What does Google AI Mode
mean for SEO strategies?

Google AI Mode launched in the UK on 28 July 2025, and if you’ve read our guide to what it is and how it works, you’ll know that it represents a significant change to Google Search. The more important question now is what that change means for your SEO strategy.

The answer goes much further than optimising for a new type of search result.

AI Mode changes where discovery happens, how information is presented, whether users need to visit your website, and how much control you retain over the customer journey. It also changes what Google needs to understand about your business before deciding whether to surface you at all.

One thing is important to establish from the outset: AI hasn’t shrunk search. It has grown it. Search query volume has continued to rise, while AI Mode queries have grown rapidly as people use search for the exploratory, conversational, and multi-part questions traditional keyword search struggled to answer.

What has collapsed is the click, not the demand.

That distinction changes the problem SEO needs to solve. Success can no longer be measured purely by whether a page ranks highly and earns a visit. Increasingly, the objective is to make sure your brand is visible, understood, trusted, and represented wherever the search journey takes place.

In other words, AI Mode is moving SEO from a ranking discipline towards a visibility discipline.

The fundamentals of SEO haven’t disappeared, but the environment around them has changed. Four shifts matter most.

1. Visibility increasingly depends on brand, not just rankings.

SEO is becoming less of a standalone keyword optimisation discipline and more of what we call “SEvO” – Search Everywhere Optimisation.

Brand awareness was already important to search. Research shows that 34% of consumers discover new brands through search engines, and the relationship between brand and organic performance has always extended beyond the individual query.

AI Mode intensifies that relationship.

Google’s AI can draw on signals including brand recognition, cross-platform presence, and previous user engagement when determining what is relevant to a particular person or question. Larger, more established brands naturally have an advantage because they already have greater awareness, larger content footprints, more third-party references, and more behavioural signals surrounding them.

That means traditional SEO activity increasingly needs support from the rest of marketing. Digital PR can build authoritative mentions and backlinks. Thought leadership content can demonstrate expertise. Social media can create awareness and engagement. YouTube can provide video evidence and educational content. Podcasts, reviews, communities, and other third-party platforms can reinforce what your brand is associated with.

SEO has always benefited from these activities. The difference is that they are becoming much harder to separate from search visibility itself.

This creates a particular problem for less-established businesses. If existing recognition and engagement make a brand more likely to surface, businesses with little visibility can find themselves caught in a loop: they are less likely to be discovered because fewer people know them, but they need discovery to build the awareness that makes future visibility more likely.

The implication is significant. Smaller brands can no longer rely on finding an under-optimised keyword and beating larger competitors on a page-by-page basis. They need to build enough presence, authority, and recognition across the wider market for Google to understand where their brand belongs.

2. Search demand is growing, but website traffic is shrinking.

The traditional relationship between search visibility and website traffic is breaking down. At Google I/O on 19 May 2026, Google brought AI Overviews and AI Mode together into a more connected AI Search experience. A user can receive an AI-generated answer and continue into a conversational search journey without needing to move through a traditional list of results.

That makes citations more valuable, but clicks less dependable.

Research suggests that approximately 93% of AI Mode sessions end without a visit to an external website, while around three-quarters of users never leave the AI Mode interface. AI Mode referral rates have been estimated at roughly 2%, compared with around 17–19% for traditional Google Search.

So demand is still there. Your brand may even be influencing more searches than before. But much of that influence can now happen without the user ever reaching your website.

That has commercial consequences beyond lost traffic.

Under the traditional search model, the website played a major role in the consideration journey. Once somebody arrived, you could explain your proposition, differentiate yourself from competitors, recommend related products, capture an email address, demonstrate expertise, present an offer, or move them towards another conversion.

AI Mode compresses much of that journey into Google itself. By the time somebody does click through, they may already have compared their options, asked follow-up questions, reviewed features, and formed an opinion about which businesses best meet their needs.

For e-commerce, that shift goes even further.

Google’s agentic commerce capabilities increasingly allow parts of the buying journey to happen directly within its ecosystem. Through the Universal Commerce Protocol, users can specify product requirements, monitor prices, and complete purchases through supported experiences without following the conventional journey through a retailer’s website.

Google has also introduced Business Agents, allowing shoppers to interact with branded virtual sales assistants within search, alongside Direct Offers, which can surface retailer promotions within AI experiences when Google considers them relevant.

