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May 20 2026

WordPress 7.0 Launches With Native AI Integration via @sejournal, @martinibuster

After weeks of delay, WordPress 7.0, named Armstrong, is finally released. The centerpiece feature was supposed to be real-time collaboration (RTC) but what is shipping is bigger: Native AI integration, a watershed moment in the content management system’s history. Native AI integration is what will carry WordPress into the future and put more distance between it and competitors.

Four Building Blocks Form The Foundation Of WordPress AI

WordPress 7.0 introduces four foundational building blocks that together form its native AI architecture. The larger story is that WordPress is building the infrastructure for a future where AI becomes part of how the CMS itself operates.

The Four WordPress 7.0 AI Building Blocks

WP AI Client
Client-Side Abilities API
AI Connectors Screen
Connectors API

These four features form the pillars that support a radical transformation of how information will be published and websites are designed. What makes this especially powerful is the massive community of developers around the world who can now create new ways of using themes, dream new ways of building websites, analyzing data, and making it easier to build a business online. No other CMS has that people-power behind it.

WordPress explains it like this:

“WordPress 7.0 unlocks AI capabilities right in your website. The new WP AI client adds a central interface that lets plugins communicate with generative AI models while remaining provider-agnostic. WordPress Core handles request routing for you. Managed in the Settings > Connectors screen with API keys funneled through the Connectors API, you can start with some preset models and add your favorites.

As a bonus, the Abilities API is integrated directly into the WP AI Client, delivering new and expansive AI abilities that can be built into workflows that run abilities fluidly, one after another.”

WP AI Client Enables AI Provider Integration

WordPress Core enables users to bring their own AI providers and easily integrate them into the CMS. The WP AI Client makes that possible by giving plugins a central, provider-agnostic interface for sending prompts to AI models and receiving responses through WordPress.

Plugin developers do not have to build separate AI integrations for every provider. They can integrate with the WP AI Client interface instead.

A plugin can describe what it needs, WordPress can route the request to a suitable configured model, and site owners can control which AI providers are available inside WordPress.

The release also introduces model preference ordering, feature detection, advanced configuration controls, and a Prompt Builder class for interacting with models. WordPress says developers can prioritize models based on capabilities, cost, and processing efficiency.

Client-Side Abilities API Extends AI Into WordPress Actions

WordPress 7.0 gives AI and automation tools a way to interact with WordPress from inside the browser. That means AI can be connected to actions such as navigating the admin, inserting blocks, running commands, and participating in workflows instead of simply generating text outside the CMS.

This is where the AI story becomes bigger than content creation. WordPress is creating a layer where AI agents, plugins, and automation tools can act on the same set of WordPress capabilities through a shared interface.

The practical effect is that WordPress can become an environment that AI tools operate within, not just a place where AI-generated content is pasted.

AI Connectors Centralize External AI Services

The new Connectors screen gives site owners one place to manage connections to outside AI services. Instead of scattering API keys and provider settings across individual plugins, WordPress is creating a central location for managing those services.

The Connectors API is the technical layer behind that screen. It handles the provider registry, authentication details, metadata, and future connection types, which gives WordPress a standardized way to recognize and manage external AI services.

That matters because AI will not be limited to one provider or one kind of integration. WordPress is preparing for a future where multiple AI services can be connected, managed, and used across the CMS.

WordPress explains how the Connectors API works behind the scenes:

“The Connectors API is the backbone of the Connectors screen; an extensibility API that facilitates and supports the inclusion of agents.

The API supports two authentication methods (api_key and none) based on provider metadata, and is designed to facilitate additional connector types in future releases. The Connectors API uses the WP AI Client’s default registry to automatically discover providers, and corresponding metadata to generate connectors, while connectors authenticated via other methods are stored in the PHP registry.

You can use the wp_connectors_init action to override connectors metadata, which will be the key for registering new connector types in future releases. The API includes three public functions for querying the registry, and the frontend UI can be customized using client-side JavaScript registration.”

WordPress Is Building Beyond AI Features

The release is not just about adding AI to WordPress. It is about giving WordPress the internal structure needed for AI-workflows like publishing, SEO automation, site design, site building, and agent-based workflows.

The four building blocks built into WordPress 7.0 make it all happen:

The WP AI Client connects WordPress to models.
The Abilities API gives AI a way to take action.
The Connectors screen gives users control over providers.
The Connectors API gives developers a standard foundation for future integrations.

Real-time collaboration was expected to define WordPress 7.0. Native AI integration may prove to be the feature that defines what WordPress becomes next.

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May 20 2026

Google Introduces New Ad Formats In AI Mode via @sejournal, @brookeosmundson

Google announced two new ad formats for AI Mode during Google Marketing Live: Conversational Discovery ads and Highlighted Answers.

Both formats are powered by Gemini and designed to place ads more directly inside AI-generated responses and recommendation flows.

According to Google, the formats will include an independent AI explainer that synthesizes information about a product or service alongside the advertiser’s creative. Ads will continue to carry sponsored labels.

Read on to learn more about the new ad formats and when you can expect to start seeing them.

Conversational Discovery Ads Respond To Nuanced Prompts

Conversational Discovery ads are designed to respond to detailed or exploratory prompts inside AI Mode.

Google’s example showed someone asking how to make their home smell like “fancy spas or a rainy forest” using low-maintenance solutions.

