What is the Future of SEO in an “AI-Mode” World?
Like technology in general, the search world is constantly evolving. When we first wrote about “the future of SEO” in 2016, we didn’t have ChatGPT, Google AI Mode, Google AI Overviews, Google Gemini, Perplexity.ai or Anthropic’s Claude. Things were simpler then, yet people were still crying “death to SEO!” With 200+ ranking factors and an incalculable number of AI updates annually, the future of traditional SEO is more foggy than ever. Will link building die a painful death only to be primarily replaced by the likes of AI, machine learning and some sort of peer-to-peer search engine built on the blockchain? But what does the future hold for search engine optimization (SEO)? Will traditional SEO die to the AI overlords? Possibly. But it’s a bit more nuanced than that. Let’s dive in. The Death of the Blue Links: How AI Is Reshaping the SERPs Gone are the days when search engine results pages (SERPs) were dominated by ten blue links. Today, Google and its competitors prioritize AI-generated answers, knowledge panels, featured snippets, video carousels, and other rich features. With the introduction of Google’s Search Generative Experience (SGE), AI-generated summaries now answer user queries directly at the top of the page, often eliminating the need for users to click through to websites. Zero-click searches are on the rise, and traditional SEO strategies that relied on ranking #1 are losing ground. Meanwhile, new AI-native search engines like Perplexity and You.com are bypassing websites altogether, citing sources within generative answers. The game is changing—and fast as witnessed by the ever-changing stats of AI search usage (thanks to Mike King of iPullRank): What Constitutes Real SEO Disruption? Because of this incremental phenomenon, it’s tough to categorize what might count as a search engine “disruption.” Usually, a tech disruption happens all at once—when a new product is released, a new trend takes off, or a new company emerges to challenge the norm. Now that all the norms of search are pretty much in place, the minor “disruptions” we’ve had so far (usually in the form of Google updates) can’t really claim to have that much impact. User search behavior has changed much in the past 20 years, but again, it’s done so incrementally. Still, knowing that, the search world may be on the verge of a major disruption in the truest sense—a new set of phenomena that may turn the nature of online search on its head. And it’s already starting to take place. Content Overload & the Rise of Machine-Generated Content AI content tools have revolutionized content creation. Platforms like ChatGPT, Jasper, and Claude allow marketers to produce blog posts, product descriptions, and landing pages at unprecedented scale and speed. This ease of content creation has resulted in a deluge of low-quality, repetitive content across the web. In response, Google launched the Helpful Content Update (HCU), emphasizing “people-first” content that demonstrates expertise and originality. The challenge now is standing out in a sea of sameness. While AI can generate words, it often lacks insight, experience, and context—areas where human oversight is critical. Backlinks & Authority in an AI-Filtered World Once the gold standard of SEO, backlinks are facing a credibility crisis. As AI-driven search engines prioritize relevance, context, and authority, the traditional model of link building services is losing potency. Today’s algorithms weigh brand recognition, topical authority, and user engagement signals more heavily than raw link counts. Digital PR, social media shares, and legitimate citations now carry more weight than directory links or guest posts. In this new reality, authenticity and trust matter more than ever. The Changing Nature of Keyword Research The way users search is evolving. Thanks to LLMs and voice assistants, queries are more conversational and complex. Instead of typing “best SEO tools,” users might ask, “What are the most effective tools for improving my site’s search performance in 2025?” Keyword research is shifting from targeting specific phrases to building topical authority. Entity-based SEO, semantic relevance, and understanding user intent are the keys to future-proofing your strategy. Winning in SEO now means optimizing for concepts, not just relevant keywords. Personalized, Probabilistic Visibility In AI Mode and AI Overviews, search is deeply personalized. LLMs use persistent context and user embeddings to tailor results. This means two users can ask the same question and receive different answers, based on interaction history, location, or inferred preferences. Zero-click searches are becoming the norm as AI-powered search engines aim to satisfy search intent directly within the interface. Instead of sending users to a third-party website, systems like Google’s SGE or Perplexity AI provide synthesized answers on the results page itself, often citing a source but without generating organic traffic. Barry Schwartz and others have referred to this as the “Great Decoupling” of clicks vs. impressions: This creates a paradox: your content might influence the user’s decision without ever being visited. As AI Mode matures, visibility no longer guarantees engagement—it must be measured in citations, not just clicks. In AI Mode, search is deeply personalized. LLMs use persistent context and user embeddings to tailor results. This means two users can ask the same question and receive different answers, based on interaction history, location, or inferred preferences. Implication for SEO: Static rankings are no longer reliable. Traditional rank-tracking tools are blind to the probabilistic, ephemeral nature of LLM-driven responses. New metrics must be created to measure AI citation frequency and visibility. Generative Relevance Engineering: The Next Discipline in SEO With AI-driven search shifting toward probabilistic passage-level ranking, a new discipline is emerging: Generative Relevance Engineering. The goal isn’t just to rank pages—it’s to create modular, vector-aligned content passages that AI models want to include in their synthesized answers. This involves: Query Fan-Out Coverage: Optimizing for the many variations of a core query. Passage Optimization: Writing atomic, standalone assertions that answer specific sub-questions. Embedding Alignment: Structuring content to align with semantic vector searches. Multimodal Content: Creating complementary assets like charts, video, or tables that AI can cite. Don’t just create AI generated content for the sake of content.