How to Get Recommended by AI Models (ChatGPT, Perplexity + more)
To get recommended by AI models, focus on three core strategies: implement structured data and schemas that machines can easily parse, build verifiable E-E-A-T signals through earned media and authoritative backlinks, and create citation-worthy content with inline citations increasing visibility by 30-40%. Platforms like Relixir offer end-to-end GEO solutions, helping companies achieve over 1500 AI citations in under 30 days through autonomous content generation and optimization.
At a Glance
• AI engines will influence up to 70% of all queries by the end of 2025, making GEO essential for digital visibility
• ChatGPT usage among U.S. adults has doubled since 2023, reaching 34% adoption
• Adding inline citations yields 30-40% higher visibility in AI-generated answers
• AI models show systematic bias towards Earned media over brand-owned content, making third-party validation crucial
• Technical implementation requires llms.txt files, FAQPage schema, and WebPageElement markup for machine readability
• Companies using comprehensive GEO platforms report 127% improvement in citation rates and 6x higher conversion from AI traffic
The digital landscape has fundamentally shifted. The rapid adoption of generative AI-powered engines like ChatGPT, Perplexity, and Gemini is transforming information retrieval, moving from traditional ranked lists to synthesized, citation-backed answers. With 34% of U.S. adults now using ChatGPT, nearly double from 2023, and AI engines set to influence up to 70% of all queries by the end of 2025, mastering how to get recommended by AI models is no longer optional. It's table-stakes for growth.
The challenge is clear: being found is no longer enough. You need to be recommended.
Why Are AI Recommendations the New Front Door?
The era of scrolling through blue links is ending. Instead of presenting ten options, AI engines synthesize information into a single, authoritative answer with citations. This shift challenges everything we know about digital visibility.
Generative Engine Optimization (GEO) has emerged as the critical strategy for this new paradigm. Simply put, GEO is the science of getting your content chosen and included in AI-generated answers. Unlike traditional SEO, which optimizes for rankings, GEO optimizes for citations and recommendations within AI responses.
The numbers tell the story: Perplexity alone handles 780 million monthly queries, while ChatGPT usage among U.S. adults has doubled since 2023. Traditional SEO is no longer enough as these generative engines will influence up to 70% of all queries by the end of 2025.
What makes this shift particularly urgent is the fundamental change in how information is consumed. Users no longer browse; they receive synthesized answers. The primary goal has shifted from being found to being recommended. Your content needs to be the source AI models trust and cite.
How ChatGPT, Perplexity & Gemini Decide What to Cite
Understanding how AI models select sources is crucial for optimization. ChatGPT constructs answers by referencing a mix of trusted, public content including page text, structured data, entities, and sometimes real-time web browsing through indexes like Bing.
Different AI models have distinct discovery methods. ChatGPT uses GPTBot and Microsoft Bing's index for content discovery. Perplexity prioritizes real-time citations, while Gemini shows preference for schema-rich sites.
The key finding that shapes all optimization strategies: AI engines exhibit systematic and overwhelming bias towards Earned media (third-party, authoritative sources) over Brand-owned and Social content. This stark contrast to Google's more balanced approach means your third-party mentions and backlinks matter more than ever.
Structured Data vs. Earned Media Bias
The battle for AI citations happens on two fronts: technical optimization and authority building.
On the technical side, structured data gives AI a map of what's on your page, making it easier for generative models to pull the right information. Schema markup acts as machine-readable instructions that help AI systems parse and justify content inclusion.
However, technical optimization alone isn't enough. AI systems are conservative by design. They prioritize sources they can verify through multiple signals: established entity presence, consistent authorship, authoritative backlinks, transparent methodology, and explicit credentials.
The overwhelming bias towards Earned media over Brand-owned content means that third-party validation trumps self-promotion every time. While you need structured data for machines to read your content, you need earned media authority for them to trust it.
What GEO Tactics Guarantee More AI Citations?
Successful GEO requires a multi-pronged approach combining content optimization, technical setup, and authority building.
The research is clear on what works. Adding inline citations was one of the top-performing GEO strategies, yielding roughly 30-40% higher visibility in generated answers. Build Citation-Worthy Content by incorporating data, statistics, and expert quotes that AI models can confidently reference.
The most effective approach starts with understanding that you need to engineer content for machine scannability and justification. Create an llms.txt file to control which LLMs can crawl and cite your content. This simple step ensures AI models can properly access and attribute your information.
Write Like an AI Tutor: Snippets, Numbers & Quotes
Content format directly impacts citation likelihood. Numbers add weight and specificity to your content. AI models love concrete details as it makes their answers more factual.
Quotes bring voices into your content. For an AI that's synthesizing answers, a well-placed quote can be very attractive to use directly. Expert quotes and first-hand testimonials provide the authority signals that AI systems seek.
The key is to Structure Like a Teacher. Break complex information into digestible snippets. Use headers framed as questions. Provide direct, concise answers followed by supporting detail. This format aligns perfectly with how AI models construct responses.