For retailers, that means the entire journey from discovery to transaction can increasingly happen without the customer meaningfully engaging with the website itself.

The sale may still happen. But the brand loses opportunities to influence what happens around it – the cross-sell, the upsell, the account creation, the loyalty message, the product discovery, the first-party data, and the wider experience that turns one transaction into a customer relationship.

SEO therefore has to account for a new reality: visibility can create commercial influence even when it doesn’t create a website visit.

3. Search performance is becoming harder to measure.

If fewer users click through, traditional analytics only show part of the value search is creating.

Your business could appear repeatedly in AI Mode, influence how someone evaluates a category, and contribute to a purchase decision without producing a measurable website session.

That creates an attribution problem.

AI visibility tools can monitor things such as brand mentions, citations, sentiment, and competitive share of voice, while Google has begun improving reporting around its AI experiences. But prompt-level behaviour, conversion-level attribution, and the relationship between AI exposure and eventual purchase remain difficult to measure precisely.

Personalisation creates another problem.

Traditional rank tracking assumes that there is a relatively consistent set of search results that can be observed from the outside. AI answers are much more fluid. Two people can ask the same question and receive different responses based on context, previous behaviour, location, follow-up questions, and other signals.

That makes the idea of holding a fixed “position” increasingly difficult to apply.

SEO measurement therefore has to become broader. Rankings, clicks, and traffic still tell you something, but they can no longer tell you everything. Brand visibility, citation frequency, share of answer, branded search behaviour, direct traffic, lead quality, and eventual commercial outcomes all become more important parts of the picture.

4. You have less control over how your brand is presented.

Traditional search results largely direct users towards your content. AI Mode interprets it.

Google can extract information from multiple sources, combine it, summarise it, and present it in a completely new context. Your website is therefore no longer necessarily the environment in which somebody first encounters your positioning.

That creates a loss of control.

A nuanced explanation about a product limitation could become a simple statement that your product “doesn’t support” something. Pricing could appear without important context. A competitor’s advantage could be given more prominence than your own differentiators. Technical information could be simplified in a way you would never choose yourself.

In extreme cases, AI can get the underlying facts wrong.

The Wolf River Electric case demonstrates the potential consequences. Google’s AI Overview incorrectly stated that the Minnesota solar company was facing a lawsuit from the state Attorney General over deceptive sales practices. The sources Google referenced were real, but they did not support the claim being made.

Customers subsequently cited the AI-generated information when cancelling contracts, including contracts worth tens of thousands of dollars. Wolf River later alleged significant financial losses and brought a defamation case against Google.

The example relates to AI Overviews rather than AI Mode specifically, but the underlying risk applies across generative search: AI systems do not simply retrieve information – they synthesise it.

That means even perfectly optimised content cannot guarantee that your intended positioning reaches the user intact.

The best defence is to make the wider information environment surrounding your brand as clear, consistent, and authoritative as possible.

The response shouldn’t be to abandon SEO. It should be to broaden what you consider part of it.

1. Build brand demand beyond Google.

If recognised brands are more likely to surface in AI-generated results, brand building becomes part of the SEO strategy. That means investing in channels that create awareness before the search happens.

TikTok, Reddit, LinkedIn, YouTube, Pinterest, PR, creators, communities, email, and other platforms can introduce people to your brand, establish what you are known for, and create the behavioural and cultural signals that eventually feed back into search.

But think wider than demand capture, can you create demand?

Rather than waiting for somebody to search for an established category term, use other channels to introduce ideas, terminology, products, and points of view that generate future searches.

A sustainable fashion brand, for example, might invest in PR, creator partnerships, and educational content around “circular fashion”. If those activities cause more people to search for the concept, the business has not simply competed for existing search demand – it has helped create the demand in the first place.

2. Optimise for search everywhere.

Content can no longer be created solely for a page on your website. Search now happens across traditional search engines, social platforms, video platforms, communities, and AI interfaces. At the same time, Google’s AI can draw information from multiple content types when constructing an answer. Your strategy should reflect that.

A strong piece of original research might become a detailed article, a series of LinkedIn posts, a YouTube video, an email newsletter, podcast talking points, short-form video, and commentary for relevant communities.

That doesn’t mean copying the same content everywhere. It means using one strong idea across the formats and platforms where your audience looks for information.