Instead of relying primarily on keyword targeting, Gemini generates tailored creative and surfaces product features tied to the context of the conversation.

That creates a different type of Search interaction than advertisers are used to optimizing for today.

These ads appear built for longer, conversational prompts where users may refine what they want throughout the interaction rather than searching with a single high-intent query.

Google has been steadily moving in this direction through AI Overviews, AI Mode testing, and earlier sponsored placements appearing inside AI-generated experiences.

Highlighted Answers Insert Ads Into Recommendation Lists

The second format, Highlighted Answers, places ads directly inside recommendation lists generated by AI Mode.

Google used the example of someone researching language learning apps before a trip. Advertisers with highly relevant ads may appear directly within those recommendations.

This moves ads closer to the recommendation itself instead of alongside traditional Search results.

For advertisers, that could create visibility earlier in the research process before users narrow down to a final decision.

Google also said these experiences will remain clearly labeled as sponsored and include AI-generated explainers alongside the ad.

Why This Matters For Advertisers

These updates suggest Google is pushing ads deeper into conversational Search experiences.

For advertisers, that may increase the importance of creative quality, landing page content, structured product data, and first-party conversion signals.

Gemini is evaluating more than a simple keyword query. It’s interpreting the broader context of the conversation before surfacing ads.

It also creates new reporting and measurement questions.

Conversational searches are far less structured than traditional keyword searches. That may make it harder for advertisers to understand which prompts, themes, or interactions actually influenced performance over time.

Similar concerns have already started surfacing around AI Overviews and other AI-driven Search experiences.

Looking Ahead

Google made it clear that AI Mode is becoming a larger part of Google’s Search strategy.

Conversational Discovery ads and Highlighted Answers also provide a clearer picture of how Google plans to monetize those experiences.

Measurement and optimization may become far more complicated as searches become longer, more conversational, and less tied to traditional keyword behavior.

Both formats are expected to be tested within AI Mode, with no confirmation yet on when they are expected to start surfacing.

Featured image: subh_naskar/ Shutterstock

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May 20 2026

Google Shares First AI Mode Usage Data After One Year via @sejournal, @MattGSouthern

Google released a report detailing how people use AI Mode in the U.S., drawing on internal Search data and Google Trends to map search behavior one year after launch.

The report, published alongside Google I/O 2026 announcements, said that AI Mode has surpassed 1 billion monthly active users globally. Queries have more than doubled every quarter since launch.

How Query Behavior Is Changing

The report states that the average AI Mode search is three times longer than a traditional search. Both short and long queries are increasing in AI Mode, with users having conversations and asking longer questions.

Follow-up queries in AI Mode rose over 40% monthly in the U.S. More than one in six AI Mode searches are multimodal, using voice, images, or video. Image-based searches are up over 40% month-over-month since launch.

Top keywords include “information,” “identify,” “find,” “explain,” and “summarize.” Common first words are “what,” “how,” “I,” “is,” and “can,” with “I” especially notable, which may suggest people treat AI Mode more like a conversation than a traditional search.

What People Search For

Google grouped AI Mode search topics into five categories: Explore, Decide, Learn, Create, and Do. The top 10 topics include creative content, media, education, fashion, food, health, tech, travel, productivity, and development.

Brainstorming queries increased 30% faster than overall AI Mode queries since launch, with searches for “where to,” “where should I,” and “ideas for” also rising, per Google Trends.

Planning-related queries grew 80% faster over six months, with decision questions starting with “which” increasing 40%, especially “which of” and “which one.”

Shopping And Local Behavior

Shoppers start with traditional search, then move to AI Mode for deeper inquiry, especially in electronics, books, apparel, health and beauty, and automotive.

In AI Mode, store-related questions focus on “near me,” replacement parts, financing-related dealership searches, online options, and stock.

Top retail concerns include price, location, color, brand, and availability. For restaurants, users seek kid-friendly options, views, bars, vegan or vegetarian choices, and outdoor seating.

Creative And Educational Use

AI Mode’s image creation queries have more than tripled since early 2026, with users mainly requesting photos, quizzes, logos, stories, and code, as well as editing photos, documents, videos, messages, and code.

For education, top subjects include math, Spanish, history, English, and biology, while professional development searches focus on Security+, black belt, Network+, bar exam, and real estate license.

Why This Matters

The data shows AI Mode users are searching in ways that don’t map cleanly to traditional keyword patterns. Queries are longer, conversational, and increasingly multimodal. Follow-up conversations are growing, and planning and decision queries are among the strongest growth signals in the report.

If query length and follow-ups keep growing, that means thin content faces a different competition than conversational answers to multi-part questions.

Looking Ahead

Google released this report the same week it announced Gemini 3.5 Flash as the new default model in AI Mode, redesigned the Search box, and previewed search agents for this summer.

The keyword and query data covers May 2025 to April 2026 and comes from a random, unbiased sample of Google searches. The Trends data measures search interest as a share of AI Mode searches, not total query volume. AI Mode Trends data is not publicly available on trends.google.com.

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May 20 2026

Google’s llms.txt Guidance Depends On Which Product You Ask via @sejournal, @MattGSouthern

Google’s Search and Chrome documentation now point in different directions on llms.txt, depending on whether the goal is Search visibility or agentic browser readiness.

