Editorial
Research Report
Power Personalized CX with AI That Remembers What Customers Don’t Want to Repeat
The Gist
- AI traffic is small—but strategically outsized. Organic search still drives most visits today, yet AI-driven discovery is reshaping how customers first encounter brands.
- Search volume is headed for contraction. Gartner projects a 25% drop in traditional search by 2026, pushing CMOs to rethink talent, content, and visibility beyond classic SEO.
- SEO vs. AEO is a false choice. The winning playbook balances near-term rankings with answer-engine optimization, as AI citations follow different rules than search results.
- Visibility is becoming a future metric. Brands absent from AI answers today risk losing awareness tomorrow as AI platforms move toward mainstream adoption.
When marketing teams examine their referral sources in their analytic dashboards, they are looking for numbers that tell a clear story. Often, the story is associated
That traffic has become increasingly represented by AI-generated searches. SEO experts are concerned about the volume of website arrivals of customers from those searches.
Experts believe that AI platforms are sending minimal traffic. According to Conductor's benchmark report analyzing 3.3 billion sessions across 13,770 domains, AI referral traffic accounts for just 1.08% of all website visits. Meanwhile, organic search continues delivering 53% of traffic, with healthcare is seeing 42.4% organic share and communication services reaching 39.6%.
This disparity raises a critical question for CMOs and marketing directors: How should brands invest heavily in Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) when the current traffic impact barely registers in analytics dashboards?
The answer requires understanding both present performance and future positioning. This post examines both conditions and what it means for your customer experience strategy.
Table of Contents
- FAQ: AI Search, SEO and the Rise of AEO
- The Emerging Shift From Search Queries to AI Conversations
- The Strategic Case for AEO/GEO Despite Minimal Current Traffic
- Building the Dual-Track Playbook: Immediate Actions and Future Preparation
- Developing the Dual-Channel Optimization Playbook
FAQ: AI Search, SEO and the Rise of AEO
Editor’s note: CMOs and digital leaders are navigating a search landscape where traffic tells one story and discovery tells another. These questions address how to balance today’s performance with tomorrow’s visibility.
Not consistently. While there is overlap, AI engines frequently cite authoritative or specialized sources that do not rank in top search positions, creating new opportunities for brands outside traditional SEO leaders.Measurement must evolve beyond clicks. In addition to organic traffic and conversions, teams should track AI citations, brand mentions in AI responses, and share of voice across AI platforms for priority topics.Because visibility is shifting upstream. Brands cited in AI answers gain awareness and credibility before customers ever reach a website. Waiting until traffic appears risks falling behind competitors already shaping AI-driven discovery.No. SEO remains the primary driver of web traffic and revenue today. The shift is not replacement but expansion, with AI answer engines introducing a parallel discovery channel that operates by different rules.Loss of future visibility. As AI platforms scale toward mainstream adoption, brands absent from AI answers risk becoming invisible during early-stage research, even if their SEO performance remains strong.SEO optimizes content for ranked links and clicks. AEO optimizes content to be selected, cited or summarized by AI systems that deliver direct answers. Success increasingly requires both.AI-driven referrals remain low because most AI platforms answer questions directly, reducing the need for users to click through to websites. Discovery is happening, but it is increasingly invisible to traditional traffic metrics.
The Emerging Shift From Search Queries to AI Conversations
AEO has been called a lot of different names, such as GEO. I prefer AISO, as I mentioned in an early post. No matter the name, the concept involves accounting for AI's influence in determining online content in a search.
Traditional search has served as marketing's primary discovery channel, with workflows built around keyword optimization, SERP positioning and click-through rate optimization. The emergence of ChatGPT, Perplexity and AI-powered search features from Google and Microsoft introduces a different paradigm: conversational discovery, where users receive synthesized answers rather than ranked links.
This shift impacts marketer workflows in measurable ways. According to eMarketer, generative AI engines account for only 3.3% of online discovery time in the US as of August 2025; this represents the early stages of a fundamental transformation in how consumers find information and make purchase decisions. In this stage customers who use ChatGPT or Google's AI Overviews to research products are encountering brand mentions embedded within AI-generated summaries rather than organic listings. Conductor's analysis found that ChatGPT drives 87.4% of all AI referrals, establishing it as the dominant player in this emerging channel.
The implications extend toward how search budgets are deployed. According to Gartner's 2024 CMO Spend Survey of 395 respondents, the average CMO allocated almost a quarter of their digital marketing budget to search. Gartner also predicted that traditional search engine volume will drop 25% by 2026 due to AI chatbots and virtual agents.
Customer experiences after viewing AI-enhanced search add another dimension. Research from Ahrefs shows that AI Overviews reduce click-through rates significantly—a 34.5% drop in position 1 CTR when AI Overviews appear. BrightEdge data reveals search impressions jumped 49% year-over-year while click-through rates dropped 30%.
