What Is AI SEO? A Practical Guide for Australian Businesses

Someone trying to organise a dinner party tells an assistant that they are looking for somewhere to book in their suburb. They have a certain number of people to feed, a budget to stick to and a number of dietary requirements. A purchasing manager looking for fabric of a certain composition, process and usage wishes to know suppliers able to fulfil their terms of supply. They then compare the results returned from the assistant's searches for manufacturers.

Whether your customer's decision is affected by the AI response or not, SEO and GEO are channels for customer acquisition that warrant investment, just like your advertising and social media efforts. However, we have no like-for-like data to compare the two and therefore don't claim that one converts over the other.

Much of our work is conducted in English and is not restricted to Australian commerce.

This work has one practical task: be found by potential customers researching competition and be able to verify that work brings in business.

In general, SEO, AI SEO and GEO are referred to in an overlapping manner by the industry and so in this site, we refer to SEO in terms of ranking pages in search results, AI SEO in terms of obtaining AI search results and GEO in terms of the work we do in this area. Our comparison of GEO vs AEO vs AI SEO sets the terms side by side, and a separate guide explains what generative engine optimisation is.

One thing to note about how we work: Our service is for the whole of your website and its content. We are talking about 'AI SEO' as used by ourselves. This is not a plugin. And most definitely not for producing loads of blogs.

They do not share one algorithm. Google says AI Overviews and AI Mode may use a "query fan-out" technique that runs several related searches. OpenAI says ChatGPT search typically rewrites a question into one or more targeted queries.

There are four outcomes that people tend to confuse. A page is found, a page is listed as a source, a page's content is used in the answer, and the business is recommended in the answer.

Just because you can view a page online does not mean that the AI has read it. We examine the structure and crawl checks in the next section. For more on the mechanics, see how AI systems choose brands to recommend.

Check the structure before adding more content

Of course we inspect your website for structure, content, external links and internal links prior to inspecting your blog, social media channels and videos. Each problem is rated for severity and once we have taken on a project for you we go through each problem one by one, diagnosing and then implementing the necessary solutions. That order is how we organise the work. It is not advice to stop blogging.

Give buyers clear product and service information

The content on your product pages should be a straightforward, plain text description of the product. This will mean listing out the composition, full specifications, suggested uses, and any previously agreed trading terms. Importantly, the basic facts about a product should not be withheld from potential customers for a sales conversation.

Use blogs to explain what makes the business knowledgeable

A good blog post is essentially a piece of you speaking to camera about something that you want to talk about. A new material in a current best seller, the technology behind a recent improvement in performance, new features of current products or new processes in the factory can all be of interest. The blog post explains what it means for the customer and links to the relevant products and a way to enquire.

Start with product evidence, then add industry context

Product facts come from the client. We work off the product material and the technical notes from the factory. Industry material is used to explain the principle behind a material and add background. Research potential of a material is not written up as proven performance of a product.

Make expertise traceable across the website

Clear heading levels, relevant internal links, consistent business information and citations a reader can follow all help people understand the business. External write-ups and genuine reviews help as well. More links do not guarantee a recommendation.

Are the three criteria for a post to go live met: 1) the post contains new information about a topic that the author is knowledgeable about, 2) the author's claims are backed up by data and articles that can be cited, and 3) the post covers a topic of interest to the reader? If so, the reader can use the post to solve their problems, and AI systems can verify that we are not misrepresenting information.

The full sequence of steps is in the seven-step LLM SEO framework.

Orange Textiles is an export website our team helped build and optimise. It supplies finished knit fabrics from Shaoxing, China, to apparel buyers overseas, so it is not an Australian business. The work shows how product material becomes website content:

• The article numbers, composition, weight and width in the fabric catalogue were organised so buyers can compare fabrics.
• Buying guides were extended from existing product material.
• The blog and the product categories were given entry points a crawler can follow.
• Structured data that did not match what the pages showed was corrected.
• Reading, product selection and enquiry were connected, including a custom development page for buyers with their own brief.

The blog was created from the same product material as the individual product pages. Subsequent enquiries with potential buyers are dealt with by the client's own sales team.

We do not claim that individual changes created orders or grew business in some way. There are no statistics about growth here.

Layer 1: Observe web-connected answers to find what to compare against

First we identify a set of questions confirmed with the client, then we expand on them. We then "lock down" this set to run it repeatedly against a fixed model / version, recording which websites return and in what order. We log dates, question versions, model details and answers. The websites that a model returns become our comparison set. A single change in ranking is not an improvement. We run these tests using the model's APIs, not the consumer facing apps.

Layer 2: Test the change with brand and domain hidden

We hide brand and domain clues and test the client's content and the comparison content through a fixed test process. We track whether the content was found, entered the context the model answers from, was used in the answer and meets the requirements. Competitor page snapshots and other conditions will remain fixed and only registered variables will be changed. Brand mentions do not count in this stage. Hiding the brand removes most obvious identity clues, although not all.

One experiment changed how we work. Swapping in the words buyers use, without adding anything specific about delivery, was recorded as ineffective. Separately, inserted text could change how a page was split into chunks, so a heading or paragraph that had been working fell outside the fragment the system read. Only then did we start checking chunk boundaries and where content enters the context. That was one internal experiment under specific conditions, not a rule for every AI platform.

Layer 3: Watch commercial results after the change goes live

Real AI answers, search appearance, visits, enquiries and orders need to be recorded separately. Before-and-after comparisons have to be based on valid test results gathered under the same conditions. Failed runs must also be recorded. Client feedback, website evidence and internal tests are all different types of proof and none can be substituted for another. A better result in a test does not necessarily mean better rankings on live platforms and this does not necessarily translate into revenues.

Our guide on how to measure AI search visibility defines the measures, and AI visibility tracking covers the ongoing record.

Buyers often ask, "If we already rank on page one, what does optimising for AI answers add?" Being ranked in search results does not automatically mean that your website will be cited or even recommended by AI-powered answers on the web.

The importance of tracking how people use AI to search for information is growing as more and more people use AI. We do not guarantee that your web pages will remain in the top ten forever, that they will be recommended by all models, or that they will generate a certain amount of sales.

1. Write down how customers would look for your product or service.
2. Gather your product material, technical notes and the evidence you already have.
3. Check whether your website presents that information clearly, and record a starting point that later results can be compared with.

If you would like this done for you, AlphaX can take on the checks, the fixes, the content work and the retesting as one engagement. The usual first step is an AI search visibility audit, and our AI SEO services in Australia page describes the wider service.

The aim of AI SEO is that customers who research on their own can find a clear and accurate account of your business.

• Google Search Central, "AI features and your website": how AI Overviews and AI Mode draw on Search, what makes a page eligible, and why appearance is not guaranteed. https://developers.google.com/search/docs/appearance/ai-features (checked 10 November 2026)
• OpenAI Help Center, "Searching the web with ChatGPT": when ChatGPT searches the web, how it rewrites queries and how citations are shown. https://help.openai.com/en/articles/9237897-searching-the-web-with-chatgpt (checked 10 November 2026)
• AlphaX internal testing: experiments run through model APIs under fixed conditions. Question sets, raw answers and figures are not published.
• Orange Textiles: details taken from the public website at https://orangetextiles.com/ (checked 10 November 2026).