrelevant.
It makes it more important.
If AI tools summarise the market by drawing from many sources, then the quality of the underlying business matters more, not less. Product quality matters. Service experience matters. Pricing clarity matters. Accessibility matters. Reviews matter. Support content matters. Reputation matters.
This is not just a B2C issue.
In B2B, the same pattern applies. A buyer might use an AI tool to shortlist vendors, compare categories, draft an RFP, summarise analyst reports or understand implementation risks. But the buyer still has to trust the vendor enough to put budget, reputation and operational risk behind the decision.
The AI answer may accelerate discovery.
It does not eliminate procurement, proof, politics or accountability.
For leadership teams, that means AI search is not just a marketing issue. It touches customer experience, product, support, communications, reputation, sales enablement and risk.
The answer a model gives about your company may be a marketing moment. The reasons it gives that answer are often operating issues.
The useful stoic idea
Walters also reached for an old stoic idea, often paraphrased through the Serenity Prayer:
Know what you can change, know what you cannot, and have the wisdom to tell the difference.
That is a useful way to think about AI search.
A brand cannot control exactly what every model says about it. It cannot control every forum post, review, comparison, complaint or third-party summary. It cannot force a customer to trust the first AI-generated answer.
But it can influence the evidence.
It can make its own content clearer. It can fix inaccurate information. It can improve the customer experience that generates reviews. It can reduce support friction. It can make product claims easier to verify. It can build a reputation that survives the summary layer.
That is the practical work.
Not gaming the model. Making the brand easier to trust when the model points at it.
The CMO takeaway
AI search matters. Brands should not ignore it.
But the wrong response is to treat it as SEO with a new coat of paint. The better response is to treat it as a pressure test of the brand’s wider evidence base.
If customers are asking AI tools what to buy, who to trust, which provider is reliable, or which option best fits their needs, the model is not just looking for your preferred message. It is looking for signals.
That should make executives uncomfortable in a useful way.
Because the question becomes bigger than: do we rank?
It becomes: what does the market actually know about us, and would we trust the answer if we were the customer?
AI search is not the customer.
It is the new middle layer.
The customer is still human. The decision is still about trust. And the brands that win will be the ones with the strongest evidence, not just the best prompt strategy.
Disclosure: Adobe invited me to Adobe Summit Sydney and covered travel and accommodation. Adobe had no editorial review or approval. I’m interested in practical AI stories, not vague transformation language or paid placement. Pitch one here.