SEO in 2026

Damien Robert explains the need to move beyond traditional web content, achieved by making content modular, leading with irrefutable evidence. In addition, he recommends managing all assets from a single source of truth to please both humans and AI consumption.

Damien says: “Re-order your content to future-proof your search dominance.”

Mark Williams-Cook explains that you also need to consider the type of search that you’re attempting to optimize for, and the way that AI engines deal with different types of searches.

Mark says: “Everyone should be determining whether their AI searches need grounding or not.”

Jason Barnard shares that you can’t look at LLMs alone as the standalone way to determine whether or not your AI optimization has been a success.

Jason says: “I'm going to explain how any marketer can optimize for AI-assistive engines.

People call it generative engine optimization; I call it AI-assistive engine optimization. Whichever name you use, the principle to SEO in the AI era is very simple, and it's called the Algorithmic Trinity.”

Garrett Sussman shares that, even though there is great opportunity in being included in AI search results, results aren’t guaranteed.

Garrett says: “Treat AI search as probabilistic, not predictable.

Build content strategies rooted in deep audience understanding, because what shows up in search results depends on who's searching and how they search.”

Katie New shares the importance of tracking metrics that actually matter to you in 2026 (not just the default ones that you're used to asking for!) Talking points include: What are the default metrics? How do you determine the metrics that matter to you? How do you know that these are the best metrics to track? How do you know the best way to go about tracking them? How often should you review your metrics? How do you persuade stakeholders to change metrics?

Nik Ranger shares that you shouldn’t necessarily conclude that ranking on Google means ranking well on AI search engines.

Nik says: “Stop thinking just about ranking on Google and start focussing on a new discipline: AI visibility engineering. This is where you can systematically probe AI models to measure brand associations, quantify perception, and then use those insights to engineer on-page, off-site, and then use those insights to engineer on-page, off-site, and strategic actions that influence how these machines understand and represent your clients.”

When we consider the fact that AI agents are starting to visit our sites, with a view to making purchase decisions or recommendations, and other AI engines are regurgitating our content, we have to ensure that they understand the essence of what we provide.

Chris says: “Technical success for SEO in 2026 requires us to understand the interpretability of content rather than just the crawlability.”

When we start preparing for the consumption of our goods and services by AI, we should also be preparing for AI user agents to navigate our sites.

Itamar says: “In the age of AI platforms and LLMs, it's important to really understand how these different platforms, and more specifically user agents, are accessing and navigating your website.”

Part of the data layer that you provide for AI should include well-structured knowledge graphs, shares Olesia Korobka.

Olesia says: “Prepare small knowledge graphs and use them for your SEO efforts – and also to optimize your content for LLMs and AI output.”

What do you mean by small knowledge graphs, and how do AI search engines use knowledge graphs?

“We know that Google uses knowledge graphs for their AI overviews and for some answers in AI Mode because knowledge graphs are facts. They are entities that provide factual information, so Google does use them intensively.

Also, search within knowledge graphs is much faster than any other search, and the information you get is much easier to use for generating anything that you want.

We used to talk about databases previously, and a knowledge graph is a fancy name for a relational database. That's about it. When you build them, it helps you to get much fewer inaccuracies, get more original information, and ensure that the information is factually correct.

By small knowledge graphs, I mean that you focus only on what you are doing for your own business or for yourself. You can optimize your own name, your company's name, or the products or services that you want people to find in search.”

Jérôme Salomon shares that you can use your server logs to perform an indexation audit at scale thanks to the 130 days rule, bypassing the URL inspector tool API limits for large websites.

Talking points include:

What is an indexation audit?

Why would you want to conduct one?

What is an indexation audit at scale?

What is the 130 days rule?

How do you use your server logs for this?

What are the url inspector tool API limits for large websites?

How often should you conduct one?

How does this feed into a strategy?

What measurable success do you get by doing this?