AI Mode (Google)

AI Mode is a search experience in Google Search where you ask a question and get a written, cited answer instead of a list of ten blue links. It runs on a custom version of Google’s Gemini models, keeps the conversation going so you can ask follow-up questions, and accepts text, voice and images as input. Where an AI Overview is a summary placed on top of the normal results page, AI Mode is a full-page, multi-turn answer experience of its own.

How it works

The central mechanism is query fan-out. When you type a question, AI Mode does not run that single query. It breaks the question into sub-topics and issues many related searches at the same time, then retrieves passages from the pages those searches surface and writes one answer with links to its sources. MLforSEO’s Semantic Keyword Research course uses the example “best running shoes”: behind the scenes the system generates related, implicit and comparative synthetic queries such as top-rated athletic footwear or shoes for a particular foot type, and each of them retrieves its own documents.

A few points about the product, as of Google’s announcements up to October 2026:

• It launched as a Search Labs experiment in March 2025, rolled out to everyone in the US in May 2025 and expanded to more than 200 countries and territories in October 2025.
• It is multimodal: it combines Google Lens with Gemini, so you can ask about a photo, and a “visual search fan-out” looks at secondary objects in an image as well as the main subject.
• Google’s documentation says there are no extra technical requirements to appear as a supporting link. A page has to be indexed and eligible to show in Search with a snippet.

How it’s used in SEO and marketing

• Coverage planning: because one question becomes many sub-queries, pages that clearly answer specific sub-questions have more chances to be retrieved. This is why MLforSEO pushes semantic keyword research and entity coverage over single-keyword targeting.
• Citation tracking: SERP APIs such as DataForSEO return AI Mode references, so you can monitor which of your pages are cited and compare that with classic rankings.
• Architecture: pages with one clear purpose and descriptive internal links are easier for fan-out retrieval to pick up.
• Visual assets: since AI Mode reads images, original, well-labelled imagery and video can surface in answers.

Example

A retailer tracks “best running shoes for flat feet”. In AI Mode the answer cites a podiatry guide, a brand comparison table and a forum thread, none of which rank in the top three for the original keyword. Each was retrieved by a different fan-out query (arch support, stability versus motion control, user experiences). The retailer’s response is to add sections that answer those sub-questions directly, with specific, verifiable facts.

Limitations and things to watch

• Fan-out queries are invisible. You can simulate them, but you cannot see the exact set Google ran for a given user, and they vary with context.
• Rank tracking alone undercounts AI Mode visibility; citations and mentions need their own measurement.
• The product changes quickly. Treat launch dates, features and country lists as a snapshot and check Google’s own announcements.

Learn it on MLforSEO

• Semantic ML-enabled Keyword Research, including the bonus module on query fan-out in AI Mode
• AI Search Optimisation and Agentic SEO
• Blog and Site Architecture for SEO and Conversions in the AI Search Era
• Image SEO in 2026: multimodal search and AI Mode
• 10 Ways to Automate SERP Analysis with AI