Entity Optimisation for AI Agents: Complete Guide — an AXD Institute resource on agentic experience design, agentic commerce, trust architecture, and human agent interaction. Founded by Tony Wood..
| Dimension | Traditional UX | Agentic Experience Design (AXD) |
|---|---|---|
| Primary material | Attention and affordance | Trust and delegation |
| User state | Present, navigating | Absent, delegating |
| Design output | Screens and interfaces | Outcomes and constraints |
| Temporal model | Session-based | Relationship-based |
| Success metric | Task completion | Trust calibration |
Entity optimisation for AI agents is the practice of building, structuring, and maintaining the digital entity representations that AI systems use to identify, evaluate, and cite your brand. It involves implementing comprehensive structured data (Organisation, Person, and Concept schema), maintaining cross-platform naming consistency, and creating content that reinforces your entity model across all AI systems.
AI systems build internal knowledge graphs from entity signals across the web. If they cannot construct a coherent entity model of your brand - due to inconsistent naming, incomplete structured data, or fragmented cross-platform presence - they cannot confidently cite, recommend, or transact with you. Entity optimisation is the foundation of all AI visibility strategies.
Optimise your brand entity through four strategies: (1) implement comprehensive Organisation and Person schema on every page with consistent properties, (2) maintain identical naming and description across all platforms (LinkedIn, Twitter, Crunchbase, directories), (3) create or update Wikipedia/Wikidata entries for maximum third-party authority, and (4) use canonical terminology consistently across all content to build concept entity associations.
Entity optimisation requires layered JSON-LD structured data: Organisation schema (name, url, foundingDate, founder, description, knowsAbout, sameAs), Person schema (name, jobTitle, worksFor, sameAs, knowsAbout), Article schema (author, datePublished, publisher), BreadcrumbList schema, and FAQPage schema. The knowsAbout and sameAs properties are particularly important for entity authority.
Measure entity optimisation through entity accuracy audits: query your brand name in ChatGPT, Claude, Perplexity, and Google AI Overviews and evaluate whether the founding date, description, key people, and expertise areas are accurately represented. Track accuracy scores monthly. Also monitor your Google Knowledge Panel for completeness and accuracy, as it reflects Google's entity understanding.
Establish the business case for entity optimisation. AI systems that cannot build a coherent entity model of your brand will not cite, recommend, or transact with you. In Use knowsAbout properties strategically. The knowsAbout property in Organisation and Person schema tells AI systems what topics you are authoritative about. Be specific and comprehensive: not just 'artificial intelligence' but ' Use canonical terminology consistently across all content. If you define a concept (e.g., '