Google Search recently published a new optimization guide that lists llms.txt among the tactics you don’t need for generative AI features. The guide groups it with content chunking, AI-specific rewriting, and special schema.

Days earlier, Google’s Lighthouse tool shipped version 13.3, which added a new Agentic Browsing category. The update includes an llms.txt audit that checks whether a site provides the file and flags server errors when retrieving it.

The Lighthouse documentation describes llms.txt as a way to provide “a machine-readable summary of a website’s content, specifically designed for LLMs and AI agents.” It adds that without the file, “agents may spend more time crawling the site to understand its high-level structure and primary content.”

What Google Search Has Said

Google’s Search team has maintained for over a year that llms.txt is not a Google initiative or something Google plans to adopt.

John Mueller compared llms.txt to the keywords meta tag, noting no AI services used it and bots didn’t request the file. He called building separate Markdown pages for bots “a stupid idea.”

At Search Central Live Deep Dive Asia Pacific, Gary Illyes and Amir Taboul confirmed Google was not pursuing llms.txt.

Google’s optimization guide explicitly states llms.txt should be skipped, providing the most recent direct statement from the Search team.

What Chrome’s Lighthouse Now Does

Lighthouse 13.3 ships with the Agentic Browsing category by default, checking WebMCP integration, agent accessibility, layout stability, and llms.txt.

The llms.txt audit only marks sites as “Not Applicable” if they return a 404; errors flag the audit. The Lighthouse docs describe llms.txt as an “emerging convention” at llmstxt.org, advising site owners to create and place it in their root directory.

This category is separate from SEO audits and indicates that llms.txt helps browser-based agents understand site structure, not improve search rankings or AI citations.

Google Has Been Here Before

Google’s internal teams have sent mixed signals on llms.txt before.

In December, Lidia Infante spotted an llms.txt file on Google’s Search Central developer documentation. Mueller responded on Bluesky with “hmmn :-/” and didn’t clarify further.

Dave Smart noted that the file appeared on multiple Google developer properties, including developer.chrome.com and web.dev. The pattern suggested an internal CMS platform update that automatically deploys llms.txt files, not a Search team decision.

The Search Central file was removed within hours, but files on other Google properties remained.

Why This Matters

Google’s answer on llms.txt varies by use case.

For Google Search, llms.txt isn’t needed for AI Overviews, AI Mode, or other generative AI Search features.

For browser-based agents, Lighthouse considers llms.txt optional in an experimental machine interaction category.

Guidance is split between different Google developer sites, which can lead to conflicting instructions when comparing Lighthouse or its llms.txt documentation with Google’s Search docs.

Looking Ahead

Google hasn’t commented on the documentation gap between the two product teams.

For many sites, creating a basic llms.txt file is simple, but maintaining it is questionable, given that Google Search states it’s unnecessary for AI Search visibility.

Featured Image: Stock-Asso/Shutterstock

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May 19 2026

Google Adds AI Agents To Search, Redesigns Search Box At I/O via @sejournal, @MattGSouthern

Google upgraded AI Mode with Gemini 3.5 Flash as the new default model and redesigned the Search box with AI capabilities, the company announced at I/O. The changes also include search agents and an international expansion of Personal Intelligence.

Liz Reid, VP and Head of Search, said AI Mode has passed one billion monthly users. She said queries have more than doubled every quarter since launch and reached an all-time high last quarter.

Gemini 3.5 Flash As Default In AI Mode

Google made Gemini 3.5 Flash the new default model in AI Mode for everyone globally, starting today.

The update continues a broader pattern of model upgrades across Google’s AI products. Google made Gemini 3 the default for AI Overviews in January and, in December, launched Gemini 3 Flash as the default in the Gemini app.

Redesigned AI Search Box

Google redesigned the Search box with AI. Reid called it the biggest upgrade to the Search box in over 25 years.

The new box expands dynamically to accommodate longer queries. It offers AI-powered suggestions beyond autocomplete and accepts multimodal inputs, including images, files, videos, and Chrome tabs. Standard search results still appear alongside AI features. The redesigned box is rolling out today in all countries and languages where AI Mode is available.

Separately, users can now ask follow-up questions directly from an AI Overview, which then flows into a conversational AI Mode session. Context carries over between the two. This is live today on desktop and mobile worldwide.

Search Agents

The company announced search agents that run in the background to monitor the web and deliver updates. The first type, information agents, will look across the web, including blogs, news sites, and social posts. They’ll also tap Google’s real-time data on finance and shopping.

Information agents will launch this summer for Google AI Pro and Ultra subscribers.

Agentic booking is also expanding to local experiences and services. Users can share criteria and get results with pricing and availability. For select categories, such as home repair and pet care, Google said users can ask it to call businesses on their behalf. These booking features will roll out to everyone in the U.S. this summer.

Google also announced new agentic shopping capabilities in Search, with details on a separate Shopping blog post.

Generative UI And Mini Apps

The Antigravity platform and Gemini 3.5 Flash coding capabilities are coming to Search. In response to a query, Search can generate custom visual tools and simulations tailored to the question.

Google said Search can also build custom dashboards or trackers that users can return to over time. Reid compared these to mini-apps for specific tasks, like tracking a health routine or managing a move.

