Click here to watch our full video episode on AI agents and reasoning.
The agent doesn't just jump to an answer. It breaks the request into smaller steps, such as: search for hotels → filter for a pool → compare prices → check availability.
It connects the dots between brand data, APIs, business profiles, and verified sources to decide how to move forward.
3. Action: Executing the task
Next, the agent uses tools — like a hotel search API or booking system — to get real-time results or complete a task. These tools help the agent act on your behalf, whether that's finding options or booking the room directly.
Let's dive into what that might look like in practice.
Real-world examples by industry
Financial services
Getting an insurance quote by having an AI agent autofill forms, compare coverage options, and highlight the best policy based on your needs.
Opening a new checking account with an agent that verifies identity, checks eligibility, and completes the application — all without human intervention.
Healthcare
Scheduling a doctor's appointment by checking provider availability, matching based on insurance, and confirming the time directly in the agent interface.
Refilling a prescription by verifying dosage, confirming pharmacy inventory, and initiating the order — without needing to visit a website or app.
Hospitality
Booking a hotel by matching preferences (like a pool, location, or loyalty program) to verified listings, checking availability, and securing the reservation.
Coordinating travel itineraries by combining flights, hotels, and transportation into a single, seamless plan based on user preferences and previous bookings.
Retail
Ordering a product by scanning multiple retailers, comparing specs and reviews, and completing the purchase from the most trusted source.
Getting back-in-stock alerts or curated recommendations based on past purchases, with the agent automatically adding the item to your cart or wish list.
Behind the scenes, agents rely on structured data and verified sources to help make these decisions. And if your brand's information isn't accurate, structured, and accessible, agents may overlook you entirely.
Explore why your website now needs to serve both humans and AI.
4. Iteration: Learning and adjusting
Here's what sets agents apart from traditional search: they work in loops. If the first search returns no family-friendly hotels, the agent updates the filters and tries again — adapting as it goes until the task is done.
Why AI agents matter for brands
In an AI-first world, agents are the new gatekeepers. That's a big deal for visibility and conversion — because if an agent doesn't "see" or select your brand when someone asks a question or makes a request, your customer never will.
Here's how AI agents are changing the rules:
Search is now selection. AI agents don't show 10 blue links. They choose for the user. If your brand isn't part of that decision, you're invisible.
Data is the difference. Agents trust structured, factual, and verifiable data — not just keywords or clever copy.
Zero-click is the norm. More than ever, customers complete their journey without ever visiting a brand's site. Agents accelerate this trend. Read more about zero-click search here.
But while many brands are experimenting with agents, most strategies fail before they scale. Three problems typically cause failures:
The agents don't coordinate. They automate tasks without aligning on outcomes.
They're built on weak data foundations, and rely on incomplete or inconsistent brand facts. They lack direct distribution.
Updates get stuck in aggregator loops instead of reaching the surfaces AI agents actually cite.
At the same time, AI agents are changing customer expectations, too. They want fast, confident answers — not long forms or confusing menus. That's why agentic AI optimization is an important key to your brand visibility strategy.
How to optimize for AI agents
To stay visible in this AI agent-driven landscape, you need more than visibility. You need orchestration: a strategy that connects data, intelligence, and execution.
Most agent strategies fail because they don't think big enough. To win, your brand needs to lay the foundations for agentic orchestration, which requires focus on:
1. Structure and connect every brand fact
Build an AI-ready data foundation: hours, providers, SKUs, services, reviews — all linked, verified, and organized.
Agents rely on structured data, so this helps them understand, recommend, and act on your brand information with confidence.
Use tools like the Yext Knowledge Graph to organize and connect your brand facts across locations, services, and channels.
2. Be present, and push every update, across every trusted source agents check
Google is no longer the only game in town. AI agents pull information from across the digital ecosystem: maps, directories, niche sites, listings, product feeds, reviews, and more. To have a chance at being one of the brands an agent finds, recommends, and/or transacts with, your information needs to be accurate, verified, and consistent, everywhere.
That means updating your listings, optimizing all of your web pages, and making sure your brand appears across trusted sources. (Psst: 86% of AI citations — i.e., what the LLMs powering agents look at and cite — are brand-managed. Here's what that means.)
The Yext Publisher Network has the largest network of direct integrations, which drives consistency.
3. Build trust through data quality and transparency
Agents want to be sure they're making the best decision for a user — so they prioritize trusted information. If your data is outdated, unclear, or contradicts other sources, they'll skip you. Use fact-based content, accurate metadata, and clear product details to earn agent trust.
4. Add governance and oversight — autonomy only works with accountability
AI agents can execute quickly, but they still need direction. Without built-in guardrails, agents can create inconsistent experiences, publish incomplete data, or make decisions out of sync with brand policy.
That's why human oversight matters. Build in approval workflows, compliance checks, and monitoring tools that give you visibility and control — without slowing agents down.
5. See beyond your brand data — context is how agents make smarter decisions
Agents don't just need brand facts — they need perspective. Without competitive context, they may prioritize tasks that don't actually move the needle (like boosting review counts in locations where you're already winning).
To optimize performance, brands need to benchmark against competitors, market conditions, and location-level dynamics. That way, agents can prioritize the activities that drive real outcomes — not just more tasks.
Yext Scout does this by scanning billions of signals, comparing your performance to the market, and surfacing recommendations that matter.
How Yext helps
Yext helps brands get AI-ready by making sure their data is:
Structured for AI discovery
Synced across every source agents rely on
Verified, factual, and easy to maintain
Our platform helps you stay visible — even when agents are the ones making the decision.
In the future, AI agents won't just be part of the customer journey — they're likely to be the customer journey. That means brands will need to rethink how they show up, how they earn trust, and how they get selected.
In the past, being seen was enough. In the agent era, being chosen (and trusted) by a machine is the goal.
That means data isn't a backend asset. It's a brand performance driver.
And the brands that structure their truth, distribute it everywhere, and coordinate their agents? They won't just keep up. They'll win.
See how Yext Scout helps you understand what AI agents are seeing.
