Google something like "Apple" and you see a panel on the right with the logo, founding date, CEO, stock price. That's the Knowledge Graph at work. It knows "Apple" the company is different from "apple" the fruit, and it knows a ton of facts about both.
What a knowledge graph actually is
A knowledge graph is essentially a giant database of things and how they relate to each other. Not just keywords and documents, but actual entities: companies, people, products, concepts, places.
Each entity has attributes (Apple was founded in 1976, its CEO is Tim Cook) and relationships to other entities (Apple makes the iPhone, Apple competes with Samsung, Apple was co-founded by Steve Jobs).
This structure lets systems answer complex questions. Not just "find pages with these keywords" but "what companies make smartphones" or "who founded Apple."
Why AI systems rely on knowledge graphs
Large language models are trained on text, which gives them general knowledge. But for current, factual, entity-specific information, they often tap into knowledge graph-like structures, either through their training data or through real-time retrieval.
When you ask ChatGPT about a specific company, it's drawing on structured knowledge about that entity. What category is it in? What does it do? How does it compare to similar entities?
If your brand exists clearly in these knowledge structures, AI can confidently talk about you. If you're a fuzzy, poorly-defined presence, AI has less to work with.
How to get into the knowledge graph
For Google's Knowledge Graph specifically:
Claim your Google Business Profile. This is the most direct way to establish your entity with Google.
Use structured data (schema markup). Organization schema, product schema, person schema. This explicitly tells search engines what kind of entity you are.
Wikipedia and Wikidata. These are major sources for knowledge graphs. If you're notable enough for a Wikipedia entry, that's a strong signal. (Don't create one yourself, that violates their rules. But you can ensure accurate information on Wikidata.)
Consistent information everywhere. Same name, same description, same key facts across your website, social profiles, directories. Knowledge graphs reconcile information from multiple sources. Consistency helps.
The connection to AI visibility
Here's why this matters for getting recommended by AI: knowledge graph presence signals legitimacy and clarity.
When AI tools decide who to recommend, they're essentially looking at entities and comparing them. If your entity is well-defined in these systems, if it's clear what you are, what category you're in, what your attributes are, you're easier to recommend.
A brand that exists as a clear entity with consistent information is easier to trust than one that's a vague collection of web pages.
Practical steps
Most small businesses won't get into Wikipedia, and that's fine. Focus on what you can control:
- Google Business Profile (if applicable)
- Schema markup on your website
- Consistent NAP (name, address, phone) across directories
- Clear, consistent brand description everywhere
- Profiles on relevant platforms that feed into knowledge systems (LinkedIn, Crunchbase for B2B, etc.)
The goal is to be a well-defined entity, not just a website. Knowledge graph thinking forces that clarity.