The landscape of search engine optimization (SEO) is undergoing significant changes due to the rise of generative artificial intelligence (AI) systems, which provide direct answers instead of traditional lists of links. This evolution, which has been particularly evident since May 2024, when Google LLC introduced AI Overviews summaries at the top of search results, is reshaping how marketers approach online visibility. According to Kevin Roy, CEO of GreenBanana SEO, these AI-generated summaries now appear on approximately 30% of U.S. searches and have led to double-digit declines in click-through rates for numerous websites.
TheCUBE Research, affiliated with SiliconANGLE, anticipates that generative AI will soon surpass traditional search engines as the preferred tool for research and vendor comparisons, projecting that AI will account for more than 70% of business-to-business software research by 2030. This shift is attributed to the “zero-click behavior” that AI systems facilitate, providing users with immediate answers while bypassing traditional web traffic to external sites. Scott Hebner, principal AI analyst at theCUBE Research, noted that conventional SEO strategies are losing their grip as AI engines dictate which brands are highlighted in their synthesized responses.
As generative AI becomes the primary tool for information discovery, particularly for professional and research-oriented queries, it offers users significant time savings. Instead of navigating through links to find relevant content, these AI platforms strive to deliver concise answers directly, often omitting the original sources. While traditional search engines assess relevance and authority based on the quantity and quality of links to a webpage, generative AI analyzes structured data, citations, and entity relationships, according to Roy.
Roy highlighted that the average age of domains referenced by AI models like ChatGPT is 17 years, indicating a preference for established, reliable sources over newer or less reputable sites. Consequently, companies that focus solely on link-based SEO may find themselves overlooked in AI-generated responses, despite maintaining strong visibility in traditional search environments.
The shift towards entity-based recognition is central to this transformation. Don Dodds, founder of M16 Marketing LLC, emphasized that generative AI systems increasingly prioritize entities—such as people, places, and organizations—over mere keyword strings. “Entity optimization focuses on machine-readable identity, semantic connections across authoritative platforms, and consistent brand context,” Dodds stated.
Visibility in the new landscape increasingly hinges on how well an AI system understands a brand’s identity, its relevance in discussions, and its authority on specific subjects. Roy explained that AI engines seek a holistic understanding of brands to determine their significance in content generation.
Roy identified two critical components of what he terms Entity Authority Engineering (AEO). The first involves the structure of content. AI systems favor clearly organized source material, which facilitates the extraction of usable information. Approaches like short question-and-answer formats and comprehensive coverage of topics are becoming essential, with FAQs transitioning from a supplementary tactic to a standard requirement for content optimization.
The second component relates to authority, which extends beyond individual pages. AI systems look for consistent signals from multiple credible sources that recognize and describe the same entity. Structured data, particularly schema markup, plays a vital role by employing standardized JavaScript Object Notation to clarify elements such as authors, organizations, products, and publication dates, allowing AI systems to interpret content without confusion.
Roy noted that while schema markup was previously considered optional, it has now become a necessity in the age of generative AI. Additionally, authorship verification is gaining importance. He advocates for linking every piece of content to a verifiable author and creating dedicated author profile pages that connect to high-authority external sources, a strategy known as entity stacking. This method bolsters AI systems’ confidence in associating content with credible individuals rather than anonymous sources.
Roy’s framework aims to “train” AI systems to acknowledge and trust brands. Key strategies include maintaining consistent structured data across various platforms, mapping brand mentions across authoritative sources, and testing content performance across multiple AI models rather than optimizing for a single platform. He asserted that while AEO does not replace the fundamentals of SEO, it does mark a distinct evolution in tactics. “The winners will be the people who aren’t ignoring this,” Roy said, emphasizing the importance of focusing on structure, schema, and authentic authority in content creation.
As the digital landscape continues its transformation, AI engine optimization reshapes not only how brands approach visibility but also the fundamental objectives of online marketing. The goal now extends beyond mere ranking; it is about being recognized as a credible entity worthy of citation in AI-generated responses.
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