## The No Nonsense Guide to Getting Cited by AI *By Ethan Young | Updated July 2, 2025* %%1-pager at 58[[The No Nonsense Guide to Getting Cited by AI v4]]%% ### Executive Summary Not all AI citations come from page 1, let alone rank 1, with extreme recency bias—a shift in SERP dynamics that calls for new optimization strategies. Brands that consistently create and get mentioned in authoritative content will maintain visibility as AI-powered search evolves. ### Top Rankings Aren't a Guarantee, Lower Rankings Aren't a Death Sentence [Advanced Web Ranking (2024)](https://www.advancedwebranking.com/blog/ai-overview-study) analyzed 8,000 keywords across 16 industries and found: - **33.4%** of AI Overview links ranked in the top 10 organic results - **46.5%** of cited URLs ranked outside the top 50 organic results ### AI Accelerates Content Decay [Seer Interactive (2025)](https://www.seerinteractive.com/insights/study-ai-brand-visibility-and-content-recency/) analyzed 5,000+ URLs cited across ChatGPT, Perplexity, and AI Overviews to examine content recency bias in AI systems and found that **nearly 65% of AI bot hits** targeted content published within the past year (2025), though there were strong system and industry variations. ### **What Works: Generative Engine Optimization (GEO)** [Aggarwal et al. (2024)](https://arxiv.org/abs/2311.09735) analyzed 10,000 queries through a simulated generative engine—an LLM + external database—built with GPT-3.5-turbo and found 6 methods that increased AI visibility by 15-40% (domain-specific optimization is possible), with real-world validation on a subset of 200 queries tested through [Perplexity.ai](https://perplexity.ai) showing improvements of up to 37%: 1. **Cite Sources** → Include citations from reliable sources 2. **Add Statistics** → Incorporate relevant data points 3. **Include Quotes** → Add credible expert commentary 4. **Optimize Fluency** → Ensure high-quality writing 5. **Simplify Language** → Make content easy to understand 6. **Avoid Keyword Stuffing** → Don't over-optimize **GEO strategy by ranking position:** lower-ranked competitors using GEO's **Sources** method caused dramatic visibility shifts: - **Challenger Brands:** Aggressively adopt GEO (5th-ranked sites gained 115% visibility) - **Established Brands:** Defend with GEO adoption (top sites lost 30% without it) ### **Why Existing Frameworks Fall short** Most AI/marketing frameworks/acronyms treat AI as a monolithic tech. In reality, there are 3 ways AI systems handle information: 1. **Standalone LLM** → trained on datasets with knowledge cutoff dates (Anthropic's Claude 3.5 Sonnet, OpenAI's GPT-4) 2. **LLM-first + search** → LLM calls search engine when needed (Claude 4 Sonnet, GPT-4o w/ browsing, Perplexity AI) 3. **Search-first + LLM** → search engine results recapped by LLM (Google’s AI Overview/AI Mode w/ Gemini, Bing Chat w/ OpenAI) While GEO proves what improves the odds of representation in generative engines (2 and 3), LLMs (1) require a different approach. ### **The 3 Pillars of Improving AI representation** To holistically address AI representation across all system types: 1. **Master SEO** (on-page, off-page, & technical, adapting to AI crawlers) **and SERP features** (snippets & knowledge panels), including Wikipedia/Google’s Knowledge Graph 2. **Create high-quality content** that incorporates GEO methods, and update existing high-performing content (prioritize decision-making & proprietary data) 3. **Earn authoritative mentions** (prioritize industry-trusted media) that simultaneously: - **Shapes future LLMs** by raising the odds of inclusion in training data - **Boosts organic search rankings** through high-quality backlinks - **Provides credible sources** for generative engines **Have questions/concerns?** [email protected]