AI search is the search format where a large model generates the answer directly: the user asks a question, the AI retrieves and synthesizes multiple sources, and responds with one composed answer, often with citations, instead of a page of links.
Also known as AI search engines · generative search
The break from traditional search
Traditional search is a retrieval tool: you give keywords, it gives links, and the comparing is your job. AI search is an answering system: you give a question, it gives a conclusion: retrieval, reading, comparison, and synthesis happen where you can’t see them.
That redraws how attention is distributed. On a results page, positions one through ten all catch some eyes; in an answer, the AI typically names two or three brands. Selection has moved from the user’s hands to the AI’s, and the brand’s competitor is no longer the other nine links, but the AI’s model of the category.
The main formats
Four formats currently coexist:
- Conversational assistants: ChatGPT, Claude, Gemini, Doubao, DeepSeek, Kimi: users ask directly; recommendations live inside the reply.
- AI-native search engines: Perplexity and peers: answer first, citations alongside.
- AI modes of traditional engines: Google’s AI Overviews and equivalents: an answer block above the classic results.
- Agent execution: the AI doesn’t just answer but acts: filtering, comparing, booking. The recommendation becomes the transaction.
Chinese and Western ecosystems are separate worlds: different models, different search backends, different content sources. A brand’s visibility can differ wildly between engines and must be managed and measured per engine.
Three user-behavior shifts
- Zero-click as default: if the answer suffices, no page visit follows; the brand touchpoint moves inside the answer.
- Questions replace keywords: “law firm Shanghai M&A” becomes “which Shanghai firms are strong on cross-border M&A?” (longer, more specific, more answerable).
- Trust is front-loaded: an AI answer implies “already screened for you”; making the answer is itself an endorsement.
For brands the conclusion is one line: invisible means nonexistent. For the way in, start with AI answer visibility and the industry guides.
Will AI search replace traditional search?
It's diverting traffic, not flipping a switch. Fact-finding, advisory, and comparison queries migrate fastest: they want answers, not links. Navigational and transactional queries still run heavily through traditional search. The practical takeaway for brands: both gateways now need managing; neglecting either forfeits a channel.
Where do AI search answers come from?
Two places: what the model learned in training, and what it retrieves live at answer time (retrieval-augmented generation). Brands therefore need presence in both: consistently recorded across the sources models learn from, and easy to fetch, parse, and cite at retrieval time.
How does a brand get into AI search answers?
Be fetchable (crawlable infrastructure), comprehensible (clear structure, conclusions stated plainly), credible (authority signals and genuine reviews), and quotable (structured data, citable phrasing). That engineering practice is GEO (Generative Engine Optimization), and its outcome is AI answer visibility.