AI Agents and Agentic Search

Agentic search is a form of search where an AI agent does more than answer a question: it plans steps, browses websites, compares options and can complete tasks such as filling forms or making bookings for the user. AI agents are the software systems that carry out this work, using a language model to decide what to do next.

Written by Paul Hoda, SEO consultant since 2005. Last updated 8 November 2026.

How agentic search works

A traditional search engine returns links, and the user does the rest. An AI agent takes a goal, such as find a family-friendly hotel in York under a set budget, and works through it. Typically it will:

  1. Break the goal into smaller searches, similar to query fan-out.
  2. Visit websites, read pages and sometimes interact with them using a browser.
  3. Compare options against the user’s requirements.
  4. Report back with recommendations, or take an action if the user allows it.

Several major AI products now include agent features that can browse the web and complete multi-step tasks, usually asking the user to confirm before purchases or other sensitive actions. Capabilities are developing quickly and vary by product and region.

Why it matters for site owners

If agents become a common way to research and buy, some visits to your site will come from software acting for a person rather than the person directly. An agent may never notice your design or brand messaging. It needs to find accurate facts quickly and complete actions without getting stuck. Sites that are hard for agents to use risk being skipped in favour of competitors whose information is clearer.

How to make your site agent-friendly

  • Clear, crawlable content: keep key information in HTML text rather than images or content that only loads after complex scripts. JavaScript SEO principles apply.
  • Structured facts: use schema markup for products, prices, availability, opening hours and locations.
  • Simple forms and checkout: clear labels, logical steps and few unnecessary obstacles help both agents and people.
  • Accessible markup: agents often rely on the same signals as assistive technology, such as proper labels and semantic HTML, so accessibility work helps here too.
  • Consistent data: make sure prices and stock match across your site, feeds and marketplaces.
  • Bot access decisions: review how you treat AI crawlers and agent user agents in robots.txt and security tools, so you do not block helpful agents by accident.

Measuring agent activity

Agent visits can be hard to spot. Some identify themselves with a user agent string, while others use ordinary browser signatures. Server logs and bot management tools give the best view. Conversions completed by agents may appear as ordinary sessions in analytics.

Common misconceptions

  • Agents do not replace SEO. They still rely on search indexes and readable pages to find information.
  • There is no single ranking system for agents to optimise against. Each product works differently.
  • Blocking all bots is not a neutral choice. It may stop agents from recommending your business.

Key Takeaways

  • Agentic search uses AI agents that plan steps, browse sites and complete tasks.
  • Agents need clear facts and usable pages rather than persuasive design.
  • Structured data, crawlable HTML and simple forms make sites easier for agents.
  • Accessibility improvements also help agents navigate your site.
  • Review bot access rules so helpful agents are not blocked by accident.

Related Terms

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