All of these trends create a paradox where visibility increases but engagement decreases as users find answers without clicking through to source websites. Marketing teams face resource allocation decisions that must balance current channel performance against projected disruption.
The Strategic Case for AEO/GEO Despite Minimal Current Traffic
While current AI referral traffic registers at approximately 1%, forward-looking marketing leaders recognize that lagging indicators shouldn't dictate future-focused strategy. The evidence suggests that brands building AEO/GEO capabilities now position themselves for significant competitive advantages as AI adoption accelerates.
The growth trajectory indicates rapid AI platform adoption despite the current low traffic share. AI-referred sessions saw a 527% year-over-year increase according to Search Engine Land's August 2025 analysis, demonstrating exponential growth even from a small base. Gartner research predicts that by 2027, mobile app usage will decrease 25% due to AI assistants as consumers shift to ChatGPT, Google Gemini and Meta AI for functions previously requiring app launches.
Citation analysis reveals that AI platforms highlight different brands than traditional search rankings, creating new visibility opportunities. Across 17 million AI answers and 100 million citations analyzed by Conductor, AI engines cited authoritative sources differently by category. In consumer industries, retail giants dominated (Amazon, Walmart, Target). For YMYL categories covering health and finance, AI cited Mayo Clinic, Cleveland Clinic, NerdWallet and Bankrate.
Research from Ahrefs found that while 76.1% of URLs cited in AI Overviews also rank in the top 10 Google search results, ChatGPT Search primarily cites lower-ranking pages (position 21+) about 90% of the time. Only 12% of URLs cited by ChatGPT, Perplexity and Copilot rank in Google's top 10 search results. This citation behavior creates strategic opportunities—brands that optimize specifically for AI answer engines can gain visibility in AI responses even without top traditional search rankings.
The conversion quality data supports investment: Semrush research shows LLM visitors convert 4.4 times better than organic search visitors, indicating higher intent among users receiving AI-generated recommendations.
Related Article: Survive the AI Takeover of Search — 5 Moves Every Brand Must Make
Building the Dual-Track Playbook: Immediate Actions and Future Preparation
Marketing leaders facing resource constraints don't need to choose between SEO and AEO—they need structured frameworks for pursuing both simultaneously at appropriate investment levels.
Here's are the pillars to building a successful content discoverability strategy in 2026:
Content Strategy Framework
The foundation requires content that serves both traditional search and AI answer engines. The average first-page Google result contains 1,447 words, but AI platforms prioritize different content attributes. Brands should create authoritative long-form content that ranks in search while ensuring key information appears in structures AI can easily extract and synthesize. According to Digital Marketing Institute research, 65% of companies report improved SEO performance with AI-generated content when combined with human editing that preserves E-E-A-T signals.
Technical Implementation
Structured data implementation helps both search engines and AI platforms understand content context. While traditional SEO benefits from schema markup for rich snippets, AI answer engines use this same structured information when synthesizing responses. Site architecture decisions should consider both crawlability for search engines and information retrieval for AI systems.
Measurement Framework Evolution
Analytics teams need expanded KPI frameworks that track both current performance and future positioning. Traditional metrics — organic traffic, keyword rankings, conversion rates — remain essential. Marketing leaders should add AEO-specific metrics: brand mention frequency in AI responses, citation rates across different AI platforms, and share of voice in AI-generated answers for core topics. Leveraging marketing analytics platforms can help teams track these emerging metrics alongside traditional performance indicators.
Talent and Capability Development
Gartner research emphasizes that 26% of tech marketing respondents increased talent investment due to GenAI, with 54% increasing technology investment. The CMO Survey data showing 73% of marketing teams using generative AI in 2025 (up from 37% in 2023) indicates competitors are developing these capabilities — talent development becomes a competitive requirement.
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Budget Allocation Strategy
Resource allocation should reflect both current ROI and strategic positioning. A pragmatic framework allocates 70-80% of search budget to traditional SEO that delivers immediate traffic and revenue, while dedicating 20-30% to AEO/GEO experimentation and capability building. This distribution maintains current channel performance while developing competencies for platform transition. Understanding marketing trends can help leaders make informed decisions about where to allocate resources.
Developing the Dual-Channel Optimization Playbook
The playbook marketers must have for modern online search strategies involves building organizational capabilities that excel at both SEO and AEO. Marketers must recognize that today's analytics reflect yesterday's user behavior while tomorrow's customer journey increasingly includes AI-powered discovery at multiple touchpoints. Marketing teams that develop dual-channel optimization expertise now avoid the scramble when AI referrals become the initial driver of customer experiences.
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