Definition
Agentic search is a major evolution in online search where autonomous AI agents perform complex, multi-step, and iterative research tasks on behalf of the user. Unlike traditional search where the user formulates a query and browses results, search agents break down a complex question into sub-tasks, consult multiple sources, synthesize information, and present a complete answer. Examples include Google Gemini's 'Deep Research' mode, Perplexity's 'Deep Search', and ChatGPT's research agents. For SEO, agentic search is a game changer: agents evaluate source reliability, favor structured and factual content, and can visit and analyze complete pages rather than being limited to snippets. This reinforces the importance of E-E-A-T, content structure, and topical depth.
Key Points
- Autonomous AI agents performing multi-step research for the user
- Examples: Gemini Deep Research, Perplexity Deep Search, ChatGPT agents
- Reinforces the importance of E-E-A-T and content depth
Practical Examples
Complex purchase research
A user asks an AI agent 'find me the best link building tool for a French SMB'. The agent performs multiple searches, compares options, analyzes reviews, and presents a synthesized recommendation.
Impact on SEO
With agentic search, your content must be sufficiently in-depth and structured for an AI agent to select it as a reliable source in its multi-source synthesis.
Frequently Asked Questions
No, but it transforms it. Traditional SEO remains essential for visibility in classic SERPs. Agentic search adds an additional layer where content depth, structure, and authority become even more critical.
Create in-depth, structured content with factual data, cited sources, and demonstrated expertise. AI agents favor reliable and well-organized sources to build their syntheses.
Go Further with LemmiLink
Discover how LemmiLink can help you put these SEO concepts into practice.
Last updated: 2026-02-07