How to prepare your digital platforms for AI agents
For decades, businesses have built their digital platforms for one kind of visitor: a person. Someone who notices your hero image, engages with your product pages, and clicks their way to checkout. But a new kind of visitor has arrived, and it plays by different rules.
AI agents act on a customer’s behalf, creating a new layer between user intent and the businesses competing to meet it. Unlike human visitors, however, agents interact with digital experiences in fundamentally different ways, with new requirements for what it means for a website to be accessible, understandable, and easy to act on.
The scale of this shift is hard to ignore. Agentic traffic grew by a whopping 7,851% in 2025, and agents could mediate three to five trillion dollars in global consumer commerce by 2030. For businesses, this changes what it takes to compete online, as digital platforms must now serve both agents and customers.
growth in AI agent traffic in 20252
projected global consumer commerce mediated by AI agents by 20301
The is an emerging phase of the internet where AI agents act on behalf of users to research, make decisions, and execute tasks across websites and digital services.
Instead of humans manually clicking website links, jumping between pages, and filling out forms, intelligent software agents understand a goal, coordinate with other services, and handle the workflow, from start to finish.
Google’s in the U.S. is an example of this in action. Its AI agent researches, selects, and completes a traveler’s reservation from start to finish—rather than surfacing listings for the user to review or handing them off to the hotel’s website to book.
agent.read("/hotels") ✓
compare(price, policy)
book(room=“quiet”) ✓
Skim the essentials in a few minutes, or go deep with tool tips, protocols and implementation detail. Switch anytime from the top bar—you’ll stay where you are.
Getting ready for the agentic web starts with understanding where your digital experience is today and where new opportunities are emerging. Here are six steps you can start taking today, no matter where you are in your AI journey.
The shift to the agentic web is creating new interactions that traditional analytics weren’t designed to capture. While direct visibility into agent behavior remains limited, adjacent AI signals are already measurable—like LLM-referred human traffic and .
Rather than waiting for a complete picture of agent activity, assess what you can see today, and where the gaps remain. Establishing that baseline now gives you something to build on as better agentic measurement tools become available.
Use Contentsquare’s Acquisition Analysis to segment AI-referred traffic at the LLM level. Instead of seeing a vague ‘AI referral,’ teams can pinpoint whether visitors came from ChatGPT, Gemini, or Claude, and compare performance across each source.
Before an agent can compare or recommend your business, it needs a clear understanding of what you offer. Yet top retailers’ product detail pages score just 63.5% for AI visibility2183, leaving more than a third of their content unreadable to AI systems.
As customers delegate more tasks to agents, this gap matters more than ever. If agents can’t easily access or interpret critical information, they may overlook or misinterpret your offer before a customer ever enters the picture.
See what decision-critical information AI bots can actually access with Contentsquare’s Bot View in CS Live. Toggle between the human-facing page and the raw HTML to spot content that disappears when JavaScript isn’t executed.
When agents visit your site, most still complete tasks the same way your customers do—clicking buttons, filling out forms, and moving through check-out flows. But experiences that feel intuitive and engaging to people can be surprisingly difficult for agents to navigate.
Teams therefore need to assess whether agents can successfully complete key tasks through the existing user interface—or if there’s hidden friction making the agent journey unnecessarily fragile or complicated.
Not sure where to begin? If you’re already using Contentsquare, tools like Journeys help identify which human customer paths deliver the greatest business value—a practical way to decide where agent-readiness strategies should start.
Example data from the Journeys view shown in the playbook.
As AI agents take on more responsibilities, teams need to decide how much authority they are willing to hand over. An agent that can search or retrieve information creates a very different level of risk from one that can change an account or make a purchase.
are creating more standardized ways for agents to access business capabilities directly, rather than relying solely on the human-facing interface. But adopting a protocol is only part of the equation. Businesses also need rules for which agents they trust and where human approval is required.
Agent protocols solve different parts of the agentic experience, from connecting AI to business systems to enabling purchases. The standards are still developing, but these four are worth understanding now.
Connects AI applications to external tools—like CRMs, databases, and business software—so they can retrieve information and take actions within those systems.
Lets websites expose structured actions to browser-based agents, like booking, signing up, or adding an item to a cart.
