Websites have been built around two primary audiences: people looking for information, products, or services, and search engines crawling their content to determine where it appears in search results.
Now a third audience has arrived: AI agents.
Rather than visiting multiple websites to research products, compare providers or complete tasks themselves, people can increasingly delegate parts of these journeys to agents acting on their behalf.
This creates a new challenge for businesses. Can AI agents reliably access and act on your website? Because if they experience any friction, they’ll bounce right to a competitor.
It’s a structural shift in brand visibility, marking an even greater need for collaboration between your SEO, content, affiliate, and influencer teams. Connecting the dots and acting requires the right martech stack, and Enterprise AIO's new analyses for LinkedIn and YouTube empower just that.
How customer journeys are moving towards agentic
If the automated future of the internet feels distant, it shouldn’t. Cloudflare Radar states that the overall traffic is currently 65% bots. This transition is well underway.
For a practical example of what this change looks like, consider a typical software purchase journey.
A prospective buyer might search for vendors, visit a handful of websites, download documentation, compare product capabilities, and request a demo.
An agent scales this process significantly. Instead of a handful of websites, it can comfortably visit hundreds, summarizing gestures and pricing as a comparison, and potentially arranging demos for the software it deems most suitable.
The agent becomes an intermediary between that customer and the businesses competing for their attention. And this AI intermediary is geared towards efficiency. If it experiences friction on your website, it’s likely to immediately move on.
Customers are already using AI to discover and evaluate options, while independent, end-to-end agentic purchasing remains at an earlier stage. Cloudflare puts the proportion of this AI traffic taking on-page actions at just over 5%, and growing.
The commercial implications of this growth look significant. McKinsey estimates that AI agents could orchestrate between $3 trillion and $5 trillion in global consumer commerce by 2030.
That means the time for businesses to take action is now.
Why an inaccessible website is a business risk
Many enterprise websites have been built and optimized over years, sometimes decades. They're designed around established customer journeys and carry many layers of technical infrastructure.
But a website that works perfectly for a person isn't necessarily one that works reliably for an AI agent.
For example, an agent might attempt to retrieve product information only to find that it’s unavailable without JavaScript execution. Another might struggle to identify important content within complex page structures, or encounter interactive elements it can’t use.
These barriers affect multiple stages of an agentic journey:
- Discovery: If agents can’t access important pages or information, your business may be excluded from relevant research or comparisons. Potentially misusing consideration completely.
- Evaluation: If content is poorly structured, incomplete, or difficult to extract, there’s a risk that agents will overlook or misrepresent important details—or they might simply bounce to another site.
- Action: If critical website functionality can’t be navigated, agents may struggle to complete tasks like submitting a form or making a purchase, again risking agents bouncing.
These issues introduce friction that makes it much more likely for an agent to move elsewhere. For enterprises managing thousands of pages across domains, languages and markets, these risks become difficult to identify, let alone to solve.
Is your website ready for AI agents? Six checks to make
1. Check whether important content relies on JavaScript
The issue: Some websites depend heavily on client-side JavaScript to render their content. AI crawlers that don't execute JavaScript may receive an incomplete page or miss important information entirely.
What to do: Inspect your initial HTML response or test key pages with JavaScript disabled. If important content disappears, consider server-side rendering, static rendering or other approaches that make essential information available without client-side execution.
2. Review which AI crawlers can access your website
The issue: Robots directives and security configurations can prevent AI search crawlers from retrieving website content. Importantly, crawlers used for AI-powered search are not always the same as those used for model training.
What to do: Review your `robots.txt` configuration and CDN or web application firewall rules. Check how permissions apply to relevant crawlers, such as OpenAI's `OAI-SearchBot` and Anthropic's `Claude-SearchBot`. Ensure legitimate access is permitted where it aligns with your business and security policies.
3. Use clear, semantic HTML structures
The issue: Websites that rely heavily on generic HTML containers or lack meaningful page structure can make it more difficult for some automated systems to distinguish primary content from navigation and supporting elements.
What to do: Use descriptive heading hierarchies and appropriate semantic elements, such as `main`, `article` and `nav`. Organize content logically, with important information clearly identified and accessible in the underlying page structure.
4. Make interactive elements accessible
The issue: AI agents may need to interact with buttons, forms, menus or other website elements. Missing labels, inaccessible custom controls and poorly structured forms can make those interactions less reliable.
What to do: Test important journeys using keyboard navigation and accessibility inspection tools. Ensure interactive elements have meaningful labels, appropriate roles and clearly defined states. Wherever practical, prioritize native HTML controls.
5. Identify important content behind authentication or unnecessary interactions
The issue: Product details, documentation or other important information may be inaccessible to agents that lack an authenticated session or cannot perform the interactions needed to reveal it.
What to do: Test what an unauthenticated visitor or crawler can access. Check that information intended for public discovery available without unnecessary login requirements or interactions, while maintaining appropriate safeguards for private content and secure workflows.
6. Validate your structured data
The issue: Missing, incomplete or inaccurate structured data can make it harder for machines to identify explicit information about products, organizations and other entities. However, structured data is not a prerequisite for AI systems to understand website content.
What to do: Review relevant Schema.org markup and use validation tools to identify errors. Ensure structured data is accurate, consistent with visible page content and maintained as information changes.
These checks form a starting point. They won't guarantee that AI systems will cite, recommend, or perform an action. But they provide a practical way to identify key technical limitations that could undermine accessibility.
STEP BY STEP DEMO
Why agent accessibility is becoming a ongoing business requirement
Another challenge is that the technical requirements for agentic interactions are still developing.
Different AI systems consume and interact with websites in different ways. Some rely on established crawling methods, others retrieve content in response to user requests, and increasingly capable agents can navigate websites through browser interfaces.
For enterprises, keeping up requires more than periodically reviewing a checklist.
A single website might contain hundreds of different templates, content owners, development teams and publishing workflows. Changes that improve one section of a website may introduce accessibility issues elsewhere.
Manually identifying and resolving these issues, particularly across multiple websites and markets, quickly becomes impossible to manage.
Agentic accessibility therefore needs to become part of continuous website health monitoring, alongside technical SEO, site performance and established accessibility practices.
Move from manual checks to enterprise-wide readiness
For businesses preparing their websites for agentic discovery and interactions, the first step is understanding where technical barriers exist.
That's where Enterprise Site Intelligence’s Agentic Accessibility Audits come in.
Building on existing crawling and website health audits, the feature enables sitewide assessment against and initial 28 different barriers to AI agent accessibility through an integrated workflow.
Teams gain a dedicated dashboard to identify supported issue types, prioritize technical problems and get guidance for solving through code snippet previews and implementation recommendations.
These make for next-generation issue reports that bridge the gap between identification and resolution, giving technical SEO and development teams a clearer path to action.
By bringing agentic accessibility into existing website health workflows, Site Intelligence helps businesses establish a more systematic approach to evaluating and improving their technical readiness at scale.
As the standards underpinning agentic interactions continue to develop, having that foundation becomes increasingly valuable.
The next phase of digital visibility starts with your infrastructure
AI agents won't replace every website visit or customer interaction. Human experiences, search engines, and AI-assisted journeys will continue to coexist, each serving different needs and audiences.
But the technical foundations of digital visibility only become more important as more decisions and tasks are delegated to agents.
The organizations best positioned to capitalize on this new agentic audience are those ensuring their digital infrastructure can support the changing ways customers discover, evaluate, and engage with their business.
