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    Home»SEO & Digital Marketing»How AI agents decide which brands make the cut
    SEO & Digital Marketing

    How AI agents decide which brands make the cut

    adminBy adminMarch 31, 2026No Comments7 Mins Read
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    Six card grid showing what AI agents evaluate on websites including pricing clarity, feature specifics, reviews, corroboration, structured data, and audience
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    You’re already outsourcing decisions you used to own.

    Think about the last time you asked ChatGPT or Gemini to find something for you. A tool, a restaurant, a recommendation for someone hard to buy for. You probably skimmed what it came back with, checked one or two links, and went with it. 

    The AI agent did the research. You just approved.

    That was the early version. Now, Google, OpenAI, Microsoft, and Anthropic are building infrastructure that doesn’t just let AI find information — it lets AI act on it. Book a table. Start a free trial. Complete a checkout. On your behalf, without you in the room.

    This is the agentic web. And researchers have a name for the behavioral shift underneath it: the delegate economy. It’s redefining how we drive brand visibility in 2026.

    What is the agentic web?

    The agentic web is internet infrastructure that enables AI agents to find, assess, and act on behalf of users. It does more than answer questions; it completes tasks. This includes browsing product pages, comparing prices, and booking reservations.

    It’s based on new protocols that enable AI systems to interact directly with businesses. And it’s moving fast.

    The infrastructure is already here

    The agentic web requires a new generation of protocols designed for AI systems to interact more with your brand.

    In late 2024, protocols for agent commerce, agent-to-agent communication, agent-tool connectivity, and open agent standards began launching in succession. All backed by companies that rarely collaborate on shared, open infrastructure.

    Vertical timeline of seven agentic web protocols from MCP in November 2024 to UCP in January 2026 with company names and adoption stats

    In March 2026, OpenAI shifted from native checkout to redirecting users to merchant sites — a sign of how fast this is evolving.

    Every protocol on that timeline is a production standard from the companies that run the internet, shipping within months of each other. 

    Google, OpenAI, Microsoft, and Anthropic jointly formed the Agentic AI Foundation (AAIF) to build shared agent infrastructure. Brands, publishers, and platforms are now adapting to what they’ve already built.

    What does this mean for marketers? Three shifts feel the most concrete and immediate.

    Shift #1: Your customer is becoming an approver

    In the delegate economy, when an AI agent handles discovery, evaluation, and shortlisting on someone’s behalf, the person often encounters your brand for the first time moments before purchase. That compresses awareness and consideration — staples in the marketing funnel — into seconds.

    Side by side comparison of traditional marketing funnel with all human stages versus agent mediated funnel where AI handles discovery through shortlisting

    Crystal Carter, Head of AI Search & SEO Communications at Wix and one of the sharpest voices on agentic search, describes this as a validation layer — a moment that looks different from traditional consideration.

    Consideration is weighing your options. Validation is confirming a decision that’s already been made on your behalf. As she put it on Search Party: “Brands haven’t experienced this level of burden of proof before.”

    Youtube video thumbnail

    Here’s what the delegate economy looks like in practice: 

    Someone tells Gemini, ChatGPT, or Perplexity to find a project management tool for a 12-person creative team. Budget under $15 per seat. Needs time tracking and client-facing dashboards. 

    The agent evaluates six platforms, reads third-party reviews filtering for creative team use cases, checks pricing pages, compares feature sets, and starts a free trial on the one that fits.

    The person gets a summary. They scan the feature list. Maybe click through to the homepage. Often, they just approve.

    That person became aware of the tool at the moment the agent presented it. The agent handled everything before the validation step — and it didn’t just recommend. It signed up.

    This is the behavioral shift underneath the delegate economy. Your customer used to be a researcher who spent hours comparing options. They’re becoming a quality assurance layer. 

    Someone who reviews the agent’s work and either approves it or sends it back with feedback. 

    And here’s the part that should keep marketers up at night: When the agent gets it right a few times in a row, the review gets lighter. Trust builds. The agent earns autonomy through positive outcomes, just like a human assistant would.

    This means top-of-funnel and conversion are converging. 

