Google’s Biggest Announcement in 25 years. Here’s what marketing leaders need to do about it

At Google I/O 2026 on 19 May 2026, Google made its clearest move yet toward AI-led search. Sundar Pichai described AI Mode as the biggest upgrade to Search ever. Looking at what was announced, it's hard to disagree.

AI Overviews now has more than 2.5 billion monthly active users. AI Mode, launched a year ago, has passed 1 billion monthly active users. Google also says people who use AI-powered features in Search use the product more, and the terms they use are less like individual queries and more like an ongoing conversation.

That last point is the one marketing leaders should pay particular attention to. Google is moving from a search results page toward an answer, comparison and action layer.

For years, the model was easy to understand:

1.      Someone searched.

2.      Google showed links.

3.      Brands fought for rankings.

4.      Users clicked through to websites.

5.      The website then educated, persuaded, and converted the user.

That journey still exists, but it now sits inside a bigger system. AI-led search can summarise the market, compare options, explain trade-offs, recommend providers, and answer follow-up questions without the user visiting several websites.

The visibility challenge has changed. The question is no longer only, "Are we ranking?" It's, "Are we being understood, trusted and recommended when AI shapes the answer?"

What did Google announce at Google I/O 2026?

A rebuilt Search experience

Google has rebuilt the Search experience around more natural, specific and conversational inputs. The direction is clear: users are being encouraged to describe the situation properly, rather than reduce their need to a short keyword.

That changes the type of content brands need to create. It's not enough to rank for broad phrases. Brands need to answer the messy, specific questions people ask when they are comparing options, trying to reduce risk or looking for a recommendation.

AI Mode at scale

AI Mode is already operating at scale. As shown above, these Google products now reach billions of monthly users, meaning this is no longer a test sitting at the edge of search behaviour.

The implication is uncomfortable for any brand still treating AI search as a future issue. Buyers are already using AI-powered answers inside Google. In many cases, those answers will shape what they believe, who they compare, and which brands they choose to investigate further.

Information agents working in the background

Google also announced information agents in Search. These are personalised AI agents that can work in the background, 24/7, to find what users need at the right moment and help them take action. They start rolling out this summer for Google AI Pro and Ultra subscribers.

This is a bigger shift than most marketers are giving it credit for. If an agent can monitor the web on behalf of a user, the act of searching becomes less active. Brands can be evaluated before a prospect types a fresh query.

Generative interfaces inside Search

Google said Search will be able to build custom experiences for individual questions, including dynamic layouts, interactive visuals, dashboards, and trackers. These generative UI capabilities are due to become available for everyone in Search this summer, with persistent custom dashboards arriving first for Pro and Ultra subscribers in the US.

That changes the website's role. If Google can build an interactive comparison, checklist, tracker or planning tool inside Search, some tasks that once happened on brand websites may happen before the click.

More personal answers

Google is pushing deeper personalisation through Gemini and Personal Intelligence too. The more Search is shaped by personal context, the less useful one fixed view of ranking becomes. Two people can ask a similar question and get different answers, shaped by who they are, what they have done, and what Google believes is relevant to them.

Why do the Google I/O 2026 announcements change the visibility challenge?

Marketing teams have built years of reporting around rankings, sessions, conversion rates, and revenue. Those measures still matter, but they do not show the whole picture anymore.

A brand can rank and still be absent from the AI answer. A website can keep receiving traffic while a competitor becomes the name AI systems use in high-intent comparisons. A marketing team can report organic growth while losing ground at the moment the shortlist is formed.

That is the issue. Influence is moving further upstream. If AI Mode reduces external click behaviour, brands need to fight to become part of the answer itself, not only the destination after the answer.

What has changed about how people search?

Search is more conversational

The new search behaviour is less about typing short phrases and more about asking detailed questions. These are the kinds of searches marketing teams need to plan for:

"Which energy supplier is best for a multi-site manufacturer that needs more accurate billing?"

"What should a housing association look for in a digital transformation partner?"

"Which private healthcare providers are trusted for fast diagnostics and transparent pricing?"

These are decision-stage questions. They carry context, risk, criteria, and commercial intent. AI Mode is built to answer this type of query directly.

Search is more personalised

Personalisation creates a serious reporting problem. Traditional ranking tools show one version of visibility. AI-led search creates many versions, shaped by audience, context, location, previous behaviour, and wider Google signals.

A single rank position no longer tells leadership enough. Marketing teams need to understand whether they appear for the right audience, in the right context, with the right message.

Search is becoming agentic

Information agents don’t wait for a user to search. They monitor, filter, and notify. In sectors with complex buying journeys, such as finance, healthcare, utilities, professional services, and B2B technology, AI could start shaping decisions before a user actively searches for a supplier.

That creates a new kind of visibility problem. You may lose the shortlist before you know there was a search journey at all.

The five risks marketing leaders need to address

1. Visibility risk

Your brand may rank in traditional search results but fail to appear in AI-generated answers. These are not the same thing anymore.

2. Authority risk

If there are not enough trusted third-party signals around your brand, AI systems have fewer reasons to cite or recommend you. Internal reputation does not automatically become machine-readable authority.

