Agents need a legible interface model
A human can often infer that an unlabeled icon opens a menu because of visual convention and surrounding context. An automated agent has to map the interface into controls and possible actions. Native elements such as button, input, label, nav, main, form, and heading levels provide a stronger model than anonymous div elements with click handlers.
OpenAI's publisher and developer guidance specifically recommends accessibility practices and descriptive ARIA roles, labels, and states for interactive elements used by ChatGPT agent experiences. That guidance aligns with established accessibility engineering rather than introducing a parallel AI-only standard.
Forms are a high-value test surface
Forms combine labels, validation, state, focus management, and submission outcomes. If the relationship between a label and input is unclear, if validation appears only as color, or if a modal traps focus incorrectly, both assistive technology and automated agents can struggle. Stable field names, explicit labels, button text that describes the action, and programmatically available error messages improve the interaction model.
Sites should also avoid surprising state transitions. A button labeled 'Continue' that silently purchases a product is poor design for everyone. Clear confirmation steps and visible consequences make automated execution safer and easier to audit.
Content discoverability still matters
Agent readiness is not only about clicking. Public documentation should be reachable through ordinary links, have stable canonical URLs, return meaningful server responses, and avoid forcing essential information behind unnecessary client-side rendering. Structured data can reinforce page meaning, but it should agree with visible content rather than act as a hidden substitute for it.
This is also where accessibility and search quality overlap. Clear headings, descriptive link text, concise page titles, and coherent information architecture help screen readers, search engines, and machine readers identify the purpose and boundaries of a page.
Test the task, not the buzzword
Instead of asking whether a site is 'AI optimized,' define tasks: find the pricing page, understand plan differences, submit a contact form, retrieve documentation, or complete a purchase with confirmation. Test those tasks with keyboard navigation, accessibility tooling, ordinary browsers, and—where appropriate—agent systems.
The result is a site that is better for people first and more reliable for automated interaction as a consequence. That is a much more durable engineering target than chasing an undocumented ranking factor.