Google AI Mode usage data shows search is getting longer, multimodal, and more decisive

Google AI Mode usage data finally puts numbers on a shift SEO teams have been feeling for months. AI search is no longer a side experiment. Google says AI Mode now has more than 1 billion monthly active users globally, query volume has more than doubled every quarter since launch, and the average AI Mode query is three times longer than a traditional search.

The more important signal is behavioral. In the U.S., follow-up queries are increasing by more than 40% per month on average, more than one in six AI Mode searches are non-text, and planning and decision queries are growing faster than overall usage. If your search strategy still assumes one keyword, one page, and one click, this data is a warning.

What did Google actually reveal after one year?

The headline numbers are simple, but they matter. One year after AI Mode launched in the U.S. in May 2025, Google says the product has passed 1 billion monthly active users globally and that AI Mode queries have more than doubled every quarter since launch.

Google also says search behavior inside AI Mode looks meaningfully different from classic web search. The average query is three times longer. Both short and long queries are growing, which means AI Mode is not replacing traditional search patterns so much as widening the range of ways people ask for help.

That distinction matters. The shift is not just toward longer prompts. It is toward more expressive prompts. Google’s top AI Mode query words include terms like information, identify, find, explain, and summarize. Common first words include what, how, I, is, and can. The presence of “I” in that mix suggests a more personal, task-oriented, conversational style than traditional search has usually captured.

• Global scale: more than 1 billion monthly active users
• Growth rate: AI Mode queries have more than doubled every quarter since launch
• Query length: the average search is triple the length of a traditional query
• Conversation depth: follow-up queries in the U.S. are up more than 40% per month on average
• Multimodal behavior: more than one in six searches use voice, images, video, or other non-text inputs

Why do longer and follow-up queries matter for SEO?

They matter because AI search is moving away from keyword compression and toward problem expression. People are no longer trying to guess the shortest possible phrase that will unlock a useful result. They are asking the full question.

Google’s own examples make that clear. Instead of searching for a destination plus a few modifiers, users are asking for full trip plans with local food, must-see sites, and places to avoid crowds. Instead of searching for a generic restaurant term, they ask for a date-night spot with a certain vibe and specific dietary options. Instead of searching for a product category, they ask which option fits a need, price point, or context.

That changes what strong content looks like. A thin page built to target one keyword may still rank in classic search, but it is less useful when the system needs to answer layered questions, handle follow-ups, or compare options. This does not mean keyword research is dead. It means keyword research is no longer enough on its own.

There is nuance here. Google says both short and long queries are growing in AI Mode. So the future is not purely conversational. It is mixed. Brands still need sharp retrieval for direct questions, but they also need coverage for the second and third turn, where the user narrows the choice or adds constraints.

Where is AI Mode behavior shifting fastest?

The fastest shifts are happening in planning, decision support, multimodal search, and creative tasks. Those are the areas where AI Mode is not just returning links. It is helping users shape a next step.

Planning-related queries have grown 80% faster than AI Mode queries overall over the past six months, according to Google. That includes things like schedules, to-do lists, exercise plans, travel itineraries, and restaurant planning. Google also highlights strong usage around Canvas, its planning workspace inside AI Mode, for vacation planning, fitness routines, budgeting, and household organization.

Decision-oriented behavior is moving quickly too. Searches beginning with “which” grew 40% faster than overall AI Mode queries over the same six-month period. Google specifically points to the rise of phrases like “which of” and “which one,” which suggests users are using AI Mode to compare and narrow, not just discover.

Multimodal behavior is another big signal. More than one in six AI Mode searches are non-text, and image-input searches have grown more than 40% month over month since launch. That means AI search is becoming less keyboard-bound. Brands should expect more journeys that start with a screenshot, a photo, a spoken question, or a live visual context.

Creative use is rising as well. Since early 2026, image creation queries in AI Mode have more than tripled. Google says users are asking AI Mode to create or edit photos, quizzes, logos, stories, code, documents, videos, notes, and summaries. In other words, AI Mode is not only a research layer. It is increasingly a working layer.

What does this say about shopping, local, and research behavior?

It says classic search still often starts the journey, but AI Mode is increasingly where users think through the decision. Google notes that shoppers often begin with traditional Search and then move into AI Mode for deeper follow-up questions.