YouTube is particularly important because video content gives search and AI systems another substantial source of information about your expertise, products, and brand. Instagram captions, video descriptions, user-generated content, PR coverage, and community conversations can all contribute to the wider context surrounding your business too.

The important part is consistency.

Your positioning, expertise, terminology, products, and points of view should reinforce one another across channels. The more consistently those associations appear across the web, the easier it becomes for both people and AI systems to understand what your brand should be known for.

3. Optimise for questions, topics, and citations – not individual keywords.

AI Mode changes how people search. Instead of typing something like “best smartphone camera”, somebody can ask, “What’s the best phone for taking photos of my friends at concerts?”

That requires a different approach to content planning.

Keyword research still provides useful evidence of demand, but content needs to start with the underlying person, problem, and intent rather than the exact phrase being typed. Ask what your audience wants to understand, compare, decide, or achieve. Then create content that answers those questions directly.

That also means reconsidering the obsession with enormous “ultimate guides”.

Research cited in the existing SEO discussion suggests that several focused pieces of content can sometimes create greater AI visibility than one page attempting to answer every related question. A single 3,000-word article may therefore be less useful than three distinct 1,000-word resources, each giving a strong answer to a specific query.

That isn’t an argument for duplicate content or publishing more for the sake of volume. Each page still needs a clear purpose. The aim is to create a connected cluster of focused resources that are individually easy to understand, retrieve, and cite.

Those resources also need evidence.

Expertise, Experience, Authoritativeness, and Trustworthiness (E-E-A-T) remain important. Include specific data, credible sources, original research, expert authorship, firsthand examples, case studies, testimonials, reviews, and third-party validation wherever they genuinely strengthen the answer.

4. Keep your authority current and consistent.

Authority isn’t something you establish once.

Google introduced information agents at I/O 2026 – background AI agents designed to monitor the web for updates around topics users care about and return synthesised briefings.

That creates another reason to treat freshness seriously.

A business publishing useful, clearly attributed information on an ongoing basis gives search systems more current evidence to work with than one relying entirely on content published several years ago.

Maintain a consistent rhythm where you have something useful to say, update important existing pages when information changes, make publication and update dates clear, and ensure every piece is unambiguously associated with your brand and relevant authors.

Named experts matter here too. Strengthen author profiles, demonstrate genuine experience, include original commentary, and make it easy to understand why the person behind the content has authority on the subject.

Consistency matters across the wider web as well. If your website says one thing, your social channels say another, and third-party sites describe the business differently again, AI systems have to reconcile those signals themselves.

The clearer and more consistent the evidence surrounding your brand, the better.

5. Measure visibility and commercial impact differently.

You shouldn’t stop measuring rankings, traffic, or conversions. But you should stop expecting them to explain the entire search journey. AI search requires another layer of measurement.

Track how frequently your brand appears in relevant AI answers, where it is cited, how your visibility compares with competitors, and whether those mentions are positive, accurate, and commercially useful.

Tools such as Peec.AI, Profound, and Scrunch can help monitor AI visibility, citations, competitive share of voice, and sentiment across different platforms.

Google Search Console can provide additional visibility into Google’s AI experiences, while platform properties can also help businesses understand how content from channels such as Instagram, TikTok, X, and YouTube performs within Google Search.

Then connect those visibility measures back to commercial signals.

Look at branded search trends, direct traffic, lead quality, conversion rates, return visitors, cross-platform engagement, customer acquisition, and lifetime value. If organic traffic falls but the leads arriving through search become substantially more qualified, raw traffic alone will give you the wrong conclusion.

The same applies if AI visibility increases branded searches or drives people directly to your business later without producing a measurable AI referral.

Attribution will inevitably become messier.

The answer isn’t to pretend every interaction can still be traced perfectly. It is to combine AI visibility metrics with broader marketing and commercial performance to understand whether your overall presence is getting stronger.

AI Mode hasn’t killed SEO. It has widened the job. Ranking highly still matters, strong websites still matter, technical SEO still matters, and useful content still matters. But they now sit within a much larger system of brand recognition, authority, cross-channel visibility, citations, and user behaviour.

The businesses that adapt fastest will stop treating SEO as the task of getting individual pages into individual positions. They will build brands that are consistently visible, credible, and relevant wherever people search.