Google I/O 2026: where Search is heading in the next few months

Google I/O 2026 gave us a big clue about where Search is heading next. More conversational, more visual and more capable of helping users complete tasks.

Users will be able to ask longer, more specific questions, explore answers through generated layouts, set up agents to monitor information and, in some cases, move closer to completing bookings.

The key Search announcements from Google I/O 2026

1. Generative UI in the SERP

One of the most interesting announcements was generative UI in Search.

Instead of returning the same style of results for every query, Google Search can generate a custom interface for the task. That might include tables, graphs, simulations, calculators, comparison layouts or interactive tools.

What generative UI could look like

Let’s use a banking example because it’s easy to see how the experience could change.

A user might search:

I’m freelance, travel regularly and want a current account with low overseas fees, no monthly fee and a good app.

Today, that might return comparison sites, bank pages and review articles.

In a generative UI result, Google could build an interactive comparison tool directly in the SERP. It might include:

• a shortlist of accounts from providers such as Monzo, Starling, Revolut, Barclays or Lloyds
• filters for monthly fees, overseas card fees, overdraft options and app features
• a cost calculator based on expected travel spend
• expandable cards showing trade-offs and eligibility
• links to check eligibility or apply on the provider’s site

The user could then refine the result:

Only show accounts with no foreign transaction fees.

Or:

Compare the lowest-cost option with the account that includes travel insurance.

The important point is that the SERP becomes part of the decision experience. The brand’s website still matters, but more of the comparison may happen before the click.

What this means for brands

This is not only relevant to banks. The same pattern could apply to insurance, SaaS, telecoms, ecommerce, travel, education, healthcare, property, energy and local services.

Any category where users compare options could be reshaped by generative UI.

For brands, the question becomes:

Can AI systems understand the facts that make us relevant to this user’s decision?

That might include:

• prices
• plans
• availability
• product features
• eligibility
• locations
• policies
• reviews
• use cases
• comparisons
• proof points
• next steps

Google’s own guidance says its generative AI features in Search are rooted in core Search ranking and quality systems. It also says Search uses retrieval-augmented generation and query fan-out to find relevant information from its index.

So SEO still matters. But a page that ranks is not automatically a page that helps AI compare, filter or recommend. Brands need clear, structured, decision-ready information.

This is where answer engine optimisation overlaps with traditional SEO. The job is to make sure your brand is represented clearly when AI systems summarise and compare options.

2. Information agents

Google also announced information agents in Search.

These are background agents that monitor information for the user. Reporting from I/O described agents that can track blogs, news sites, social media posts and real-time sources such as finance and sports data, then notify the user when something relevant appears.

What information agents could look like

Using the same current-account example, a user might ask Google to monitor the market for:

Current accounts with no monthly fee, low overseas fees and a switching offer above £175.

Instead of searching again every week, the user could leave an agent running in the background. If a new offer appears, the agent might send a summary:

A current account now matches your criteria. It has no monthly fee, a £200 switching offer and no foreign card transaction fee. The offer closes on 30 June.

The user could then ask:

What are the conditions?

Or:

Compare it with the other accounts I was considering.

The same idea could apply across many categories:

• a traveller watching for a flight or hotel deal
• a parent tracking school holiday availability
• a homeowner monitoring mortgage rates
• a retailer watching competitor prices
• a buyer tracking SaaS tools that meet certain criteria
• a consumer waiting for a product to come back into stock

The search experience becomes less session-based. The user does not have to return to Google and search again. Google can keep watching on their behalf.

What this means for brands

Information agents make freshness and accuracy more important.

If an offer, price, product, feature or availability changes, AI systems need to understand:

• what changed
• when it changed
• who it applies to
• what the conditions are
• whether it is still live
• how it compares with alternatives

This is where AI Search becomes a systems problem, not only a content problem.

Brands need a clear source of truth for the facts that influence decisions: prices, stock, availability, locations, opening hours, features, policies, reviews, eligibility and booking options.

Ecommerce brands often have an advantage here. A well-run ecommerce store usually already has product data, pricing, stock, variants, delivery rules, returns information, reviews, structured data and product feeds connected. Google’s own guidance says Merchant Center feeds and Google Business Profiles can help product, service and local business information appear in AI responses and Search results.