The generative UI capabilities will be free for everyone in Search this summer. Antigravity mini apps will start rolling out for AI Pro and Ultra subscribers in the U.S. in the coming months.

Personal Intelligence Expands Internationally

Personal Intelligence in AI Mode is expanding to nearly 200 countries and territories across 98 languages. The feature no longer requires a subscription.

Users can connect Gmail and Google Photos to AI Mode, with Calendar support coming. The feature first launched for AI Pro and Ultra subscribers in January and expanded to free U.S. users in March.

Why This Matters

These updates extend the trajectory Pichai outlined in April. He called search an “agent manager” and predicted users would run long-running tasks rather than browse results. Search agents and custom mini apps move in that direction.

More query activity within Google’s AI interfaces may mean that fewer queries result in outbound clicks. Google says queries hit an all-time high, but independent measurements have consistently found that AI Overviews reduce clicks on queries where they appear.

Personal Intelligence expanding without a subscription in nearly 200 countries is the most concrete change to monitor. Personalized results at this scale could affect how Google selects which content to surface. When connected, the system can draw on a user’s email and photos alongside web results.

Looking Ahead

Gemini 3.5 Flash is now available in AI Mode. The redesigned Search box is starting to roll out. Personal Intelligence is expanding to nearly 200 countries and territories without a subscription requirement.

Several features are scheduled for this summer with different availability tiers. Information agents and Antigravity mini apps will require an AI Pro or Ultra subscription. Agentic booking will be available to everyone in the U.S. Generative UI will be free for everyone in Search.

No timeline was given for Google Calendar integration with Personal Intelligence.

Featured Image: Danuta Hyniewska/Shutterstock

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May 19 2026

Google Brings AI Content Verification To Search via @sejournal, @MattGSouthern

Google is expanding its SynthID verification tools to Search today, with Chrome support planned over the coming weeks. Users will be able to check the origin of images through Search features such as Lens, AI Mode, and Circle to Search.

The company is also launching an AI Content Detection API on Google Cloud, initially available to a group of trusted partners. Several companies are bringing SynthID watermarking to their AI-generated content, according to a blog post by Laurie Richardson, VP of Trust & Safety, and Pushmeet Kohli, Chief Scientist at Google Cloud and VP at Google DeepMind.

SynthID Verification In Search & Chrome

Google said it is expanding SynthID verification to Search today and plans to bring it to Chrome over the coming weeks.

Users can check whether an image was made with AI through features like Lens, AI Mode, and Circle to Search. You can ask questions like “Is this made with AI?” or “Is this AI generated?” to get verification results.

SynthID verification was already available in the Gemini app for images, video, and audio. It works by embedding imperceptible digital watermarks into AI-generated content.

C2PA Content Credentials

Google is also adding verification for C2PA Content Credentials, an industry standard for recording how media was created and modified.

The C2PA verification feature is rolling out in the Gemini app starting today and will roll out to Search and Chrome in the coming months.

AI Content Detection API

Google is launching a new AI Content Detection API on Google Cloud’s Gemini Enterprise Agent Platform, available to select partners. The API is a Google Cloud offering that Google says can detect AI-generated content made by Google and other popular models.

The API can help businesses evaluate and manage media across their platforms. Use cases include sorting feeds, preventing insurance fraud, fact-checking, and labeling synthetic media.

Initial partners include Shutterstock, Snap, Avid, Fox Sports, and Canva.

Industry Adoption Of SynthID

Companies including OpenAI, Kakao, and ElevenLabs are bringing SynthID technology to their AI-generated content. Google has open-sourced its SynthID text watermarking technology and partnered with NVIDIA to watermark AI-generated video from NVIDIA’s Cosmos models.

Meta, a fellow C2PA Steering Committee member, will start labeling camera-captured media with Content Credentials on Instagram. This means photos and videos shot on Pixel phones will be recognized and labeled on Instagram as camera-captured media.

Why This Matters

Google has been developing content-provenance tools since it first introduced SynthID in 2023. At that time, the technology was limited to select Google Cloud customers and was limited to images. The expansion to Search and Chrome moves verification from a specialized tool into surfaces where people encounter content every day.

The AI Content Detection API opens a different use case. Publishers and platforms that need to check whether content was made with AI will be able to access that capability through Google Cloud.

Searchers can already check image context through features like “About this image,” which Google expanded to Circle to Search and Lens in 2024. The SynthID verification adds a layer that checks for watermarks embedded at the point of creation, rather than relying on metadata that can be stripped.

The broader industry adoption of SynthID is worth watching. If more AI-generated media carries SynthID watermarks, Google’s verification tools have a wider base of content to check against. But SynthID only detects content watermarked with SynthID. Content from AI tools that don’t use it may not be identified through SynthID verification.

Looking Ahead

C2PA Content Credentials verification will come to Search and Chrome in the coming months. Google didn’t share specific timelines for broader availability of the AI Content Detection API beyond its initial partner group.

Featured Image: FOTOGRIN/Shutterstock

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May 19 2026

Google Announces New Universal Cart At I/O via @sejournal, @brookeosmundson

Google used its I/O 2026 event to introduce Universal Cart, a new AI-powered shopping experience designed to work across Search, Gemini, YouTube, Gmail, and participating merchants.

The announcement signals another major step in Google’s broader push toward “agentic commerce,” where AI systems do more than recommend products. Instead, they actively help users manage shopping decisions, monitor pricing, surface deals, and eventually complete purchases on their behalf.

