AI Mode is Google’s dedicated AI-powered search interface — a full-page conversational search experience separate from standard Google Search. Announced at Google I/O 2025, AI Mode allows multi-turn conversations, complex multi-step queries, and deep research tasks powered by Gemini.
AI Mode vs. AI Overviews
| Feature | AI Overviews | AI Mode |
|---|---|---|
| Location | Embedded in standard search results | Dedicated tab/interface |
| Query complexity | Single-turn, relatively simple queries | Multi-turn, complex research |
| Response format | Brief summary with citations | Extended, conversational responses |
| User intent | Most regular Google searches | Deep research, complex tasks |
| Availability | Default for eligible queries | Opt-in feature (initially US) |
Why AI Mode matters for brand visibility
AI Mode represents a significant expansion of the surface area where brands need AI visibility. Users conducting deeper research — product evaluations, comparison analyses, market research — are more likely to use AI Mode than AI Overviews, making it particularly high-value for B2B and considered-purchase brands.
AI Mode’s multi-turn capability means brand visibility depends not just on appearing in initial responses but on sustaining that presence across follow-up queries in a research session.
Optimizing for AI Mode
AI Mode draws on the same signals as AI Overviews — Google’s Gemini model, live web retrieval from Google’s index, and E-E-A-T signals — so existing AI Overviews optimization strategies apply. Additional considerations:
- Comprehensive content: Deep research queries benefit from comprehensive, well-structured pages that cover a topic fully — AI Mode is more likely to retrieve and synthesize from multiple sections of a long page
- Follow-up anticipation: Create content that addresses the natural follow-up questions to your primary topic — multi-turn sessions surface related content from the same domain when trust is established
- Structured entity data: Clean schema markup helps Gemini correctly understand brand and product attributes across complex synthesis tasks