3. Content risk

Many brands have plenty of content. The problem is that too much of it is generic, thin or written for old keyword models. AI search will expose the gap between content volume and content usefulness.

4. Measurement risk

Rankings, sessions, and last-click conversions no longer tell the full story. If an information agent evaluates your brand in the background, that influence may never appear as a standard analytics visit.

5. Brand demand risk

As search becomes more personalised, brand familiarity becomes more valuable. People are more likely to trust names they recognise. AI systems also have stronger signals to work with when a brand is searched, mentioned, linked to, and engaged with across the web.

The Mediaworks view: build AI-ready category authority

The answer isn’t to panic about SEO or chase every new Google feature. The answer is to build a brand presence that humans can trust and AI systems can interpret.

We call this AI-ready category authority.

It means connecting search, content, PR, social, paid media, technical SEO, and measurement around one commercial aim: making your brand easier to find, easier to understand, and easier to recommend.

Start with an AI Search Readiness Audit

Before investing in another round of content or campaigns, marketing leaders need to know where the brand currently appears, where it's absent, and which competitors are being cited.

That audit should test Google AI Overviews, AI Mode-style results, Gemini, ChatGPT, Perplexity, and other answer engines. It should cover commercial queries, comparison queries, and problem-led searches. It should also identify which sources are being used to support answers.

In some categories, the important source will not be a competitor website. It could be a trade publication, review platform, YouTube video, Reddit thread, buying guide, government page, or data report.

Move from generic content to decision-useful content

Brands need fewer forgettable blogs and more content that helps buyers make confident decisions.

That means answering questions like:

·        What should buyers consider before choosing a provider?

·        What risks should they understand?

·        What drives cost?

·        How do different options compare?

·        What proof exists in their sector? And;

·        What should procurement be asking before a decision is made?

Most brands are weak here. They often have awareness content and product pages, with a gap in the middle where the buyer is weighing up risk, value, and credibility. AI search will make that gap harder to ignore.

Strengthen entity clarity

AI systems need to understand who you are, what you do, who you serve, and why you are credible. That requires clear proposition language, stronger service pages, structured data, consistent internal linking, expert author profiles, and tighter alignment across content hubs and conversion journeys.

If your positioning is vague to a human, it will be vague to a machine. If your website structure is inconsistent, AI systems must work harder to understand what you should be associated with.

Use digital PR as a visibility asset

Third-party validation now has a direct role in search visibility. If AI systems draw confidence from the wider web, credible mentions in relevant places become more than brand activity. They become evidence.

Data-led campaigns, expert commentary, awards, accreditations, trade media coverage, and case study distribution all help. The aim is to be referenced in the right context, using the right category language, by sources that carry authority.

Rebuild measurement around influence

Keep tracking rankings, traffic, leads, and revenue. Add AI answer presence, citation share, competitor citation gaps, branded search demand, share of search, source asset performance, and assisted conversion impact.

A traffic-only view will become misleading. A brand can influence demand without generating a measurable visit. A brand can also keep generating traffic while losing the shortlist earlier in the journey. Leadership teams need to see both.

Five strategic objectives for marketing leaders

Objective 1: Protect visibility in AI-led discovery

Commission an AI visibility audit across priority services and sectors. Identify where competitors are being cited, which sources AI systems appear to trust, and which commercial queries your brand is absent from.

Objective 2: Become a trusted source for category decisions

Build content around buyer’s actual questions, not just search volume. Priority pages should include expert commentary, evidence, FAQs, sector proof, comparison guidance, and clear next steps.

Objective 3: Build authority beyond your website

Strengthen your footprint across trade press, industry bodies, review platforms, YouTube, LinkedIn, reports, and awards. Digital PR and organic visibility need to be planned together.

Objective 4: Use brand demand as a performance lever

Paid media, social, video, founder-led content, PR, and events build familiarity before the search, or the agent, kicks in. If the wider web already connects your brand to the right topics, AI systems have stronger signals to work with.

Objective 5: Rebuild reporting around influence

Show where your brand is visible, trusted, cited, and losing ground. Connect that view to pipeline, lead quality, and conversion performance. Otherwise, teams will keep optimising for the easiest metrics instead of the most commercially useful ones.

The leadership takeaway

Google's I/O 2026 announcements confirm where search is heading. It's becoming a system that shapes decisions, sometimes on behalf of users and sometimes before they have typed a new query.

Ranking and traffic are still important, and websites still need to convert. But the decision journey around those measures is changing faster than most dashboards show.

The brands that win the next phase of search will have substance behind them: clear expertise, useful answers, consistent signals, and strong third-party validation. Content volume alone will not be enough. The content has to help buyers decide.

Ready to understand how visible your brand is in AI-led search?

As Google changes how people discover, compare and choose brands, marketing leaders need to know where they stand.

Mediaworks can help you assess how your brand appears across AI Overviews, AI Mode-style results and answer engines, identifying where you are visible, where competitors are being cited, and what needs to change across content, SEO and digital PR.

Contact us today to book an AI Search Readiness Audit.

Sources: Google, "Google I/O 2026: Sundar Pichai's opening keynote", 19 May 2026.