Whether you’re sick of hearing about AI, or can’t get enough of the machine overlords, AI is now an undeniable element of SEO.
Initially, when AI became a part of SEO, specialists like The Marketing Optimist, had to use our experience and intuition to navigate SEO for AI search. The AI lords weren’t handing out handy guides like this one. Now in May 2026, as the change curve has flattened somewhat, Google and the industry’s leading SEO specialists have published studies and articles highlighting a clear approach.
It just so happens to be the one we’ve been using the whole time – “Stick with the same SEO playbook as before” (in the words of Bing’s Product Manager speaking on their partnership with open AI)
In this guide to SEO for AI search we’ll break down what AI search is and why it’s important, the key considerations for SEO’s (or those optimising their website content for AI search), and the best approach to take.
Let’s jump in, shall we?
What is SEO for AI Search? & Why Should You Care?
AI search engines are search tools, similar to Google etc, but powered by AI, leaning on natural language processing, machine learning and large language models.
It’s claimed that AI search engines are capable of deeper understanding, and are therefore more thorough and effective in providing you with the most appropriate query-specific responses. If optimised of course.
SEO for AI search is the process by which content is optimised for these search engines, which don’t just use keyword-based indexing, but also analyse the context, intent and semantics of the search query/prompt to return more tailored responses.
According to a 2026 study by Search Engine Land, 37% of consumers start searches with AI search engines. A significant figure right? That’s why you need SEO specialists experienced in SEO for AI search.
Google AI Search Feature Optimisation
When it comes to SEO for Google AI search (their generative AI features such as AI Overviews and AI Mode), Google published a guide stating that traditional SEO best practises still fully apply, because their generative AI features are still rooted in the core search ranking and quality systems used to rank traditionally optimised content.
According to Google, best practices remain:
- Create valuable, non-commodity content for your audience
- Build and maintain a clear technical structure
- Optimize your local business and ecommerce details
For a list of what you don’t need to do, you can view this section of Google’s guide.
Speaking of traditional best practices, you can explore our guides to the key factors of traditional optimisation via our: Guide to Keyword Research, Guide to Content and Page Optimisation & Guide to SEO Reporting.
SEO for AI Search Engines
Fundamentals:
Traditional crawling and indexing remains ubiquitous across both traditional and AI search, and the tried and true methods of enabling bots to crawl content are consistent for AI search also. While you may not have had to consider AI bots before, avoid blocking them as this is a sure fire way to not appear in their search results.
Content & Content Optimisation:
Regularly adding new and improving existing optimised content is key to conducting SEO for AI Search. Now more than ever, SEO is not a set and forget it project, it’s a living process.
Content AI optimisation best practices are consistent with traditional methods. Keyword selection, market and audience understanding (in terms of search behaviour), appropriately crafted copy (that balances keyword placements with semantic relevance), and content and page optimisation applied in line with traditional SEO.
Schema tags are also a valuable addition to the technical SEO for AI search process. They help signal to search engines exactly what it is they’re looking at, to help them index, structure and rank the content. They’re also a key factor in helping you appear in Google SERP features above organic results.
Optimising for AI Search (A Somewhat Reductive Look at the Process)
To gain a full understanding of the full optimisation process from keyword research to reporting, read our guides:
Otherwise, here’s a quick and dirty look at the features of SEO for AI search (and traditional optimisation as a whole):
Keyword Research
- Audit
- Keyword research with search metrics and search intent
- Note who is competing for each term, whether the competing content is a blog or a page, and how they’re generally optimising for the term (SEO titles etc)
- Map keywords to your website architecture
Content Optimisation
- Assess competitor content related to each key term (via SEO tools, like Moz).
- Create a plan/discovery document and have it populated by appropriate knowledge leads in your organisation.
- Content writing (in documents)
- Proof reading
- Eventual update and adaption of optimised content
When it comes to SEO for AI search, FAQ sections, and utilising real-life longer tail queries and answers in your content is a very helpful tactic.
Page Optimisation
- Populate web page with your content
- Optimise your titles (H1) and subtitles (H2)
- Optimise Alt text
- Add internal and outbound links
- Optimise the page URL
- Add an optimised meta description and SEO title
- Develop a plan to build incoming links (speak to our team about Digital PR)
SEO Reporting
- Monthly keyword rankings reporting
- Monthly web analytics data from GA4 and Google Search Console
Need Some Help?
Of course, like all areas of SEO and marketing generally, things change, and at The Marketing Optimist, we have our fingers on the pulse to help you remain competitive in spite of a changing SEO landscape.
If you’ve gotten to the end of this blog, and have more of a grasp on SEO for AI search, but need some help to tackle the lengthy process, contact our team today.
We offer a full SEO service covering strategy, keyword research, copywriting, content optimisation, page optimisation, reporting and technical SEO.
Beyond SEO, we can all support you with marketing strategy, social media marketing, website design, and digital PR.
