Conversational AI Search Is The New SEO And AthenaHQ Is Proving It

For decades, businesses and digital marketers have optimized their websites for search engines, following traditional Search Engine Optimization (SEO) strategies to rank higher on Google, Bing, and other search platforms. However, as artificial intelligence rapidly reshapes digital interactions, a new paradigm is emerging that is Answer Engine Optimization (AEO). This shift is redefining the way content is structured, delivered, and discovered, aligning with the needs of AI-driven search systems that generate direct answers rather than displaying a list of links.

SEO Isn’t Enough Anymore

SEO has long focused on ranking web pages based on keywords, backlinks, and metadata. However, AI-driven models such as ChatGPT, Perplexity, and Gemini are remodeling the way users find information. Instead of displaying a list of links, these AI systems synthesize data and generate direct answers, creating a shift from conventional search rankings to content that is structured to be retrieved instantly. 

As David Kaufman, founder of GPTrends mentioned, “Unlike traditional search results in Google, results produced by LLMs in products like ChatGPT, Perplexity, Claude AI and others are non-deterministic. This means that the old way of understanding SERP results by location and language won’t cut it. For product visibility analysis in AI Search.”

The landscape is being radically and rapidly transformed by the emergence of generative AI, large language models, and AI chatbots.

AEO differs from traditional SEO by focusing on clustered queries rather than isolated keywords. 

Brand Visibility

Businesses must now frame their content to address multiple related questions comprehensively, ensuring relevance across various user intents. AI models prefer structured, authoritative responses, making it necessary to craft content in a way that is clear, informative, and conversational. The importance of readability, factual accuracy, and logical flow has never been greater, as AI systems prioritize these elements when determining the best responses.

For a year, AEO has garnered some attention. However, its prominence surged in early 2025 when generative AI services like OpenAI’s ChatGPT started featuring prominent links and citations within their responses more frequently. This shift significantly boosted AEO, particularly in terms of brand visibility. 

The integration of retrieval-augmented generation (RAG) technology has significantly improved the potential for businesses to optimize their content for AI-generated search. Unlike earlier AI models that relied on static datasets, newer systems pull fresh information from search engines before generating responses. This advancement allows companies to shape how their content appears in AI-driven answers, providing an opportunity for real-time optimization. Businesses that embrace AEO now have a better chance of influencing the way AI retrieves and presents their information.

AthenaHQ Is Gaining Momentum

Ethan Smith, the CEO of the digital marketing firm Graphite Growth, has mentioned certain startups that are already foraging into this new world of AI searches. 

AthenaHQ is one such leader in AI-driven search optimisation, providing tools that track brand mentions, analyse AI-generated responses, and refine content strategies for businesses. Its experts emphasise that GEO is two-dimensional, where ranking matters, but so does the quality of a brand’s mention in AI-generated answers. Being referenced inaccurately or without proper authority can be just as harmful as not being mentioned at all.

The need for GEO is already proving itself in real-world applications. A SaaS company recently reported a 30% increase in qualified leads after optimizing its content for AI-generated answers rather than solely relying on traditional SEO. This highlights the biggest difference between SEO and GEO while ranking in search engines brings visibility, appearing in AI-generated responses builds trust. Users who receive direct AI-driven recommendations are far more likely to engage with a brand compared to those who merely stumble upon it in traditional search results.

To optimize for AI-driven search, businesses must take active steps to reshape their content strategies. Structured data, such as schema markup, helps AI models interpret context and relevance more effectively. Instead of relying on keyword-heavy pages, brands need to craft well-organized, authoritative content that AI platforms can easily extract insights from. Monitoring how often and in what context a brand is mentioned in AI-generated answers also allows businesses to adjust their strategies in real time, ensuring they remain visible in AI search landscapes.

Early adoption of GEO is already proving to be a key advantage for businesses looking to stay ahead. As its co-founder, Andrew Yan, mentioned in one of his LinkedIn posts, “There will be winners and losers in this shift to AI-based search and product discovery. Less focus on pretty graphics and animations and more on the semantic meaning of website content.”

The company has already surpassed one million AI search responses analyzed, reinforcing the importance of tracking AI mentions and refining content strategies to remain competitive. Much like the companies that optimized for SEO in its early days, those embracing AEO now are positioning themselves for long-term dominance in AI-driven search.