    Brand awareness and “close the deal” need to happen in the same place because agents are collapsing the distance between them.

    Shift #2: Your website was built for humans. Agents need more.

    The protocols reshaping the web are creating specific ways for AI agents to interact with your business. Your website is where that interaction happens.

    Proposed standards like WebMCP would let websites declare their capabilities to agents in a structured, machine-readable way. What you offer, what actions are available, how to take them. The agent interacts with your business programmatically rather than scraping pages and guessing.

    Important reading: WebMCP: What It Is, Why It Matters, and What to Do Now

    The broader picture: New commerce protocols (like Google’s UCP and OpenAI’s ACP) are creating standardized ways for agents to access product information, discover what your site supports, and verify your claims against independent sources. The technical details differ across protocols, but they share a common goal — giving agents structured paths to interact with your business instead of scraping and guessing.

    Six card grid showing what AI agents evaluate on websites including pricing clarity, feature specifics, reviews, corroboration, structured data, and audience

    AI systems take the path of least friction. 

    When two brands offer similar products, the one whose site lets agents understand, verify, and act on what’s available has an advantage. 

    The brand whose site requires an agent to scrape, infer, and guess is more likely to get passed over. Not because the product is worse. But because the agent couldn’t do its job there as easily.

    The specifics will keep evolving. But the principle is stable: Make it easy for agents to understand what you offer, verify it, and take action on it.

    Shift #3: Declare who you’re for or get matched to no one

    Personalization is how agents decide whether you belong in front of a specific person at all.

    When an agent acts on someone’s behalf, it’s filtering through that specific person’s needs. Their budget, their industry, their use case, their constraints. Not running a generic search. Running a match.

    Brands that explicitly declare who they serve get matched. Brands that describe themselves in broad terms become harder for agents to connect to anyone in particular.

    Salesforce is one of the clearest B2B examples. Dedicated pages, content, and product configurations for each target industry — automotive, healthcare, financial services, and retail.

    Salesforce webpage showing industry selection icons and headline about becoming a leading customer company

    When an agent evaluates “CRM for automotive dealerships,” Salesforce’s automotive page speaks that language explicitly. Industry-specific features, use cases for that buyer, and case studies from automotive companies. The agent doesn’t infer relevance. It’s declared.

    Salesforce Automotive page promoting Agentforce 360 with dashboard UI and automotive brand logos

    That specificity shows up in the data. Salesforce’s AI Visibility Score: 82 out of 100. Frequently mentioned and often preferred by AI systems.

    AI visibility dashboard showing mentions, citations, cited pages, and trends for salesforce.com

    Patagonia is the standout DTC example. And like Salesforce, they’re consistently atop Semrush’s AI Visibility Index.

    Semrush AI search leaderboard ranking brands by share of voice, with Google, Samsung, and Apple at the top

    Patagonia’s review forms prompt customers to note height and primary activity. Every review becomes richer data for agents evaluating fit. “Durable hiking pants for a 5’10” person who mostly does scrambling” — Patagonia’s reviews contain exactly the structured detail an agent needs to match confidently.

    Product review snippet showing user height, activity, rating, and detailed feedback on biking pants

    This goes beyond product pages. 

    Declaring what you do, who you serve, and what makes your offering right for a specific person has always been good marketing. But in the delegate economy, that specificity carries new weight. If you’ve already been doing this well — across your site, reviews, and content — you have a head start. Agents reward the clarity that good marketers have been building for years.

    When an agent evaluates five options and needs to match one to a user with specific preferences, the brand with the clearest declaration of fit wins.

    What this means for your brand visibility strategy

    How do you track brand visibility when the visitor is an agent? How do you know if an agent recommended your brand — or skipped it — inside a conversation you’ll never see?

    We’re still early. But the direction is clear: The companies that build the internet are standardizing how agents interact with businesses. 

    Your customer is becoming an approver.

    The question is whether your brand is ready for the AI agent to do the work on their behalf.

    To see how AI systems currently perceive your brand, try Semrush’s AI Visibility Toolkit.

    agents brands cut decide
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