The landscape of search engine optimization, which has been a cornerstone of digital marketing for over 20 years, is undergoing major changes. Generative artificial intelligence systems are redefining the way users interact with information online, favoring direct answers over traditional lists of hyperlinks.
Encouragingly, many of the established techniques for improving content rankings on search engines also work well with generative AI. However, as our AI engine optimization experts have made clear, industry professionals will have to significantly adapt their strategies to increase visibility on platforms like ChatGPT and Gemini.
Since May 2024, there have been visible changes, especially with Google LLC's AI Overview appearing at the top of search results. As Kevin Roy, CEO of GreenBanana SEO, points out, this feature currently accounts for about 30% of searches in the US, leading to a noticeable drop in click-through rates for many websites.
By next year, a majority of consumers will prefer AI assistants for research and vendor comparisons, according to a report by TheCUBE Research, a SiliconANGLE subsidiary. The forecast suggests that by 2030, more than 70% of B2B software inquiries will be facilitated by AI.
“The observed drop in click-through rates may be due to ‘zero-click behavior,’ where AI systems generate and directly serve answers, effectively sidelining traditional websites,” said Scott Hebner, Principal AI Analyst at TheCUBE Research.
“Traditional SEO strategies are losing visibility as AI platforms decide which brands to highlight in synthetic output.”
Generative AI platforms are rapidly evolving into powerful discovery tools, especially for professional and research-focused queries. Their main appeal lies in efficiency. The generative AI engine strives to provide instant responses, so users can receive answers without having to sift through links.
Roy said that while traditional search engines assess relevance based on the quality and quantity of external links pointing to a web page, generative AI models gain knowledge from structured data, citations, and entity relationships.
prioritize longevity
Roy cited research showing that the average domain age of sources cited on ChatGPT is typically 17 years, indicating that AI systems tend to favor established, consistent entities over less reliable or new sources. Businesses whose strategies rely solely on link-based rankings risk getting obscured by AI-curated answers, despite their potentially powerful search visibility.
Essentially, traditional search engines and generative AI both evaluate similar attributes, but with different methodologies. As Don Dodds, founder of M16 Marketing LLC, states in a Forbes article, AI engines prioritize entity recognition rather than keywords and backlinks.
“Entity optimization emphasizes machine-readable identities, semantic correlation across authoritative platforms, and consistent brand context,” Dodds asserted. “Both search and AI systems are increasingly focused on entities such as people, places, and organizations, rather than just strings of text.”
Visibility is increasingly dependent on how well AI systems can understand a brand’s identity, its products, and the basis for its citations. “They're looking for an overall understanding of your importance in relation to a subject,” Roy added.
Entity Authority Optimization (AEO) consists of two interrelated dimensions. The first one concerns content structure. AI systems typically return concise, synthesized answers, which require well-organized source material.
Employing formats such as short Q&A segments, frequently asked questions, and comprehensive content coverage can significantly help the model extract useful information. While this approach has been historically important in SEO, it has become essential today.
Emphasis on structure
The second dimension concerns authority beyond a single page. AI systems look for indicators that other authoritative sources consistently mention the same entity. Structured data, especially schema markup, is critical to this assessment.
Schemas should utilize standardized JavaScript Object Notation formats to identify important elements such as author, organization, product, and publication date, facilitating clearer interpretation by AI systems.
“Schema used to be a supplementary consideration,” Roy said. “Today, it's almost a necessity.”
Attribution is also gaining attention. Roy advocates associating each piece of content with a legitimate, verifiable author and establishing a dedicated author profile page linked to authoritative external sources, such as professional certifications and industry features.
This approach, called entity stacking, helps AI systems ensure that content links to trusted individuals rather than anonymous sources.
Roy's comprehensive framework, called Entity Authority Engineering, allows organizations to effectively “train” their AI systems to recognize and advocate for their brand.
Key components include ensuring consistent structured data across platforms, tracking brand mentions in authoritative contexts, and evaluating content performance across different AI models rather than just focusing on a single platform.
According to Roy, AEO doesn't make SEO obsolete. However, clear divides are forming within the industry. “Success will favor those who pay attention to these changes,” Roy said. “They're focused on structure, schema, and actual authority. Shortcuts are no longer viable.”
AI engine optimization does not replace basic SEO principles. Rather, it transforms strategy execution. The goal now is not just to secure a ranking, but to gain recognition as a notable entity worthy of being cited in the discourse.
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