Agentic search optimization (ASO) is the practice of making your brand discoverable, parseable, and trustworthy to AI agents that compare options and act on a user's behalf. It sits next to SEO and generative engine optimization (GEO) as the third layer of how brands earn visibility in AI-mediated discovery.
The term became a named discipline in April 2026 when Adobe completed its acquisition of Semrush and put the acronym into mainstream marketing vocabulary. This page is the working definition I use with clients, the framework I think practitioners should adopt, and the honest read on what's hype and what's signal.
The short definition of agentic search optimization
ASO is the practice of optimizing a brand's content, data, and trust signals so that AI agents acting on a user's behalf can discover, evaluate, and select that brand during autonomous tasks like comparison shopping, vendor shortlisting, or transaction completion.
If GEO is "make sure the LLM cites you in its answer," ASO is "make sure the agent picks you when it's choosing on the user's behalf."
That second framing is the one that matters, because the user isn't reading the answer anymore. The agent is reading the answer and acting.
How we got here: the four-layer stack
The optimization stack has added a layer roughly every two years. Each layer adds to the previous one, and it’s important to remember that none of them replaces what came before.
The Four-Layer Stack
SEO → AEO → GEO → ASOWhy ASO is happening now
Three numbers explain the urgency.
Adobe's own analytics show AI traffic to U.S. retail sites jumped 269% year over year in March 2026. Loni Stark, VP of strategy and product at Adobe, told Marketing Brew the Q1 number is closer to 393%. Separately, Stark noted that traffic referred from LLMs converts at a higher rate than average traffic, meaning AI visibility has moved from vanity metric to pipeline metric.
The protocol layer is what makes agentic, specifically, possible. Model Context Protocol (MCP) lets agents pull from your systems directly. Agent Communication Protocol (ACP) handles agent-to-agent interactions. Google's Universal Commerce Protocol (UCP) is doing the same for shopping. Adobe is selectively adopting parts of these depending on which ones are actually being used by brands and customers; MCP adoption has been strong, ACP has been slower, UCP is still mostly product-discovery rather than transactional.
Translation - agents have started to act on real data, but the protocols and behaviors are still settling. ASO is a long-horizon discipline.
What ASO requires that GEO didn't
Three things changed when the agent became the actor:
Machine-readability moved from optimization to entry requirement:
If an agent can't parse your product catalog, your service offerings, your pricing, or your availability, you're functionally invisible at the moment of decision. Schema.org markup, structured product data, and consistent entity definitions are no longer just ranking enhancers. Adobe Commerce updates explicitly call out catalog enrichment and product page optimization for AI-driven shopping journeys.Citation persistence began to matter more than citation frequency:
A reasoning agent doing a comparison task won't cite forty sources. Agents anchor on a few key sources that it trusts and will reason from there. Showing up once in a generated answer is still a win, but surfacing in a small set of brands an agent consistently anchors to when reasoning through a category is a different kind of win that puts your brand in an exclusive category.Trust signals shifted in weight:
Reasoning models care more about coherence across surfaces than ranking algorithms ever did. If your brand says one thing on your site, a different thing on G2, and a third thing in a podcast transcript, a reasoning model has nothing to anchor on.
The ASO readiness checklist
Six things to work on, in rough order of difficulty.
A clean structured product or service catalog that an agent can actually parse.
For services, that means proper Service schema, clear pricing or pricing logic, and consistent descriptions across your site, your profiles, and any third-party directories. For products, it means catalog completeness and consistency at a level most B2B sites haven't bothered with.Schema implementation depth.
JSON-LD on every page that matters, with linked entity definitions (Person, Organization, Service, Product, FAQPage, BreadcrumbList) and sameAs arrays pointing to your authoritative profiles elsewhere on the web. The goal is a clean knowledge graph an agent can traverse without guessing.A brand coherence audit across surfaces.
Pull what your brand says about itself from your site, your LinkedIn, your G2 or Capterra profile, your Wikipedia entry if you have one, and any podcast transcripts or guest posts. If the descriptions don't agree, fix them. Reasoning models will pick the description that appears most consistently across the most authoritative surfaces.A point of view on Model Context Protocol.
Whether you build MCP endpoints or not is a strategic question, not a tactical one, but you should at least know whether your category has any early movers experimenting with it. If your competitors are exposing inventory or service-availability endpoints to agents, you'll want to know.Tracking that measures consideration-set inclusion, beyond raw citation frequency.
Adobe's LLM Optimizer is one approach. Conductor's AgentStack and Siteimprove's AEO Insights are others. Semrush, now inside Adobe, is doing the same. The market will sort itself out over the next year, but you should be measuring something today, even if it's a manual quarterly audit of how the major LLMs answer your top ten category queries.A third-party citation portfolio.
Off-site mentions in authoritative sources are where AI models build their confidence in your brand. Guest posts, podcast appearances, press mentions, listicle inclusions, and high-authority directory listings all contribute.
You can also test your content right now with the free AI Brand Visibility Analyzer, which scores your content across SEO, AEO, and GEO.
Want help building an integrated SEO, AEO, & GEO strategy for your organization? Jarred works directly with marketing teams through consulting, speaking, & workshops.