Session Tiltle：Exploring relationships between AI answer engines and organic SERPsIn April 2025, MediaReach, Inc. attended BrightonSEO Spring 2025, one of the world’s premier search marketing conferences held in Brighton, UK. This report covers a key session led by Ray Grieselhuber, CEO of DemandSphere, titled “Exploring relationships between AI answer engines and organic SERPs.”As AI-powered answer engines like ChatGPT and Perplexity become more prominent in the search journey, SEO professionals must rethink how visibility is defined and achieved. This session delved into the underlying mechanisms of these engines—especially their reliance on traditional indexes like Google and Bing—and how technologies such as Retrieval-Augmented Generation (RAG) are reshaping the landscape.Our SEO Consultant, Ayaka Uchida, shares practical takeaways from the session and reflects on what these developments mean for the future of organic visibility in an AI-driven world.Written by Ayaka UchidaSEO Consultant, MediaReach, Inc.1. Executive SummaryThis session explored how AI-powered answer engines like ChatGPT and Perplexity are reshaping the way users interact with search and how SEO professionals must respond. The talk covered the mechanics behind these engines, particularly how they retrieve and rank information using traditional indexes.It was emphasized that generative AI is not replacing SEO, but rather creating new layers of complexity in visibility, measurement, and optimization strategies. Insights were backed by original data comparing how different engines (Google, Bing, Perplexity, ChatGPT) handle source content.2. Session DetailsSession Title: Exploring relationships between AI answer engines and organic SERPsSpeaker: Ray Grieselhuber (CEO, DemandSphere)Date / Time: Thursday, April 10, 2025 — 03:20 PMVenue: Auditorium 1, Brighton Centre, Kings Road, Brighton and Hove, Brighton, BN1 2GR, United KingdomEvent: BrightonSEO Spring 2025Session Link: https://brightonseo.com/sessions/ai-and-user-experience3. Report Details3-1. Context and BackgroundThis session focused on the evolving relationship between traditional organic search and emerging AI-driven answer engines. Although the surface interfaces are shifting—moving from keyword queries to natural language prompts—underlying systems still rely heavily on indexed content from engines like Google and Bing.The speaker addressed the rise of Retrieval-Augmented Generation (RAG), where LLMs pull updated information from web indexes to supplement outdated training data. This process makes traditional SEO practices relevant even in AI-first environments.3-2. Key Messages and TakeawaysAI engines continue to rely on traditional search indexes for real-time, accurate responsesCurrent AI-generated answers often cite outdated or incomplete sources unless RAG is usedRanking high on Google does not guarantee visibility in ChatGPT or Perplexity resultsThere is no standard way to measure AI visibility (e.g., share of voice) yetPrompt clustering and query transformation offer new areas for SEO experimentationDespite small overall traffic volume from AI search engines (less than single-digit percentage), their influence is growing rapidlyGoogle and Bing indexes are still powering approximately 80% of AI responses, with Perplexity using Google's index about 55% of the timeProprietary datasets reveal major differences in how engines cite and re-rank content3-3. Visual Materials and SlidesFigure 1: Slide showing the shift to multimodality in search interfac：Figure 2: RAG (Retrieval Augmented Generation) diagram connecting search index with language models：Figure 3: Chart showing Gen AI search traffic volume (less than single-digit percentage)：Figure 4: Live Retrieval (RAG) components illustration：Figure 5: Framework for prompt targeting using People Also Asked patterns：Figure 6: Share of Voice (SoV) evaluation metrics for AI visibility：3-4. Practical SEO ImplicationsShort-term:Track which URLs are being cited in AI-generated contentBegin experimenting with prompt-based SEO structuresMonitor discrepancies between traditional rankings and AI responsesAnalyze "People Also Ask" data to identify potential AI prompt patternsLong-term:Create content structures optimized for RAG indexing and retrievalEstablish measurement systems for AI-driven visibilityInvest in branding and trust signals to influence inclusion in generative answersDevelop content optimized for conversational AI queries3-5. On-site ImpressionsIn the afternoon session, many participants gathered in the venue, showing a high level of interest in the relationship between AI and search experience. Ray Grieselhuber, the speaker, carefully explained industry trends and data-backed analysis, with attendees taking notes attentively. Particularly, the explanation of RAG and the relationship with traditional SEO deeply engaged the professionals in the room.3-6. Personal ReflectionActually, I've been using ChatGPT as my first step in searches lately. I used to think that as OpenAI accumulates more data, it could surpass Google. However, after this session, I realized that Google’s index remains the core of the search ecosystem. I strongly resonated with the view that Google will continue to be the 'Database' as long as service information is stored in LPs.4. Supplementary MaterialsSpeaker Deck: https://speakerdeck.com/raygrieselhuber/exploring-the-relationship-between-traditional-serps-and-gen-ai-searchWritten by Ayaka UchidaSEO Consultant, MediaReach, Inc.