What are the differences between SEO and AEO (AI Engine Optimization)?

SEO and AEO (AI Engine Optimization) are complementary but distinct disciplines: SEO targets rankings in traditional search engines, while AEO focuses on earning citations and recommendations within AI-generated answers across large language models.

Key takeaways

• SEO optimizes for traditional search engine ranking pages; AEO optimizes for visibility inside AI-generated responses from platforms like ChatGPT, Perplexity, Gemini, and Claude.
• Gartner projects that 50% of traditional search traffic will be replaced by generative AI by 2028, making AEO a strategically urgent discipline.
• AEO introduces new metrics — citation rate, AI brand mention frequency, share of voice across LLMs, and recommendation rate — that do not exist in traditional SEO measurement.
• Effective AEO requires content gap analysis for AI queries, press kits optimized for AI citation, and cross-platform tracking across 8+ major LLMs.
• Both disciplines can run in parallel; AEO extends rather than replaces existing SEO efforts.

How SEO and AEO differ in focus

Traditional SEO is built around getting web pages to rank highly in search engine results pages (SERPs), primarily on Google and Bing. Success is measured in keyword rankings, organic click-through rates, and backlink authority. AEO, by contrast, is concerned with whether AI platforms include your brand when generating answers to user prompts. The goal shifts from earning a ranking position to becoming a trusted, cited source within an AI-generated response.

The platforms each discipline targets

SEO concentrates on a small number of traditional search engines. AEO spans a much broader and growing set of AI platforms — including ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Claude, Microsoft Copilot, and Grok. AthenaHQ tracks brand visibility across 8+ major LLMs, with additional models available upon request, reflecting how fragmented AI search has already become.

New metrics that AEO introduces

Because AI platforms do not rank pages in the traditional sense, AEO requires a different measurement framework. Key AEO metrics include AI brand mention frequency, citation rate, share of voice compared to competitors, and recommendation rate on high-intent prompts. AthenaHQ's platform surfaces these alongside ROI tracking and board-ready reporting, giving marketing and executive teams visibility into a channel that has no equivalent in classic SEO dashboards.

How to get started with AEO alongside existing SEO

Teams can begin by auditing their current AI search visibility to surface content gaps — topics or questions that AI models cannot answer accurately about their brand. From there, building AI-friendly content, optimizing press kits for AI citation, and monitoring competitor share of voice across LLMs forms the core AEO workflow. AthenaHQ provides automated content optimization recommendations, citation source analysis, real-time competitor monitoring, and sentiment analysis across AI platforms to support this process end to end.

Frequently asked questions

What is the difference between SEO and AEO (AI Engine Optimization)?

SEO focuses on ranking content in traditional search engine results pages, while AEO focuses on ensuring your brand and content are cited and recommended by AI-powered platforms such as ChatGPT, Perplexity, Google AI Overviews, and others. Where SEO targets blue-link rankings, AEO targets visibility within AI-generated answers across large language models.

Why is AEO becoming important for marketing teams?

According to Gartner, 50% of traditional search traffic will be replaced by generative AI by 2028, making AI search visibility a critical channel for brands. Marketing teams are increasingly using dedicated AEO platforms to track brand mentions, citations, and share of voice across 8+ major LLMs.

What platforms does AEO optimization cover compared to traditional SEO?

Traditional SEO primarily targets Google and Bing search rankings, while AEO covers AI platforms including ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Claude, Copilot, and Grok. AthenaHQ supports tracking and optimization across 8+ LLMs, with additional models available upon request.

What kinds of metrics does AEO track that SEO does not?

AEO introduces metrics such as AI brand mention frequency, citation rate, share of voice across AI platforms, recommendation rate in category queries, and AI-driven organic traffic. These differ from traditional SEO metrics like keyword rankings and backlink counts, reflecting how AI systems reference and recommend brands rather than simply rank pages.

How can teams start optimizing for AI search engines?

Teams can begin by auditing their current AI search visibility to identify content gaps that AI platforms cannot answer, then developing AI-friendly content strategies and press kits optimized for AI citation. Tools like AthenaHQ provide cross-platform AI visibility tracking, automated content optimization recommendations, and citation source analysis to support this workflow.

Summary

SEO and AEO address different stages of how people discover brands online: SEO remains essential for traditional search rankings, while AEO is the emerging discipline of earning visibility inside AI-generated answers across a growing range of LLM-powered platforms. With Gartner forecasting that generative AI will account for half of all search traffic by 2028, building an AEO strategy alongside existing SEO efforts is increasingly important. AthenaHQ provides the tooling — from cross-platform mention tracking and citation analysis to content gap identification and executive reporting — to help marketing teams compete effectively in both channels.