That infrastructure gives AI systems cleaner data to work with.

For brands with messier systems, the risk is inconsistency. If the website says one thing, a feed says another, a marketplace listing is out of date and Google Business Profile has different information, AI systems have less reason to trust the brand’s own version.

3. Agentic booking

Google also announced an expansion of agentic booking in Search.

The examples shared around I/O focused on users giving Search specific criteria, such as finding a private karaoke room for a group on a Friday night. Search can then bring together pricing and availability, with links to complete the booking through the provider. Google also said that, for selected categories such as home repair, beauty and pet care, users will be able to ask Google to call businesses on their behalf.

This is worth watching, but it’s important not to overstate the immediate impact. We’re still some way from every purchase or booking becoming fully agentic. For most brands, the near-term priority is making sure information is accurate, accessible and useful in AI-led research and comparison.

What agentic booking could look like

For a travel example, imagine someone searching:

Find a dog-friendly Airbnb in Cornwall for the first weekend in August, under £220 a night, with parking and flexible cancellation.

A more agentic Search experience could help the user compare options by:

• availability
• total price
• location
• amenities
• cancellation policy
• reviews
• booking provider
• trade-offs

The booking may still finish on Airbnb, Booking.com, Vrbo, a hotel website or another provider. But the discovery, filtering and comparison could happen inside Google.

The same model could apply to restaurants, beauty appointments, event tickets, local trades, activities, short breaks and other booking-led categories.

What this means for brands

For booking-led businesses, the challenge is simple:

Can AI systems understand what is available and what the user needs to do next?

That means making key information easy to access:

• availability
• total price
• fees
• cancellation rules
• location
• amenities
• policies
• reviews
• booking links
• contact routes

Not every business needs live data to the same degree. Hotels, retailers, restaurants, events companies, property platforms and local services need to care more because the user’s decision often depends on what is true now.

A consultancy, law firm, B2B SaaS company or manufacturer may not need real-time availability in the same way. But they still need accurate, structured information about services, products, industries, proof points, locations and next steps.

So the point is not that every brand suddenly needs live booking infrastructure. The point is that AI Search rewards businesses that provide reliable information in a format search systems can understand.

Could a traditional SEO strategy still work?

Yes, but only so far.

Google says existing SEO best practices still apply to generative AI Search. To be eligible to appear in Google’s generative AI features, a page needs to be indexed and eligible to show in Search with a snippet. Google also says there is no need for special AI-only files, special markup or rewriting content only for AI systems.

So a brand with a strong SEO strategy from five years ago may still have useful foundations:

• crawlable pages
• indexable content
• internal links
• page speed work
• structured data
• useful landing pages
• helpful content
• authority signals

But that does not mean the strategy is complete for AI Search.

A traditional SEO strategy was usually built around rankings, keywords, content pages and traffic. AI Search is more likely to involve longer prompts, comparison logic, source synthesis and decision support.

Google’s guidance describes query fan-out, where Search generates related queries to gather more context around a user’s question.

That changes the job.

A brand does not only need a page about the product. It needs clear, consistent evidence across the questions AI systems may ask while building an answer.

For example:

Sector

What AI systems may need to understand

Ecommerce

Product attributes, price, stock, delivery, returns, reviews and variants

Travel and hospitality

Availability, total price, amenities, cancellation rules, location and reviews

Financial services

Rates, fees, eligibility, terms, switching offers and trust signals

SaaS

Use cases, pricing model, integrations, security, comparisons and customer proof

Professional services

Services, sectors, credentials, locations, case studies and next steps

Local services

Service areas, opening hours, availability, pricing guidance and contact routes

A good way to summarise it:

SEO helps Google find you. AI-search readiness helps Google understand, compare and recommend you.

AI Search rewards operational truth

One of the bigger implications of Google’s announcements is that marketing can’t sit separately from product, data and operations.

If Search can build comparison tools, monitor changes and help users move closer to an action, it needs accurate information. That information has to come from somewhere.

Brands with a single source of truth have an advantage. They’re more likely to have consistent information across the website, feeds, Google profiles, comparison sites, product pages and third-party sources.

