The arrival of generative artificial intelligence and its continuously expanding applications have disrupted various industries and specific professions or practices. Consider digital marketing and search engine optimization as prime examples.
Google has integrated AI in its Google Search results. Generative chatbots like Google Gemini and ChatGPT from OpenAI. Even Meta Platforms and X have built-in chatbots in their platforms. These tools are changing the way people look for information online. Several practitioners have noted that generative AI tools will soon replace search engines.
Enter generative engine optimization or GEO. The term emerged in late 2023 and further gained traction in 2024 and 2025. A 2024 pre-print article by a team of computer science researchers also used and described GEO both as a term and a concept.
What is GEO: Understanding Generative Engine Optimization
Purpose and Principles of Generative Engine Optimization
The purpose of GEO is to increase the chances that a particular webpage or web content is referenced in the search results of an AI-powered search engine and responses of AI chatbots based on large language models with retrieval-augmented generation or online search features. Below are the principles of generative engine optimization:
• Ensure Content is Referenced and Summarized: The primary goal of GEO is for the content to be the source that generative AI tools reference and synthesize when generating direct and comprehensive answers to user queries or prompts.
• Ensure Content is Contextually Rich and Relevant: Optimizing for generative AI also means creating high-quality and in-depth content that tackles user intent and provides comprehensive and accurate information that fits naturally into responses.
• Ensure Content is Structured for AI Understanding: It is also important to make content that particular or various generative AI applications can readily process and integrate using proper structure and information presentation.
• Ensure Content is Authoritative and Trustworthy: The entire GEO undertaking further involves building brand authority and ensuring the particular content is well-sourced since generative AI applications depend on authoritativeness and trustworthiness.
A particular generative engine optimization undertaking has the central purpose of optimizing for visibility in AI-powered search engines and generative chatbots. It specifically involves writing rich and relevant content using clear and factual language, using proper structuring and formatting, ensuring that the brand or the domain is associated with topical authority.
Notable Comparisons With Search Engine Optimization
Traditional search engine optimization or SEO primarily aims to rank websites higher in a list of search results based on keywords and backlinks. However, as the algorithms of search engines like Google Search evolved, modern SEO involves producing high-quality content and websites that demonstrate EEAT or experience, authoritativeness, and trustworthiness.
Most of the principles of generative engine optimization or GEO modern are derived from modern SEO practices. This stems from the fact that modern search engines are now powered by advanced language and information retrieval models. It is still important to underscore the fact that GEO has notable and critical differences with SEO. Take note of the following:
• Purpose: SEO aims to improve the ranking of a webpage or website in search engines or search result pages. GEO aims to get actual content cited and summarized by generative AI applications or tools.
• Output Focus: Optimizing for search engines means getting higher ranks in search result pages to generate organic website traffic. Optimizing for AI or generative engines means getting citations or references to responses.
• Content Emphasis: SEO is a combination of keywords, content quality, backlinks, and other technical factors. GEO puts a premium on content quality, context, relevance, user intent, and EEAT factors.
• Audience: Content optimized for search engines is written in consideration of both search engine crawlers and human readers. Optimizing for a generative engine means writing and publishing content with AI as the content consumer.
The growing popularity of generative chatbots like ChatGPT and the integration of AI in search engines like how Google integrated Gemini in its Google Search have increased the use case for generative engine optimization. Both web content creators and digital markets have the goal of driving referenced traffic from these generative AI applications.
It is still worth mentioning that search engines are still useful for searching web pages or specific web content. Both will remain the main purpose of search engines and SEO practices. Generative AI is useful for getting direct answers. This will become a critical aspect of emerging practices and evolving principles of generative engine optimization.
FURTHER READINGS AND REFERENCES
- Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., and Deshpande, A. 2024. “GEO: Generative Engine Optimization.” In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5–16). KDD ’24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM. DOI: 1145/3637528.3671900