Agentic Search
Definition
Search where an AI agent acts for the user, monitoring options, calling businesses and completing the task, instead of returning a list of links for a human to read.
The shift that matters is not "search but smarter". The shift is that an agent makes a single call. A human scanning ten results clicks two or three; positions four through ten still earn traffic. An agent picks one option, dials it, and the job is done. The long tail of "good enough" listings collapses to a binary: cited or invisible. For a service business, that is a different game.
Google's I/O 2026 announcements made the layer official. Information Agents monitor the web for the user. Agentic Booking holds a slot once it finds one. Agentic Calling rings the business and completes the task by phone. Gemini drives the loop. The underlying protocols are public: MCP for tool access, function-calling for action, JSON-LD for the structured signal the agent reads first. Gartner's agentic AI research places agentic systems as the next dominant interaction layer; Anthropic's research on agent reliability sets the pattern that the action-shaped model is here, not a future bet.
A concrete one. Saturday morning, a pipe bursts in a Brunswick kitchen. The homeowner asks Gemini to handle it. The agent checks three plumbers within five kilometres, filters for "open now" and "emergency callout", calls the first one, confirms a 90-minute ETA, books, and tells the owner who to expect. The owner did not read a single page. Two of the three plumbers were never even considered.
The implication for AI Search Optimisation is structural. Brand mentions and citation surface still matter, but the load-bearing work shifts to machine-extractable signal: LocalBusiness schema with real opening hours, a callable phone number, services named and scoped, sameAs links across Google Business Profile and Bing Places. Live availability beats clever copy. An AI agent acting as the buyer needs structured truth, not a beautifully written about-page. Sites that ship that layer get picked; sites that do not get skipped silently. UnderCurrent Automations builds the agent-readable layer as part of SEO & AI Visibility, because the binary outcome is already here for the queries that convert.
Common questions
How is agentic search different from AI search like ChatGPT or Perplexity?
ChatGPT and Perplexity synthesise an answer for a human to read. Agentic search goes one step further: the agent acts. It calls the plumber, books the appointment, fills the form, then reports back. The output is a completed task, not a paragraph.
Does agentic search kill the long tail?
For task-completion queries, yes. When a human scans ten results, places two and three still get clicks. When an agent picks one option and dials it, place two gets nothing. The outcome collapses to a binary: cited or invisible. The long-tail traffic pattern only survives for browse and research intent.
What does an Australian SMB need to do to be picked by an agent?
Three load-bearing things. Machine-extractable structured data (LocalBusiness JSON-LD, services priced or scoped). Live availability (hours, booking link, an answered phone). Entity clarity across Google Business Profile, Bing Places and your site. Without all three, an agent will skip you and call the next listing.