The categories where this behavior shows up most include electronics, books and media, apparel, health and beauty, and automotive. Once users enter AI Mode, the follow-ups get practical fast. Google highlights store-related questions around “near me,” replacement parts, dealership financing, online options, and whether something is in stock.

The same pattern shows up in local search. Restaurant follow-ups are less about generic discovery and more about fit. Users want kid-friendly places, views, bars, vegan or vegetarian options, private rooms, live music, dog-friendly spots, and outdoor seating. That is a strong reminder that “best restaurant” or “best store” is rarely the real query anymore. The real query is contextual.

Education and professional development show a similar change. Google says AI Mode is being used to build quizzes and study guides for subjects like math, Spanish, history, English, and biology. It also sees growth in follow-up searches around credentials such as Security+, Network+, the bar exam, real estate licensing, CPA, and Scrum Master paths. Search is becoming less about finding a page and more about progressing through a task.

BotRank's Take: the real unit of visibility is the conversation

Google’s numbers confirm something many teams still underestimate: in AI search, visibility is not stable at the single-query level. A brand can appear in the first answer, disappear in the follow-up, then get replaced when the user adds a constraint like budget, location, or style. That instability gets even harder to read when more journeys include image input, voice, and multi-step planning.

This is exactly where BotRank’s AI Visibility feature becomes useful. It lets teams create reusable prompts, run them across multiple LLMs, compare how a brand and its competitors appear over time, and inspect the sources and brand mentions behind those answers. In a world where AI Mode queries are longer and follow-up behavior is accelerating, that kind of measurement stops being optional. It becomes the only practical way to understand whether your brand is actually present in the moments that shape consideration and choice.

What should brands and SEO teams do next?

The takeaway is not that every page should turn into a chatbot transcript. The takeaway is that content and technical SEO both need to support richer question paths.

• Map decision journeys, not just keywords. If users are increasingly asking “which one” or “where should I,” your content should support comparison, trade-offs, and scenario-based choices.
• Build for follow-up questions. Product, service, and category pages should answer the next question, not just the first one. Price, availability, location, fit, alternatives, and constraints matter.
• Cover attributes people actually use to decide. Google highlights signals like price, brand, color, availability, size, material, and location in retail, plus dietary needs and vibe in local search.
• Prepare for multimodal discovery. Images, structured product detail, descriptive alt text, and clear page entities matter more when users start with a photo or voice query instead of typed text.
• Track AI visibility by scenario. A brand may perform well for broad discovery prompts and poorly for comparison or local-intent prompts. Measurement needs to reflect that reality.

There is also a strategic lesson in Google’s five usage buckets: Explore, Decide, Learn, Create, and Do. These are not just product categories inside AI Mode. They are a useful model for content planning. Brands that only publish top-of-funnel explainers will miss the “Decide” and “Do” moments where revenue is often closer.

FAQ

What is Google AI Mode?

Google AI Mode is Google’s conversational search experience that combines traditional search capabilities with Gemini-powered reasoning and multi-turn interaction. It launched in the U.S. in May 2025.

Is AI Mode replacing traditional Google Search?

Not entirely. Google’s own data suggests users still often begin with traditional Search, especially for shopping, then move into AI Mode for deeper questions and decision support.

What kinds of queries are growing fastest in AI Mode?

Google highlights strong growth in planning, brainstorming, decision-making, multimodal input, and creative tasks. Planning-related queries and “which” queries are growing faster than overall AI Mode usage.

Why should brands care about longer AI queries?

Longer queries usually carry more context, constraints, and intent. That makes visibility harder to win with shallow pages and easier to lose if your content cannot support follow-up questions.

What is the practical next step for SEO teams?

Start by identifying the prompts that matter most to your brand across discovery, comparison, local intent, and planning. Then measure how often your brand appears, how it is described, and which sources AI systems rely on to build those answers.

Google’s first AI Mode numbers do not just show a bigger product. They show a different search behavior. The teams that adapt fastest will be the ones that stop optimizing for isolated keywords and start optimizing for the full decision path. If you want to see how your brand actually appears in those AI-driven journeys, BotRank is the right place to start.