The End of Traditional SEO
Search Engine Extinction: From SEO to GEO 2.0
Picture this: It’s July 1, 2055. It feels like the hottest day you’ve ever experienced. While you were confident you dressed appropriately in the morning, yating. Enough iour tank top quickly feels suffocs enough. You whip out your phone to type your search, “This tank top isn’t cutting it in the 135-degree heat. I need something more breathable, and I need it to match my favorite summer shorts.”
Your search engine yields three results, each of which matches your summer shorts perfectly and aligns with style notes from past queries — including your preferred neckline and fit. At the bottom of those search results, you see your favorite water bottle in a color that matches one of the shirts. It’s also displaying the latest sneakers from a brand you’ve purchased from in the past — their new Airy Star Sprinters — which are made from breathable fabric.
You confirm your purchase of all three shirt recommendations, the water bottle, and sneakers with one click. Just like that, all three items will be at your door in an hour — all without having to visit individual websites, filter color preferences, or select your size. This is the future of retail. Major search engines now provide users with extremely accurate and personalized AI-generated results at the top of the page, and it’s been years since you’ve doomscrolled through an online store to find your ideal product, especially through any search results for “The Best Tank Tops for Summer.”
According to BrightEdge, click-through rates on SERP have declined 30% since search engines launched AI-generated summaries in 2024. Large Language Models (LLMs) crawl websites and content differently than the search engines we are used to. As of July 2025, an estimated 5.6% of U.S. search traffic on desktop browsers went to AI-powered LLMs, according to The Wall Street Journal. As a result, products that once achieved record sales from being featured at the top of the SERP are increasingly overlooked, challenging retailers to adjust their marketing strategies in a way that is understood by AI. The shift is already taking place.
The rise of Generative Engine Optimization (GEO) marks a major change in how consumers shop online. Now, when a consumer starts a “search” for a product, LLMs can respond to their full query with fewer, but more relevant results based on the consumer’s past purchases and preferences that the LLM has learned over time. Amid this shift to GEO, brands must ensure their product data is structured, current, and accessible to AI systems — whether through direct integrations or standardized formats — and will benefit from verified user feedback, and more. Providing content in an accessible, universally readable format ensures that products are consistently surfaced in personalized AI-driven results — not because of keyword stuffing, but because the AI understands the product’s value in the shopper’s specific context.
As soon as 2030 AI generated search experiences could dominate, reducing reliance on traditional rankings and shifting how shoppers discover products. Retail websites will evolve alongside search to serve both human users and AI systems — transitioning to structured data hubs that support personalized, context aware results.
Search engine optimization (SEO) is currently transforming into a broader strategy that includes optimizing for AI generated summaries, structured data and semantic relevance marking the rise of GEO, requiring retailers to focus on how they will shift their content strategy to remain relevant in the GEO era.
AI Agents Will Run the Rankings
For decades, brands have poured money into marketing strategies aimed at placing products at the top of search results. SEO requires marketers to tailor content for better visibility in search results via strategic keywords, high-functioning websites, and quality backlinks to increase organic visibility. But according to Digiday, search experts are less focused on increasing a brand’s ranking on the SERP and instead are innovating on how they can increase brand exposure across a variety of channels.
With the emergence of advanced, AI-generated search results, brands must reposition their content so it provides immediate value — not only to minimize website navigation for users, but also to ensure relevance and accessibility for AI summaries across channels. Retailers must also think of ways to structure content in a more personalized manner to the user’s habits and preferences, focused on use intent rather than keyword optimization.
With this change, retailers should complement traditional SEO strategies with real customer reviews and feedback, as AI systems increasingly prioritize real world sentiment and product relevance over keyword density. While these AI-driven changes are reshaping search, maintaining strong SEO fundamentals remains critical for retailers to help boost their discoverability and properly structure their content for both traditional search engines and AI systems.
While paid placement will remain in the mix over the next few years, AI will increasingly recommend products based on quality, reviews, and personalized needs — suggesting products that match the user’s preferences based on real customer feedback. This shift will transform retailers’ marketing playbooks, enabling new demand generation strategies and potentially reducing dependence on paid search.
As we get closer to this reality, websites will evolve to balance visual branding with structured data repositories, serving both human users and AI systems that digest and interpret product information. No longer designed purely as aesthetic destinations to keep users engaged, websites will primarily provide information. In this environment, brands must strategically redesign to embed their unique voice and identity into the data, ensuring consistency between the reimagined website and how AI presents their brand.
As consumer expectations shift toward deeper personalization, shopper behavior will ultimately favor brands that combine AI convenience with trustworthy information sources and verified outputs. Retailers who want to future-proof their business should shift their content strategy so it aligns with the new way customers find information in AI-driven environments.
Is your content stuck in an SEO universe while customers are living on an AI-powered planet? To navigate this new AI frontier, listen to our 60-second Retail podcast episode on creating a roadmap for tech investments.
Best Practices for Shifting from Traditional SEO to AI-Optimized Content
The transition to GEO will require retailers to reimagine the way they create and distribute content. For their products to break through the noise, they will need to focus on structured data that clearly defines product attributes, pricing, and availability. This means maintaining consistent factual product data across all digital touchpoints that AI can easily crawl and verify. These models learn from well-optimized content, making SEO a prerequisite for effective AI readiness.
There are several elements retailers should consider when assessing their websites and apps to improve how AI platforms interpret and repurpose their content. In addition to clearly displaying product data, authentic brand voice will play a key role in the next phase of GEO. AI systems will increasingly prioritize content that statistically aligns with user behavior and semantic relevance, making consistency and clarity in content critical for retailers to gain visibility with AI. A consistent brand voice is critical because AI determines which information to present to users based on its ability to identify patterns, distinguish the content as relevant, and pair that with verified customer feedback.
Though the move from SEO to GEO is still in the early days, some retailers are already beginning to adjust their strategies. One furniture retailer, for example, already set its internal algorithm to “reward accuracy, consistency, and depth.” Another diaper retailer saw an increase in purchases originating from AI searches and is now trying to determine how they can enhance their GEO for product-related search queries.
Retailers that take advantage of this new discovery method now may unlock a competitive advantage in the future, as AI-driven search continues to evolve. By gaining early insights into how AI interprets and presents product information, they can better refine marketing strategies and strengthen brand consistency. To face these changes with confidence, retailers should consider working with experienced digital advisors who can help assess and realign business strategies to respond to AI-driven market shifts.
Reset, Rethink, and Respond: How BDO Helps
Retailers Adapt to AI-Driven Market Shifts The rise of GEO 2.0 is more than a technology upgrade — it’s a fundamental market shift. Retailers must reset their strategies to adapt, not just adopt, as AI transforms how consumers discover, evaluate, and purchase products. This means rethinking how you structure product data, engage customers, and measure success before undertaking more mature AI initiatives.
BDO’s Strategy & Innovation group can evaluate your current business strategies and operations, helping you determine the right timing, scope, and approach for evolving operations in response to AI-driven market shifts. Whether you’re looking to audit your current marketing technology stack, develop comprehensive demand generation strategies, or elevate customer acquisition and retention programs, BDO is ready to help retailers build a resilient foundation for measurable ROI.
If you are further along in adapting your strategy, our BDO Digital Demand Gen team can help you modernize marketing strategies for the AI era. We help retailers strengthen demand generation, adapt to the evolving role of SEO in an AI-first search landscape, and identify gaps and opportunities in your digital ecosystem.
Is your retail organization ready for the new rules of engagement in an AI-First world? Discover how AI agents are reprogramming consumer interaction and decision-making in the AI era with BDO's Retailer's Guide to Agentic AI.