[[{"@type":["Event"],"@id":"https:\/\/www.schemaapp.com\/events\/bseo-san-diego-2026\/#Event","@context":{"@vocab":"http:\/\/schema.org\/","kg":"http:\/\/g.co\/kg"},"url":"https:\/\/www.schemaapp.com\/events\/bseo-san-diego-2026\/","organizer":[{"@id":"https:\/\/www.schemaapp.com\/#Organization"}],"eventAttendanceMode":"OnlineEventAttendanceMode","offers":[{"@type":"Offer","@id":"https:\/\/www.schemaapp.com\/events\/bseo-san-diego-2026\/#Event_offers_Offer","availability":"InStock","price":"0","priceCurrency":"CAD"}],"location":"VirtualLocation","startDate":"Tuesday, September 15, 2026\nCopyright \u00a9 2026 Hunch Manifest Inc dba Schema App. All Rights Reserved. ","subjectOf":[{"@type":"MediaObject","@id":"https:\/\/www.schemaapp.com\/events\/bseo-san-diego-2026\/#Event_subjectOf_MediaObject","video":"About the Speaker\nMartha van Berkel is the co-founder and CEO of Schema App, an end-to-end Schema Markup solution provider based in Guelph, Ontario. She focuses on helping SEO teams globally understand the value of Schema Markup and how they can leverage Schema Markup to boost their SEO strategy and drive results.\nPrior to Schema App, Martha was a Senior Manager at Cisco Systems for 14 years responsible for the global online support strategy. She has a degree in Applied Mathematics and Engineering, attended MIT for Innovation and Strategy, is a Mom of two, as well as an avid rower.\n"}],"name":"From Search to AI Agents: How to Succeed in the Agentic Web Using Schema Markup and Knowledge Graphs","description":"Martha van Berkel at BrightonSEO: Shaping What AI Understands About Your Brand\nAt BrightonSEO San Diego, Martha van Berkel, CEO and co-founder of Schema App, challenged marketers and SEOs to rethink what success looks like as search evolves into AI-driven discovery.\nFor years, websites have been optimized to be found. Rankings, clicks, impressions, traffic, and rich results told us whether search engines could discover and surface our content. But AI systems are changing the role of the website. They don\u2019t just retrieve information \u2014 they interpret it, synthesize answers, decide what to trust, and increasingly act on behalf of users.\nMartha argued that this requires marketers to move beyond asking, \u201cAre we showing up?\u201d and start asking a more important question: \u201cHow are we shaping what AI understands about our brand?\u201d (Read this article to learn more)\nFrom Visibility to Machine Understanding\nAI systems are probabilistic. Without enough structure and context, they are left to infer meaning \u2014 and those inferences can result in inaccurate or inconsistent representations of a brand.\nMartha explained that organizations can reduce that ambiguity by giving machines two things: structured data to communicate the facts, and context to explain how those facts and concepts are connected.\nThis is where Schema Markup takes on a much bigger role. When implemented in a connected way, Schema Markup can create a knowledge graph \u2014 a semantic data layer that helps machines understand the people, products, services, locations, topics, and other entities that define an organization.\nBuilding the Semantic Data Layer for Marketing\nMartha outlined three areas organizations should focus on as they evolve their approach:\n\nBuild the Foundation for Machine Understanding \u2013 Establish strong Schema Markup coverage and quality so machines have a reliable, structured representation of the information across your website.\nEstablish Topic Authority \u2013 Connect the concepts in your content to internal and external entities, creating clearer context around what your organization knows about and where it has authority.\nAction Your Data Layer \u2013 Make that structured, connected knowledge accessible beyond search so it can support AI assistants, copilots, and emerging agent experiences.\n\nThe result is a reusable semantic data layer (also called a context layer) that supports multiple technologies, rather than requiring marketers to build a new foundation every time another AI platform or interface emerges.\nFrom Machine Understanding to Agent Readiness\nAs AI systems become more agentic, being understood is only part of the equation. Agents also need reliable ways to access information, discover available capabilities, and take action.\nShe also introduced emerging technologies including Model Context Protocol (MCP), Microsoft NLWeb, and Agentic Resource Discovery (ARD), which are beginning to define how AI agents can connect with organizational data, discover resources, and interact with websites.\nBuilding for AI Without Sacrificing Search\nPreparing for the agentic web doesn\u2019t mean abandoning the work marketers are doing today.\nMartha shared examples of Schema App customers using advanced Schema Markup and entity linking to improve both traditional search and AI performance, including increased AI Overview visibility, increased search visibility and clicks, and the resolution of an AI hallucination by providing machines with clearer context.\nThe opportunity is to build one foundation that becomes more valuable as the ecosystem evolves \u2014 strengthening machine understanding today while making that same knowledge available to tomorrow\u2019s AI experiences.\nThe Takeaway\nYour website is no longer just a destination for customers or a collection of pages for search engines to crawl. 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