James Dooley, an AI search specialist, argues that Entity SEO for AI Search depends on establishing Knowledge Graph Middle IDs (KGM IDs) through high-weight sources like Google Books to ensure visibility in generative engine optimization (GEO). Dooley’s expertise stems from his work identifying the connection between identity confidence and AI retrieval logic. Entity SEO for AI Search suits business owners seeking to build a digital moat, while PPC specialists should focus on paid advertising channels instead.
Who should act on Entity SEO for AI Search and who should skip it
Readers who should act on Entity SEO for AI Search
- In-house SEO Managers should prioritize KGM IDs and entity clarity over simple keyword volume to ensure brand visibility as Google shifts toward AI-generated answers.
- Agency Owners should use complex entity connections, such as awards and specific locations, to build unreplicable authority that competitors cannot easily mimic.
- Business Founders should use the publication pipeline of writing a book to establish a personal knowledge panel that strengthens the business’s own KGM ID.
- Content Strategists should structure content using semantic triples and third-person descriptions to make information easier for LLMs to chunk and retrieve.
Readers who should skip Entity SEO for AI Search
- PPC/Paid Ads Specialists should skip this and look at Google Ads documentation or PPC-specific tutorials instead.
- General Social Media Marketers should skip this and focus on social media growth and engagement guides.
What to do next about Entity SEO for AI Search
- Publish a book on Amazon and submit it to Google Books to trigger a KGM ID within a 3-4 week wait time.
- Create a specific /about/[name] URL slug to define the personal entity home page.
- Rewrite the about page bio in the third person to facilitate semantic triple extraction.
- Claim and optimize an IMDb Pro profile for $96 per year to connect media and event entities.
- Link 5+ specific entities, including a date, location, and specific people, to an award or event to build entity juice.
The Shift to Entity-Based Algorithms in AI Search
Entity SEO for AI Search relies on a move toward an entity-based database where Google identifies ‘who’ an entity is rather than just ‘what’ a page says. This shift makes the Knowledge Graph Middle ID (KGM ID)—a unique identifier in Google’s Knowledge Graph database—the foundational requirement for all AI search visibility. Without a KGM ID for a founder or a website, a brand may struggle to appear in AI overviews as the system moves toward reasoning-based results.
What is a KGM ID?
A KGM ID (Knowledge Graph Middle ID) is a unique identifier that Google uses to group all information related to a specific entity, such as a person, place, or thing. It allows the Knowledge Graph to connect disparate data points—like a social profile, a book, and a business—into a single, authoritative identity. Establishing this ID is the primary way to build confidence in the eyes of an AI search engine.
Google determines the visibility of an entity based on a Confidence Score, which measures how certain the system is that a set of facts belongs to a specific entity. If the Confidence Score is low, the system may fail to populate a Knowledge Panel or include the entity in a generative response. The focus shifts from high-volume keywords to the clarity of these connections, a concept Dooley terms ‘entity juice.’
Establishing a Personal Knowledge Panel
Establishing a personal knowledge panel is often the most effective first step because a founder’s identity provides the ‘juice’ that strengthens the business’s own KGM ID. Dooley recommends a specific publication pipeline to trigger an identity: an individual should write a book and publish it on Amazon. This creates an Amazon profile to define the person’s attributes, which can then be submitted to Google Books.
Google Books serves as the number one weighted source for establishing an entity’s identity because it is a direct property of the Google ecosystem. Once the submission is made, it typically takes about 3-4 weeks for the KGM ID to be generated. Following this, the user should wrap the Google Books URL, the Amazon URL, and the Goodreads URL on a dedicated entity home page to centralize the data.
Technical implementation for entity SEO requires a dedicated /about/name entity home page
Technical implementation for entity SEO requires a dedicated entity home page, often using a specific slug like /about/name. This page acts as a hub where the user wraps all high-weight URLs, including Google Books, the Play Store, and Goodreads, to improve the Confidence Score. By centralizing these links, the site provides the Knowledge Graph with multiple pathways to verify the same entity.
Schema markup functions as the connective tissue for these nodes, and it must nest back to the entity home description to connect edges in the knowledge graph. Proper schema allows the system to see that a specific person is the same person mentioned in a book or on a social profile. This structure reduces the friction for the search engine to map the relationship between different digital footprints.
Optimizing for Semantic Triples
Optimizing for semantic triples involves structuring information so that an AI can easily identify a subject, a predicate, and an object. Dooley argues that it is always better to write about a person in the third person because it is the cheapest way for the system to extract and chunk information. When a sentence says ‘James Dooley is a UK entrepreneur,’ the system does not have to resolve what ‘I’ refers to, which lowers the cost of information retrieval.
What are Semantic Triples?
Semantic triples are a way of connecting entities using a subject-predicate-object structure, such as ‘Subject-Verb-Object’ or ‘Entity-Attribute-Value.’ They are the basic building blocks of the Knowledge Graph, allowing the system to understand relationships between objects. Using these triples ensures that an AI can quickly verify facts like a person’s birthdate or professional titles without complex linguistic processing.
Building ‘Entity Juice’ Through Connections
Building ‘entity juice’ involves creating high-confidence connections between different entities to increase the clarity of a brand’s identity. Using awards is a powerful strategy; for example, if an individual wins an award, the documentation should include a specific date, a specific location, and the names of the people involved. These specific details create a dense web of connections that the Knowledge Graph can use to verify the entity’s status.