Lets customers discover and buy products inside AI conversations like ChatGPT, while the business stays the merchant of record.
Standardizes the full shopping journey—search, cart, checkout, and post-purchase—between agents and retailers.
Contentsquare’s MCP server gives AI tools like Claude, ChatGPT, Dust, and Microsoft Copilot a standardized way to connect to Contentsquare data, so teams can query experience data and surface insights in natural language. Explore more MCP applications and use cases in the MCP Guide.
While agentic readiness focuses on AI agents, human customers are still the ones businesses ultimately serve. Adapting for agents should therefore complement the user experience—not weaken it.
That means treating agent readiness as an extension of the customer experience, rather than a separate goal146.
Preparing for the agentic web doesn’t fit neatly within one team. Product and engineering may build the underlying capabilities, but marketing, ecommerce, security, and leadership will all make decisions that shape how agents interact with the business.
Without careful planning, agent initiatives can become disconnected from team priorities. Digital leaders therefore need a shared understanding of where agent readiness stands, where problems are emerging, and which improvements matter most.
Businesses that treated mobile as a side project in the early 2010s spent the next decade catching up to competitors who quickly reorganized around it. The agentic web is following a similar curve, with what looks optional today becoming table stakes faster than roadmaps anticipate.
The advantage won’t go to the businesses with the single best initiative, but to the ones that make readiness an integral part of how teams across the business work.
A two-minute self-check on the six steps. Answers explain themselves—wrong ones too.
You don’t need a fully developed strategy to begin preparing for the agentic web. Focus on a few practical actions that identify where agents could interact with your business, build familiarity, and help you decide what deserves investment next.
Choose one low-risk task you’d normally complete yourself and delegate it to an AI agent. One easy way to do this today is through an AI browser like Perplexity’s Comet, which has a built-in agent. Ask it to compare products across different sites, weigh prices and reviews, and—if authorized—add the best option to your cart.
Pay attention to where the agent works independently, where it asks for clarification or approval, and where it struggles. This gives you a firsthand view of how agent-led journeys work in practice and how they differ from simply asking AI for an answer.
Choose one high-value page—like a product, pricing, or service page—and check whether your most important information is available in a machine-readable format. Focus on basics like structured data, clear product identifiers, and critical details that can be accessed without relying on JavaScript, then apply the necessary updates this month.
Use Contentsquare’s guide on the AI visibility gap to understand common issues that can keep important content out of reach, what to check first, and how to fix it.
Choose one workflow where an agent could realistically interact with your business, then explore how a relevant protocol could support it.
Map what the agent would need to access or do, what the protocol would standardize, and what your team would need to investigate before taking it further. By the end of the month, you should have one concrete use case worth investigating further.
Not sure where to begin? Google’s Developer’s Guide to AI Agent Protocols explains how major standards fit together and the capabilities each is designed to support.
Identify the stakeholders who need to be involved in preparing your business for the agentic web—like product, engineering, ecommerce, marketing, security, and legal. Bring them together for a working session to agree on one or two priorities, how you’ll measure progress, and who will own each next step.
Deloitte’s 2026 survey of senior leaders4. Closing that gap starts with a team that owns the work.
As AI agents become a new layer between customers and businesses, brands need to rethink how their content, journeys, and transactions work when an AI system is acting on the customer’s behalf.
The organizations that stay ahead are the ones taking action now—making critical information easier for agents to understand, exploring the protocols needed to support more reliable agent-led interactions, and rallying their business around an agent-readiness strategy.
See how Contentsquare can help you understand what AI agents are doing across your site and where to improve next.
Contentsquare is the all-in-one AI-powered customer experience intelligence platform designed to be easily used by anyone who cares about digital journeys. With our flexible and scalable platform, you quickly get a deep understanding of your customers’ whole online journey.
Our AI-powered insights provide those ‘aha’ moments you need to deliver the right digital experiences. You get to work faster and smarter, with the confidence to know what to do next to improve.
Leading brands use Contentsquare to grow their business, deliver more customer delight, and move with greater efficiency in a constantly changing world. Our insights are used to optimize the experience on over 1.3 million websites worldwide.
Visit us at contentsquare.com to learn more.