Universal Cart also builds on Google’s expanding Universal Commerce Protocol (UCP), which the company described as a shared infrastructure layer meant to make cross-platform shopping and checkout more seamless.

While many marketers have focused heavily on AI-generated search experiences over the past year, this launch suggests Google is equally focused on turning AI into a transactional commerce layer.

Universal Cart Turns Shopping Into A Persistent AI Experience

According to Google, Universal Cart functions as an intelligent shopping cart that follows users across Google properties and participating merchants.

Users can add products while browsing Google Search, chatting with Gemini, watching YouTube, or even reading Gmail. Once products are added, the system continuously works in the background to monitor deals, price drops, inventory availability, and purchase opportunities.

Google says the experience is powered by Gemini models and will continue improving as the models evolve.

One of the more notable elements of the launch is how aggressively Google is positioning Universal Cart as proactive rather than reactive.

The company says the cart can identify product incompatibilities, suggest alternatives, surface loyalty perks, and recommend savings opportunities automatically.

Google also confirmed the system integrates with Google Wallet, allowing the cart to reference payment methods, loyalty programs, and merchant offers during the shopping process.

Some of these checkout features will be rolling out with large merchants including Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair, and other Shopify merchants this summer.

For users building more complicated purchases, such as custom PCs with parts from multiple retailers, Google says the cart can help validate compatibility issues before checkout.

Google Expands The Universal Commerce Protocol

The launch of Universal Cart also serves as a major expansion of Google’s Universal Commerce Protocol initiative.

Google first introduced UCP earlier this year as a common language for commerce systems and AI agents. At I/O, the company confirmed the protocol is already gaining broader retailer and technology partner adoption.

Google says UCP helps enable a smoother checkout process across merchants while still allowing brands to remain the merchant of record.

The company also announced several geographic and vertical expansions tied to the protocol:

UCP-powered checkout is expanding into Canada and Australia, with the U.K. planned later
UCP is coming to YouTube in the U.S.
Google plans to expand into additional commerce categories, including hotel bookings and local food delivery

This portion of the announcement may ultimately matter more to advertisers and retailers than the cart itself.

Google appears to be building a commerce infrastructure layer that connects discovery, shopping behavior, checkout, payments, and AI agents into one ecosystem.

For retailers already investing heavily into Merchant Center feeds, product data quality, and omnichannel commerce experiences, this likely increases the importance of structured product information even further.

What This Means For Advertisers And Retailers

Universal Cart is another strong signal that Google wants shoppers spending more of the purchase journey inside Google-owned experiences.

Historically, Google Search primarily sent users outward to retailer websites. Universal Cart starts pulling more of that activity back into Google itself.

Now, Google is positioning its platforms as the place where users discover products, compare options, monitor pricing, manage carts, and potentially complete purchases.

That creates both opportunities and new challenges for advertisers.

Retailers with strong product feeds, accurate inventory data, loyalty integrations, and competitive pricing may gain stronger visibility across these experiences.

It also increases the importance of Merchant Center optimization beyond traditional Shopping campaigns.

Product data is increasingly becoming the foundation for how products appear across AI-driven discovery surfaces.

The YouTube expansion also stands out to me.

Google continues tying video engagement more closely to shopping behavior and checkout infrastructure. That could create more pressure for brands to think about YouTube as a ecommerce channel, not just a video awareness platform.

From a measurement standpoint: If more shopping activity happens inside Google interfaces, advertisers may need to rethink how they evaluate attribution, assisted conversions, and customer journey reporting across channels.

Looking Ahead

Universal Cart is in its infancy stage, and many of the more advanced agentic commerce features will likely take time to mature.

Even so, this announcement offered a clearer picture of where Google appears to be heading with shopping.

The company is moving beyond AI-enhanced product discovery and deeper into the shopping journey itself.

From product recommendations and cart management to pricing insights and checkout infrastructure, Google is steadily expanding how much of the buying process happens inside its own platforms.

For advertisers and retailers, that could eventually change far more than just where ads appear.

It may also change how brands measure influence, attribute conversions, and compete for visibility during the purchase journey.

Featured image: Courtesy of Google, May 2026

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May 19 2026

YouTube Expands AI Creation Tools With Gemini Omni And Conversational Search via @sejournal, @brookeosmundson

YouTube brought several AI-focused updates to Google I/O this year, but two announcements stood out more than the others.

The platform is introducing a new conversational discovery experience called “Ask YouTube” alongside expanded AI video remixing powered by Gemini Omni.

Together, the updates suggest YouTube is putting more focus on helping users discover content through natural-language interactions while making Shorts creation easier and faster for creators.

YouTube also spent considerable time discussing creator protections alongside the rollout, including watermarking, metadata labeling, opt-out controls, and expanded likeness detection tools tied to AI-generated remixes.

YouTube Introduces “Ask YouTube” Conversational Search

One of YouTube’s bigger AI announcements at I/O was a new conversational search feature called “Ask YouTube.”

According to Google, the experience allows users to search using more detailed questions instead of relying on traditional keyword searches.

Google’s examples included searches like:

Tips for teaching a child to ride a bike
Finding cozy game reviews before bedtime
Refining searches through follow-up questions

Rather than returning a standard list of videos, Ask YouTube compiles content from across YouTube, including both long-form videos and Shorts, into what the company describes as an “interactive, structured response.”