Think of entity juice as a clear map for an AI agent, where every landmark is a confirmed fact. When a brand links its location to a Google Business Profile or an award to a specific event, it builds a digital moat. This moat makes it harder for low-quality content farms to compete because they lack the verifiable, real-world connections that provide the necessary confidence for AI search.
Weighting of high-weight sources for KGM ID generation includes IMDb Pro for $96
Leveraging high-weight sources is the most efficient way to boost a KGM ID, with Google Books serving as the number one source. YouTube follows as the number two source for podcasting and video content, while Wikipedia remains a top-tier source for broad consensus. Because these platforms are owned by Google or have massive authority, their data carries more weight in the Knowledge Graph calculation.
IMDb Pro offers a unique opportunity for media-based entities, as it is a high-authority profile that can be claimed for a fee of $96 per year. An IMDb Pro profile costs $96 per year, which calculates to $8 per month, providing a high-authority profile for $8 monthly. By filling out the bio and linking to other connections, a user can rank alongside major actors and influencers in the eyes of the Knowledge Graph.
| Source Platform | Rank | Primary Use Case | Ownership |
|---|---|---|---|
| Google Books | 1 | Author/Entity Identity | |
| YouTube | 2 | Video/Podcast Content | |
| Wikipedia | 3 | Broad Consensus | Independent |
Decision Engine Optimization (DEO) vs. Discovery
Decision Engine Optimization (DEO) represents the shift from being ‘found’ to being the recommended choice in AI-led decision-making. While traditional SEO focuses on discovery, DEO focuses on the reasoning process where an AI compares multiple options and selects the best one. This is the difference between appearing in a list and being the primary recommendation given to the user.
AI trust is a growing factor, as public trust in AI recommendations often exceeds trust in standard search results. Dooley notes that AI leads can convert at 26%, which is three times higher than word-of-mouth conversions. This high conversion rate suggests that being the ‘chosen’ entity in a decision engine provides a significant competitive advantage over simply ranking for a keyword.
Why do most brands fail to appear in AI Overviews? They lack the confidence score provided by verified external entities. To win in a decision engine, a brand must provide the AI with the facts it needs to justify a recommendation, such as awards, specific locations, and high-weight third-party profiles.
The Strategy of AI Clones and Real Content
The strategy for creating digital clones, such as using HeyGen or ElevenLabs, involves a significant trade-off in effort versus authenticity. Dooley suggests that creating a perfect digital twin is often harder than simply filming one or two real videos to define an entity. The time required to get lip-sync and phonetics perfect for an avatar can be extensive, often taking days of recording to achieve a natural result.
A digital clone can be a powerful tool for scaling content, but the primary goal should be establishing the initial entity. It is often more efficient to produce a few high-quality real videos to establish the identity before moving toward a virtual entrepreneur model. Once the entity is established, a digital twin can then be used to maintain and scale the presence in the Knowledge Graph.
How to Trigger a KGM ID via the Publication Pipeline
- Write a book for the business owner or CEO to establish a primary personal entity.
- Publish the book on Amazon to generate a formal profile.
- Create and optimize a Goodreads profile to link the book to a social entity.
- Submit the book to Google Books to trigger the KGM ID.
- Wait 3-4 weeks for the KGM ID to be generated and appear in the database.
Google has not announced Knowledge Graph API confidence score calculation methods
- Google has not announced a specific confidence threshold required to trigger a knowledge panel.
- Google has not specified the exact calculation for the Knowledge Graph API confidence score.
How a Plumbing Specialist Gains AI Visibility
Suppose Sarah owns a plumbing company and wants to be the go-to expert in her city for AI searches. She follows the publication pipeline by writing a book on ‘Modern Plumbing’ and publishing it on Amazon and Google Books to trigger a KGM ID. She then creates a dedicated /about/sarah page with a third-person bio and links her specific local awards, including the dates and locations of the ceremonies. Because she has established a high-confidence connection between her identity, her expertise, and her location, Google gains enough confidence to pop her Knowledge Panel. If Sarah had only focused on keywords without the KGM ID and book links, she would likely be lost in ‘query fanouts’ where the AI selects competitors with stronger entity connections.
Frequently Asked Questions
Why should I use the third person on my about page?
The third person is used to reduce the cost of information retrieval for Google’s Knowledge Graph by allowing the system to easily extract and chunk semantic triples. By naming the subject directly, the system does not have to resolve what ‘I’ refers to, making it easier to map the entity’s attributes.
How long does it take to get a KGM ID?
It typically takes about three or four weeks for a KGM ID to appear after the book is submitted to Google Books. This timing is dependent on the processing speed of the Google Books database.
What is the best way to create an entity connection?
The most effective way to create an entity connection is by using awards that include a specific date, location, and the names of the people involved. These specific data points provide the high-confidence links that the Knowledge Graph requires to connect nodes.
What happens if I use AI avatars for my content?
AI avatars are high-effort to get right because achieving perfect lip-sync and phonetics requires significant training and recording time. It is often more effective to film one or two real videos first to establish the entity before investing in a digital clone.
Source: Entity SEO for AI Search w/ James Dooley (Charles Floate).