Brands with messy systems will struggle. If a price appears in one place, an old offer appears somewhere else and a directory has different information again, AI systems have less reason to trust the brand’s own version.

This is why AI Search is not only a content task. It’s a marketing systems task.

Brands should be asking:

• Where does our product or service data live?
• Who owns it?
• How often is it updated?
• Does the website match our feeds?
• Does Google Business Profile match the website?
• Do comparison sites and directories show the right information?
• Are our most important facts crawlable and visible?
• Can users and AI systems understand the next step?

For some brands, the answer may be a technical SEO clean-up. For others, it may mean product data work, better structured content, updated commercial pages or stronger evidence across third-party sources.

A simple starting point is to check whether your website is technically accessible and easy to interpret. Tilio’s free AI visibility checker reviews signals like crawler access, structured data, metadata and on-page context.

What brands should do next

The practical response to Google’s AI Search updates is not panic. It’s getting the basics right, then improving the information AI systems need to make decisions.

1. Keep SEO foundations strong

Make sure important pages are crawlable, indexable and internally linked. Avoid blocking useful content with robots rules, CDN settings, scripts or login walls.

2. Make key facts explicit

Turn vague product copy into clear decision-supporting information. Explain pricing, features, eligibility, availability, terms, limits, policies and trade-offs.

3. Improve structured data and feeds

Use structured data where relevant. For ecommerce and local businesses, make sure product feeds, Merchant Center and Google Business Profile data are accurate and maintained.

4. Build source-of-truth pages

Create strong pages that explain who your product or service is for, how it compares, what it costs and what the user should do next.

5. Measure AI visibility separately

Traditional SEO tools won’t show the full picture. Brands need to know whether they appear in AI answers, how they’re described, which sources are cited and where competitors are being chosen instead.

That’s the kind of work covered in an AI search visibility programme: tracking prompts, benchmarking competitors, improving cited pages and strengthening the signals AI systems use.

The takeaway

Google’s I/O announcements point to a clear direction of travel.

Search is becoming more conversational, more visual and more action-led. Users will ask longer questions. AI systems will compare more options. Some search experiences will become interactive. Agents will monitor information in the background. Booking flows will become more integrated in selected areas.

SEO still matters. Google has been clear on that.

But brands need to go further than a traditional SEO strategy built around rankings and traffic. The brands most likely to benefit are the ones with clear information, reliable data, strong content, accurate feeds, consistent third-party signals and a single source of truth behind their marketing.

In AI Search, visibility depends on whether a brand can be found, understood and trusted at the point a user is making a decision.

FAQs

What did Google announce about AI Search at I/O 2026?

Google announced several AI Search updates, including generative UI in the SERP, information agents that can monitor the web in the background, and expanded agentic booking experiences. Together, these point towards Search becoming more interactive, personalised and action-led.

What is generative UI in Google Search?

Generative UI means Google can create a custom interface in response to a query. Instead of only showing links, Search could generate tables, comparison tools, calculators, simulations or interactive layouts that help the user make a decision directly in the results page.

When is generative UI coming to Google Search?

Google has said generative UI capabilities will roll out this summer and be available for everyone in Search, free of charge. More persistent mini apps and dashboards are expected later, starting with Google AI Pro and Ultra subscribers in the US.

What are information agents in Search?

Information agents are AI agents that monitor information in the background. A user could ask Google to watch for a specific price, offer, product, rate or availability change, and receive an update when something matches their criteria.

What is agentic booking in Google Search?

Agentic booking is Google’s move towards helping users find and compare bookable options based on their criteria. For example, a user might ask for a dog-friendly stay in Cornwall under a certain price, or a local service appointment at a specific time. Google could help compare availability and send the user to the provider to complete the booking.

Does traditional SEO still matter for AI Search?

Yes. Google has said its generative AI features are still rooted in core Search systems, so crawlability, indexation, useful content, internal links and technical SEO still matter. But SEO alone may not be enough. Brands also need clear, accurate and structured information that AI systems can understand and compare.

What should brands do to prepare for AI Search?

Brands should focus on accurate data, clear product or service information, structured content, strong technical SEO and consistent signals across their website, feeds, Google profiles and third-party sources. The aim is to make the brand easy for AI systems to find, understand, trust and recommend.