The update pushes YouTube closer to the same conversational discovery experience Google is increasingly building across Search through AI Overviews and AI Mode.

Instead of users manually sorting through results themselves, YouTube’s systems may play a larger role in interpreting intent and organizing recommendations around the query itself.

Ask YouTube is currently available to Premium members ages 18 and older in the United States through youtube.com/new, with broader rollout plans expected later.

Gemini Omni Expands AI Remixing Inside YouTube Shorts

Another major announcement focused on Gemini Omni integration inside YouTube Shorts Remix and the YouTube Create app.

YouTube described Gemini Omni as an upgrade designed to help creators generate new video variations from prompts and images while making remixing faster and easier inside Shorts.

According to the announcement, creators can:

Change scenes into different visual styles
Insert themselves alongside creators
Generate new concepts while preserving context from the original video
Perform more advanced video and audio edits automatically

Google says the system handles more of the editing complexity behind the scenes, reducing some of the technical work traditionally required for video remixing.

What stood out most from YouTube’s presentation was how heavily the company framed these tools around creator participation rather than pure automation.

Many recent AI creative announcements across Google products have emphasized efficiency and scale. YouTube’s messaging leaned more toward helping casual creators participate in trends and create content more easily.

The company also spent significant time discussing creator protections.

AI-generated remixes created through Omni will include digital watermarks, identifying metadata, and links back to original videos.

Creators can also opt out of visual remixing inside Shorts entirely.

YouTube additionally announced expanded access to its likeness detection tool for creators ages 18 and older. The system is designed to help creators identify and manage AI-generated uses of their likeness.

Gemini Omni remixing is rolling out now at no cost inside Shorts Remix and the YouTube Create app.

What These Updates Could Mean Next

Ask YouTube suggests YouTube may gradually shift toward a more conversational discovery experience instead of relying as heavily on traditional search behavior alone.

That could eventually create new challenges for creators, marketers, and advertisers trying to understand how content is surfaced and discovered inside the platform.

Historically, YouTube optimization has depended heavily on measurable signals like search queries, clicks, watch time, thumbnails, subscriptions, and recommendations.

Conversational discovery introduces more interpretation between the user query and the final content recommendation.

That creates a situation where users may become less likely to search using highly trackable keywords and more likely to rely on broader conversational prompts and follow-up questions.

Advertisers are already navigating similar visibility and reporting concerns across AI Overviews and AI-powered Search experiences.

If YouTube continues moving in that direction, measurement and attribution may become increasingly difficult there as well.

Google did not announce any ad-specific changes tied to these updates.

The announcements remained heavily focused on creator tools, remixing capabilities, and user experience improvements.

Still, the longer-term implications around reporting transparency, discovery visibility, and AI-organized content experiences will likely be worth watching as these features expand more broadly across YouTube.

Featured image: gguy / Shutterstock

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May 16 2026

SERP FAQ Removal & New Data Challenge Schema’s AI Search Value via @sejournal, @MattGSouthern

Schema markup had a rough week. Google ended FAQ rich results. Four days later, Ahrefs published a report, finding that adding JSON-LD didn’t produce a clear citation lift across Google AI Overviews, AI Mode, or ChatGPT.

These developments weaken two common pitches for schema markup: increased SERP visibility and potential AI citation gains. This article examines their implications and what the data indicates about schema’s future.

Google’s Visible Schema Rewards Have Been Narrowing For Years

Google has been pulling back visible Search rewards tied to specific structured data types since 2023. Google restricted FAQ rich results to authoritative government and health sites, and HowTo rich results were limited to desktop and later deprecated.

In 2025, Google announced the retirement of several structured data features, including Course Info, Claim Review, and Estimated Salary. Book Actions was initially included but later carved out after Google removed its deprecation banner. Google called the remaining retirements “not commonly used in Search” and no longer providing value to users.

In 2026, Practice Problem structured data was deprecated. John Mueller noted on Reddit that “markup types come and go, but a precious few you should hold on to.”

The pattern is that visible structured data rewards have disappeared after becoming familiar SEO tactics. The markup itself stays valid, but the rich result doesn’t. Google doesn’t always describe these removals as responses to overuse, but the pattern offers less reason to treat any single markup type as a durable strategy.

These recent updates differ because the evidence for one proposed replacement value also weakened. The “GEO” advisory space claims schema boosts AI citations, and Ahrefs data tested part of that.

What The Ahrefs Report Found

Ahrefs tracked 1,885 web pages that added JSON-LD schema. Each page was matched against control pages that never added schema. Citation changes were measured across Google AI Overviews, AI Mode, and ChatGPT.

The results were flat. Google AI Mode showed +2.4%, ChatGPT showed +2.2%, and Google AI Overviews showed -4.6%.

The first two were too small to tell apart from random variation. The AI Overviews decline was statistically significant, but Ahrefs said it can’t confidently attribute that to schema.

Every page in the dataset already had more than 100 AI Overview citations before any schema was added. These pages were already being crawled and cited.

Ahrefs acknowledged that for pages not yet visible to AI, schema might still help with crawling, parsing, or indexing. But their data can’t confirm that.

