The internet is experiencing a substantial shift in how users interact with online platforms.

As well as growing adoption in AI platforms like ChatGPT, and confidence in Google’s AI Overviews and AI Mode results, we’re also beginning to experience a more delegative form of online interaction.

We are transitioning from a web where humans browse pages and click buttons to a system where automated software agents perform these tasks.

With technology companies launching autonomous tools, artificial intelligence agents are doing more than summarising text, they are now operating web browsers to complete multi-step transactions on behalf of users, such as booking travel, purchasing products, or comparing different services.

This development raises an important question of whether business websites are ready for automated systems. If a website is not prepared, the business may lose visibility to automated buyers.

Human and machine interfaces

To a human user, a website is a visual presentation with specific layouts, fonts, and colours. To an artificial intelligence agent, a website is a functional interface. Being ready for agents means that the code of a website is structured so that an automated tool can understand the context, navigate the layout, and complete actions without human assistance.

The search company Google recently introduced tests for automated browsing into its development tools.

This tool does not evaluate websites for standard search ranking, but instead tests functional infrastructure. It checks for a machine readable summary file in the root directory to explain what the website does. It also checks for code elements that indicate a form can be submitted directly by an agent.

It measures layout stability to ensure elements do not shift during loading, which can cause an agent to select the wrong button.

If a site does not meet these standards, an agent will fail to navigate it and will instead select a competitor website that is properly configured.

How the accessibility tree enables machine navigation

While building a compatible website requires technical adjustments, the fundamental solution uses existing technology, specifically the accessibility tree. Automated agents navigate websites using raw code, visual screenshots, and the accessibility tree. Because processing raw code is complex and visual reasoning is slow, agents use the accessibility tree as their primary model.

When a browser loads a website, it translates the standard code and removes visual details like styles, colours, and layout configurations. This leaves a simplified structural map designed for assistive technologies like screen readers. When an artificial intelligence agent reads a webpage, it uses this exact map.

An agent uses this structure systematically to complete tasks. If an agent needs to purchase an item, it follows the path defined by the accessibility tree.

Method Positive aspects Negative aspects
Semantic HTML It is naturally accessible, it requires less code, and it is universally supported by browsers and agents. It cannot cover complex custom components, and it is limited to standard default elements.
ARIA attributes It allows developers to make custom elements accessible, and it provides rich descriptions for dynamic states. It is easy to implement incorrectly, and it can conflict with native browser behaviours if used poorly.
Visually hidden text It allows custom descriptions without affecting the visual layout for sighted human users. It can clutter the accessibility tree, and it requires careful style management.

The agent identifies interactive elements through their assigned roles. If a developer builds a button using generic code and styles it to look like a button, a human user can see it. The element will not have a functional role in the accessibility tree, and the agent will ignore it. Using correct semantic code tells the agent that the element is clickable.

The agent then requires clear names for elements.

An artificial intelligence agent cannot interpret a simple visual icon. If a button only contains an image, the agent cannot identify its purpose. Using text labels in the code provides a clear name in the accessibility tree that the agent can read.

Then agent the monitors changes in state. When an agent interacts with a menu, it checks the tree for dynamic attributes to confirm if the menu opened and what options are now visible.

This approach benefits businesses in two distinct ways, as the primary advantage is that accessibility features designed for human users also make the website accessible to artificial intelligence. Businesses do not need to rebuild their websites or purchase expensive external software.

By focusing on standard accessibility guidelines, correcting broken form labels, using semantic tags, and maintaining a clear accessibility tree, businesses achieve two goals.

They create an inclusive website for visually impaired human users, and second, they ensure their digital services are accessible to the automated agents that are expected to handle a significant portion of future online transactions.

The immediate agentic impact

Travel and ecommerce businesses will face the most immediate impact from these developments.

It is unlikely that consumers will immediately grant full autonomy to machines for final purchases, as people still prefer to maintain control over financial transactions.

Users will regularly delegate preparatory tasks such as researching hotel options, tracking product prices over time, and comparing service features.

Because these initial automated searches dictate which brands are presented to the final buyer, maintaining agentic readiness remains essential for businesses in these sectors to avoid being excluded from the selection process.