TLDR: As AI-powered search engines increasingly dominate how users discover information, brands are rapidly adopting Generative Engine Optimization (GEO) strategies to ensure visibility and relevance, with geographical information playing a more prominent role.
The digital marketing landscape is undergoing a significant transformation as Artificial Intelligence (AI) fundamentally reshapes how users interact with search engines. Brands are now compelled to rethink traditional Search Engine Optimization (SEO) strategies, with a growing emphasis on Generative Engine Optimization (GEO) to secure visibility in AI-powered search results.
Unlike conventional search engines that primarily rely on keywords, large language models (LLMs) and AI-driven platforms like Google’s Search Generative Experience (SGE), Microsoft’s Bing AI, ChatGPT, Gemini, and Perplexity respond to prompts and generate curated, summarized answers. This shift means that simply ranking high in traditional search results is no longer sufficient; brands must now optimize their content to be pulled, understood, and cited within these AI-generated responses.
Industry experts highlight that LLM-based searches are projected to outpace traditional Google searches by 2028. Data from 2024 indicates that Google searches themselves grew by over 20%, partly fueled by the introduction of AI Overviews and new search modes. AI Overviews, which provide summarized answers at the top of search results, now appear in over 13% of desktop queries, significantly impacting organic traffic to traditional links.
Geographical information (GEO) is emerging as a critical component of this new optimization paradigm. As AI assistants become more ‘agentic,’ customer loyalty and hyper-personalized, hyper-local content are becoming essential. This means brands must prioritize data accuracy and a consistent, tailored experience across all channels, ensuring their local presence is optimized for AI consumption.
Several companies are already seeing tangible benefits from embracing GEO. Intimacy wellness brand MyMuse reported a 10% increase in monthly searches on ChatGPT since focusing on GEO. Similarly, wellness brand Kerala Ayurveda has seen its traffic from ChatGPT increase by 2.5 times in the past two months after implementing GEO strategies. Siftly, a Y Combinator-backed startup, and Asva AI are among the companies providing GEO services to businesses across various sectors.
Chalam PVS, co-founder and CEO of Siftly, explains the underlying mechanism: ‘Every LLM relies on some form of search engine under the hood. When a user enters a prompt, the model often queries multiple search engines in real time, scans the results, interprets the content, and then summarises it, all within a few seconds.’ This process underscores the necessity for brands to be structured and credible enough to be referenced and cited by AI systems.
Utkarsh Mishra, Chief Product and Tech Officer at Kerala Ayurveda, noted the growing importance of being cited in AI responses, stating, ‘If users search for travel planning on ChatGPT, it will suggest flights, hotels and restaurants. All brands in these categories now want to be cited in the model’s answer.’ While brands are not currently charged for visibility on LLM platforms, monetization is anticipated in the near future.
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The evolution of local search has progressed through distinct phases: Local 1.0 focused on data accuracy and citation consistency; Local 2.0 emphasized discovery, relevancy, authority, experience, and engagement. Now, Local 3.0, driven by AI, demands that websites serve more as data repositories for AI consumption, with local search results increasingly integrated into AI Overviews. This necessitates a shift from optimizing for keywords to optimizing for how AI pulls, understands, and summarizes content, ensuring brands are visible in an ‘answer-first’ world.