Gianluca Fiorelli, a strategic SEO consultant, called the study “one of the more honest pieces of research to come out of the AI Search space in 2026.” But he argued the scope was narrower than the headline suggested. He compared it to “testing whether adding a label to a bottle already on the supermarket shelf makes customers pick it up more often.”

Ahrefs also cited a searchVIU experiment that found five AI systems relied on visible HTML during direct page retrieval and did not use hidden JSON-LD, Microdata, or RDFa. That finding covers one stage of the pipeline. It does not rule out schema playing a role earlier in indexing or entity understanding.

Ryan Law, Ahrefs’ director of content marketing, summarized the finding on LinkedIn, saying:

“Does adding schema markup help your pages get cited in AI search? Probably not,” he wrote. He added that schema is “probably not some magic fix for improving your AI citations.”

The Practitioner Debate

Both updates land in the middle of an active argument about schema and GEO.

Roughly 168,000 pages use the phrase “FAQ schema is critical for GEO,” according to search results that Lily Ray, VP of SEO and AI Search at Amsive, flagged on LinkedIn. She called the trend familiar.

“Anything that can be spammed in SEO, will be spammed,” Ray wrote. She’d warned about this in a 2019 Moz article when FAQ schema first launched, and described Google’s FAQ removal as the same cycle repeating.

Ray hedged throughout her post, calling it “putting on my tin foil hat” and “just an idea.” But the pattern she described is the same one visible in the timeline above. A useful markup type gets scaled as a tactic, Google pulls the reward, and the industry moves on to the next one.

Joost de Valk, founder of Yoast, made the connection explicit in a blog post. “The GEO industry is replaying early SEO, just faster,” de Valk said. “And the FAQ schema deprecation is the first concrete proof point that the cycle is back on.”

He also filed a Schema.org proposal for a new FAQSection type to address what he sees as the structural problem, separating “this page has an FAQ section” from “this page IS an FAQ.”

The frustration was sharpest from practitioners who’d been watching the GEO playbook harden around schema as its most concrete recommendation. Mark Williams-Cook, director at Candour and founder of AlsoAsked, shared the Ahrefs report on LinkedIn.

“GEO bros are selling snake oil with schema to boost citations, but people like Gianluca Fiorelli are talking sense,” he posted.

Marie Haynes, founder of Marie Haynes Consulting, commented on Ray’s post with a different theory altogether.

“My theory is that Google needed our FAQs to train AI so they gave us incentive to add them (aka rich results.) And now they don’t need them anymore,” she wrote. The theory is unconfirmed by any primary source, but it shows how far the speculation has traveled.

Some practitioners pushed back on the gloomier readings. Google’s broader guidance still presents structured data as a way to make page information machine-readable, and at a 2025 Search Central Live event in Madrid, the Search Relations team told practitioners that supported structured data types are still worth using.

What The Data Can’t Answer Yet

Whether schema helps pages that aren’t yet being cited is a separate question that the data can’t answer, because every page already had more than 100 AI Overview citations before schema was added.

The test also pooled all schema types together. Article, FAQ, Product, HowTo, and Organization were all treated as one category. Type-specific effects haven’t been isolated, and they could look different.

The 30-day measurement window may miss slower effects, and on live websites, schema changes can overlap with other page changes, making it hard to separate what schema did from what changed around it. The report only examined schema in the page’s HTML, not schema injected via JavaScript, which AI crawlers treat differently.

Ahrefs measured Google AI Overviews, AI Mode, and ChatGPT. Whether Bing, Copilot, Perplexity, Claude, or other answer systems treat schema differently from the systems Ahrefs measured is an open question.

Google’s FAQ deprecation notice says the company will continue using FAQ structured data to “better understand” pages. What that produces in measurable terms is unclear. The same uncertainty applies to whether schema affects citations indirectly, through eligibility, entity understanding, or source selection, rather than during the direct retrieval that searchVIU tested.

Nobody has published data that isolates that path.

Why This Matters

The Ahrefs data gives no measured reason to add JSON-LD, expecting short-term AI citation gains for pages already visible in AI Overviews. The trickier question is what to do with schema strategies more broadly.

Product, Review, Event, Video, and some other structured data types still support active rich result features. Organization, Person, and Article markup can still help describe entities and content, even when the payoff is less visible.

A blanket “schema doesn’t work” reading overstates what the data showed, because the test pooled all types and measured only one outcome. What the data does challenge is a specific sales pitch.

“Add schema to boost AI citations” has been one of the more concrete recommendations in GEO guides. For example, Frase.io called schema markup “critically important for AI search, GEO, and AEO.”

Without data support for that claim, it’s harder to justify the investment. AI systems in searchVIU’s test relied on visible HTML during retrieval, not JSON-LD. That suggests content structure, clear headings, and direct answers in prose may matter more for AI citation than markup structure.

Looking Ahead

The question hanging over the SEO industry is where schema creates measurable value. Adding JSON-LD didn’t measurably increase AI citations for pages already visible in AI Overviews.

For those pages, schema looks more like plumbing that serves other systems than a lever that moves citation counts. That’s still real value, but it’s a different pitch.

Featured Image: BEST-BACKGROUNDS/Shutterstock

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May 15 2026

Google’s New AI Search Guide Calls AEO And GEO ‘Still SEO’ via @sejournal, @MattGSouthern

Google published a new documentation page to help websites optimize for generative AI features in Search, including AI Overviews and AI Mode.

