Beyond Keywords: Moving to Entity-Based SEO for the AI Search Era

But as search evolves into Generative Search (SGE/AEO/GEO), Google and other LLMs have stopped looking at strings and started looking at things. In technical terms, we are moving from keyword matching to Entity-Based SEO.

At Atlantic Zero, we help organizations transition from simple content creation to building a verified digital footprint. Gartner research indicates that by 2026, traditional search engine volume will drop by 25 percent as people pivot toward AI-powered search engines and generative agents¹. To remain visible, brands must shift their focus toward structured data that defines who they are, rather than just what they say.

We operate with a few key tenets in mind whenever we evaluate the fit for Entity-Based SEO:

Advanced Schema: Building the Source of TruthSchema markup is no longer just for "star ratings." It is the primary language through which you tell search engines who you are. By using nested JSON-LD markup, linking Service to AreaServed and Organization to KnowsAbout, you create a "Source of Truth" that AI models can ingest without the risk of hallucination.

Connectivity and "SameAs" TriangulationAI models build trust through cross-referencing. By utilizing the sameAs property in your schema, you can explicitly link your website to high-authority third-party sources like LinkedIn, Wikipedia, or industry-specific review sites. This triangulation confirms your authority to the Knowledge Graph, making your brand a "trusted entity."

Content Chunking for AI ConsumptionLLMs prefer fact-dense content. Instead of long, winding paragraphs, restructure your technical and service pages into concise modules. Use headers as clear questions and the body text as definitive, data-backed answers. This makes your content easily "snippetizable" for AI-generated summaries.

When applied strategically, this approach creates long-term resilience. According to Microsoft Research, entities provide the structural foundation for modern information retrieval because they allow search engines to move beyond text matching toward true semantic understanding².

The Impact: Resilience in the Knowledge Graph

• Regional Healthcare Network (Healthcare): We deployed a nested MedicalBusiness schema that explicitly maps physician credentials to local facility entities, resulting in a 42% increase in citations within Google AI Overviews for high-intent surgical queries.
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• Commercial Restoration Franchise (Home Services): We implemented a ServiceAreaBusiness (SAB) framework that redefined geographic boundaries via advanced areaServed markup, driving a 35% lift in brand mentions within Perplexity and Gemini "Top Recommendations" for urgent local prompts.
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• Enterprise Logistics SaaS (B2B Tech): We utilized "SameAs" property mapping to triangulate brand authority across independent review platforms and technical documentation, ensuring the brand now appears in 80% of AI-generated "Top 5" comparison lists for their category.

In the AI search era, you are not just trying to rank for a term. You are trying to be recognized as the definitive answer.

References

1. Gartner – Gartner Predicts Search Engine Volume Will Drop 25% by 2026 (2024)https://www.gartner.com/en/newsroom/press-releases/2024-02-19-gartner-predicts-search-engine-volume-will-drop-25-percent-by-2026-due-to-ai-chatbots-and-other-virtual-agents
2. Microsoft Research – Entities as a First-Class Citizen in Search (2023)https://www.microsoft.com/en-us/research/publication/entities-as-first-class-citizens-in-search-and-recommendation/

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