TL;DR: Search has evolved from blue links to AI answers. But the constant through it all? The Knowledge Graph. In this article, Sam Davis explains how Yext's Knowledge Graph supports visibility across traditional listings, AI-generated search, and future-facing standards — helping UK brands stay discoverable wherever customers look next.
Search has never stood still.
I remember a world before the internet, where searching for information, products, or services relied on scouring through catalogues or the Yellow Pages. Then, the rise of search engines (remember Alta Vista or Ask Jeeves?) through to how Google guided us through the evolution of multiple blue links to map packs, voice assistants to AI agents. The way people discover information has changed again and again. But for brands, the real question isn't what's changed in search? — it's how do we stay discoverable no matter what changes next?
That's where the Knowledge Graph comes in. It's not just a piece of your search strategy — it's the infrastructure that holds it all together.
And it has been for a while.
The past: Listings powered discoverability — and the Knowledge Graph powered listings
For over a decade, search discovery revolved around one dominant surface: Google. That meant having correct, consistent listings data across the web.
Google relied on a network of data aggregators and publishers to verify business information like opening hours, locations, phone numbers, services, and more. If that data was inconsistent or out of sync, your visibility suffered — and your perceived trustworthiness dropped.
That's why the Knowledge Graph mattered. It allowed brands to centralise their business data — and publish it everywhere it needed to go, in the format Google and other platforms required. Structured, consistent, verified data became the foundation of search visibility.
If you were a multi-location brand, trying to manage all of this across hundreds (or thousands) of entities, the Knowledge Graph didn't just help; it made it possible. So, in the era of traditional search, the Knowledge Graph was already doing the hard work: keeping brand data structured, synced, and discoverable.
The present: Search is about answers – and structure drives visibility
Search isn't just about links anymore. People scroll, ask, swipe, and chat — and expect fast, helpful answers everywhere they go. That experience is increasingly powered by AI.
And AI needs data it can interpret — not just content, but context.
That's where structured, brand-managed data makes all the difference.
Recent Yext research shows that 86% of AI citations — the sources that appear in answers from ChatGPT, Gemini, and Perplexity — come from places brands already control: websites, listings, and review platforms. In other words, AI visibility isn't random. It's something you can influence.
The Knowledge Graph is what makes that possible.
By structuring your business information — locations, hours, products, services, FAQs — into machine-readable entities, the Knowledge Graph makes sure your data is ready for AI to understand and surface. Whether it's through an AI experience on your website or a third-party model like Gemini or ChatGPT, the Knowledge Graph is your foundation, powering your brand visibility.
The future: Search will be about integration
We're entering a new phase: one where AI models don't just search the web, they interface directly with brand systems.
Emerging standards like Model Context Protocol (MCP) aim to formalise this. MCP allows large language models (LLMs) to access structured data from registered, machine-readable endpoints, so AI can pull from verified business logic, real-time inventory, analytics sources, location-specific data, and more.
This is the future of AI-powered discovery.
But here's the thing: it's not plug-and-play. It requires infrastructure. It requires your data to be centralised, structured, and ready for integration.
With a Knowledge Graph already in place, you're not starting from scratch — you're starting from strength.
One system. Every era of search.
Whether you're:
Managing listings across hundreds of locations and publishers
Tracking how your brand appears in AI-generated answers
Preparing to expose trusted, machine-readable data to LLMs through protocols like MCP
…it can run on one platform: the Yext Knowledge Graph.
With Yext, you turn brand facts — like store hours, menu items, insurance coverage, FAQs, articles, help & support content — into structured entities that power visibility everywhere search is happening.
From traditional search engines to emerging AI platforms, including behind-the-firewall applications, the Yext Knowledge Graph is your foundation.
Ready for what's next? Start with Scout.
Yext Scout is your brand visibility agent — built on your Knowledge Graph. Deliver fast, accurate answers on your website, in chat, and across digital channels. Click here to learn more.
FAQs:
1. What is the role of the Knowledge Graph in modern search? The Knowledge Graph structures your brand data — like locations, services, and FAQs — into machine-readable entities. This structure helps ensure your information appears accurately across both traditional search engines and AI-powered platforms like ChatGPT and Gemini.
2. How does Yext help brands stay visible in AI-generated search results? Yext helps brands centralise and structure their data so that it's ready for discovery. Recent research shows 86% of AI citations come from brand-managed sources like websites and listings — the very data Yext helps organise and publish.
3. What is MCP, and how is it connected to the Knowledge Graph? Model Context Protocol (MCP) is an emerging standard that will enable AI models to pull structured data directly from trusted brand systems. The Yext Knowledge Graph provides the perfect foundation needed to feed structured entity data directly into MCP servers — making your data AI-ready at scale.
4. Why should marketers act now? Search is shifting fast. AI-generated answers are becoming the norm, and new standards like MCP are already being adopted. Brands that invest in structured data today — with a Knowledge Graph at the centre — are positioned to win in the next era of search.