The page, “Optimizing your website for generative AI features on Google Search,” expands Google’s prior AI features documentation published in 2025. The earlier page explains how AI features work, how inclusion is controlled, and how performance is reported. The new guide focuses more directly on optimization advice and tactics Google says site owners can ignore.

Two sections are specifically worth highlighting. Google directly names popular optimization tactics it says aren’t necessary, and it redefines the AEO/GEO conversation as part of standard SEO.

Google Says AEO And GEO Are ‘Still SEO’

Google opens by confirming that foundational SEO best practices remain relevant for generative AI search. Its AI features are “rooted in our core Search ranking and quality systems” and rely on retrieval-augmented generation (RAG) and query fan-out to surface content from the Search index.

On the terminology debate, Google is direct. It defines “AEO” as “answer engine optimization” and “GEO” as “generative engine optimization,” then states:

“From Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.”

This echoes positions Google employees have taken at conferences. Gary Illyes and Cherry Prommawin told Search Central Live attendees that GEO and AEO don’t require separate frameworks. The position now appears in Google’s published documentation, providing an official reference to cite.

What Google Says You Don’t Need To Do

The guide includes a “Mythbusting generative AI search” section listing tactics it calls unnecessary for Google Search. The guide is more explicit than Google’s prior AI features page, particularly in naming llms.txt, chunking, inauthentic mentions, and AEO/GEO directly.

The guide says site owners can ignore the following for Google Search.

On llms.txt files and other “special” markup, Google says you don’t need to create machine-readable files, AI text files, markup, or Markdown to appear in generative AI search. Google may discover and index many file types beyond HTML, but that doesn’t mean those files receive special treatment.

On “chunking” content, the guide says there’s no requirement to break content into small pieces for AI systems. Google’s systems “are able to understand the nuance of multiple topics on a page and show the relevant piece to users.” Danny Sullivan made similar comments in January 2026, saying he’d spoken with Google engineers who recommended against chunking.

On rewriting content for AI systems, Google says AI systems can understand synonyms and general meanings. Site owners don’t need to capture every long-tail keyword variation or write in a specific way for generative AI search.

On seeking inauthentic “mentions,” the guide acknowledges that AI features can surface what’s said about products and services across blogs, videos, and forums. But it says seeking inauthentic mentions “isn’t as helpful as it might seem” because core ranking systems focus on quality while other systems block spam.

On structured data, the guide says it isn’t required for generative AI search and there’s no special schema.org markup to add. It recommends continuing to use structured data as part of an overall SEO strategy for rich results eligibility.

Several recommendations run counter to advice that appears in some AI search optimization guides. Multiple GEO resources have promoted chunking and structured data as priorities for AI search visibility.

What Google Says To Focus On

The optimization advice follows familiar SEO territory, though Google contextualizes it for AI features.

Google puts particular emphasis on “non-commodity content.” It contrasts commodity content (“7 Tips for First-Time Homebuyers”) with a non-commodity alternative (“Why We Waived the Inspection & Saved Money: A Look Inside the Sewer Line”). The distinction is whether content provides unique insight beyond common knowledge.

On the technical side, pages must be indexed and eligible for snippets to appear in generative AI features. Google recommends following crawling best practices, using semantic HTML where possible, following JavaScript SEO best practices, providing good page experience, and reducing duplicate content.

Local and ecommerce optimization gets its own section. Google recommends Merchant Center feeds and Google Business Profiles for product and local business visibility in AI responses. It also mentions Business Agent, a conversational experience that lets customers chat with brands on Google Search.

Agentic Experiences Get Initial Guidance

A new section on agentic experiences describes AI agents as “autonomous systems that can perform tasks on behalf of people, such as booking a reservation or comparing product specifications.”

Google notes that browser agents may access websites by analyzing screenshots, inspecting the DOM, and interpreting the accessibility tree. The guide links to web.dev’s guide to agent-friendly website best practices and references the Universal Commerce Protocol (UCP) as an emerging protocol that “will allow Search agents to do more.”

Google announced UCP earlier this year, and Vidhya Srinivasan’s annual letter said it was co-developed with Shopify with more than 20 companies endorsing it.

Why This Matters

This guide gives Google’s most explicit guidance yet on what you should and shouldn’t do for generative AI features in Search. It consolidates positions that were previously scattered across conference talks, podcast appearances, and blog posts into a single reference.

The mythbusting section carries the most weight. Google is now telling you in its own documentation to skip tactics that a growing industry of AEO/GEO services has been promoting. That doesn’t settle the debate for non-Google AI platforms like ChatGPT or Perplexity, which may weight signals differently. But for Google’s own AI features, the guidance is now on record.

The agentic experiences section puts browser agents and UCP into Google’s official documentation for site owners. The guidance is early, and Google frames it as optional for businesses where agent access is relevant.

Looking Ahead

Google’s closing section says you don’t need to accomplish everything in the document to succeed. It notes that “plenty of content thrives in Google Search (including generative AI experiences) without any overt SEO at all.”

The agentic experiences guidance is labeled as something to explore “if this is something that’s relevant to your business and you have extra time.” That suggests Google sees agent optimization as forward-looking rather than urgent.

Featured Image: Anatolir/Shutterstock

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