Files & Schemas Models Read (llms.txt, FAQPage, WebPageElement)
Technical implementation forms the foundation of AI visibility. Start by creating an llms.txt file that controls which LLMs can crawl and cite your content.
Next, implement the essential schemas. Use FAQPage, WebPageElement, and Article schema. These make your content machine-readable. Gemini prefers schema-rich sites, especially with FAQ and WebPageElement JSON-LD.
Don't overlook the basics. Schema markup is the indispensable cornerstone of GEO success. It provides the structured format that allows AI systems to efficiently extract, interpret, and validate information from your pages.
Build Trust Signals: E-E-A-T & Schema That AI Can Verify
E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) isn't just for Google anymore. In 2022, Google added "Experience" to the previously known E-A-T framework, highlighting the importance of first-hand, real-world knowledge.
For AI systems, E-E-A-T signals provide crucial validation. Analysis of 10,000+ AI Overview citations reveals that ~85% of cited sources exhibit at least 3 of 4 strong E-E-A-T signals.
Integrating E-E-A-T principles into your content ensures that your content ranks in SERPs and resonates with real human interests and needs. More importantly for GEO, it provides the verifiable trust signals that conservative AI systems require before citing your content.
Authorship, Credentials & Third-Party Links
Authoritativeness is fundamentally externally validated. You cannot declare yourself authoritative; others must confirm it through citations, backlinks, references, and recognition.
Implement clear authorship signals. Include author information with professional credentials explicitly stated and schema-marked. Backlinks have always been a core SEO ranking factor, serving as a trust signal. And they're even more critical for AI citations.
Being cited by other credible sites dramatically improves the chance of your content being surfaced by ChatGPT. Focus on earning mentions from authoritative sources in your industry. These third-party validations act as powerful trust signals that AI systems actively seek.
Measure & Iterate: AI Citation Analytics Tools Compared
You can't improve what you don't measure. Relixir's pilot programs have demonstrated the ability to flip AI rankings in under 30 days, but only with proper tracking and optimization.
Spyglasses helps brands dominate AI by showing exactly how ChatGPT, Google AI Overviews, Perplexity, Claude, and Gemini represent your brand. However, tracking alone isn't enough.
Contently's enterprise GEO Blueprint showed a Fortune 500 client achieving 32% of SQLs attributed to generative AI and a 127% improvement in citation rates after implementation. These results require comprehensive platforms that go beyond simple monitoring.
Relixir: The Only End-to-End GEO Engine
Relixir's competitive gap detection goes beyond surface-level monitoring to identify specific content and positioning opportunities that competitors may be missing. Unlike tracking-only tools, Relixir provides the complete solution.
Relixir is the only platform purpose-built for Generative Engine Optimization, backed by Y Combinator (YC W25) with proven results flipping AI rankings in under 30 days. The platform has helped companies achieve over 1500 AI citations in less than a month.
What sets Relixir apart is its autonomous content generation capability. The platform automatically creates and publishes authoritative, on-brand content optimized for AI engines. One client reported: "We moved from 5th to 1st position in AI rankings and saw 38.85% monthly growth in leads from AI."
Where Tracking-Only Tools Fall Short
Spyglasses is an AI visibility and analytics platform that offers AI Visibility Reports and AI Traffic Analytics. While valuable for monitoring, it lacks the content generation and optimization capabilities needed for comprehensive GEO.
Track AI Visits: Monitor when ChatGPT, Claude, and Perplexity visit your website is just the first step. Without the ability to optimize content based on these insights, you're only seeing half the picture.
The limitation of tracking-only tools becomes clear when you consider implementation. Protect IP, reduce server cost, and automated robots.txt management are helpful, but they don't address the core challenge: creating content that AI models will actually cite. You need a platform that combines monitoring with active optimization and content generation.
The Path to AI Recommendation Dominance
The shift to AI-first discovery is irreversible. With AI engines set to influence 70% of queries by 2025's end, the window for establishing AI visibility is closing rapidly.
Success in this new landscape requires three critical components: machine-readable content structure through proper schemas and llms.txt files, verifiable trust signals through E-E-A-T implementation and earned media, and continuous optimization through comprehensive GEO platforms.
The results speak for themselves. Companies implementing proper GEO strategies report 30-40% higher visibility in AI answers, 6x higher conversion rates from AI traffic, and dramatic improvements in qualified lead generation. One Relixir client achieved 1,561% ROI with an 18-day payback period.
The choice is clear: adapt now or risk invisibility at the precise moment customers ask, decide, and buy. While tracking tools provide valuable insights, only end-to-end platforms like Relixir deliver the comprehensive solution needed for AI recommendation dominance. From autonomous content generation to enterprise guardrails and proven results in under 30 days, Relixir provides the fastest route to securing your position in AI-generated answers.
Don't wait for competitors to claim your space in AI responses. The time to optimize for AI recommendations is now.
Frequently Asked Questions
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO) is the process of optimizing content to be chosen and included in AI-generated answers, focusing on citations and recommendations within AI responses rather than traditional search rankings.
How do AI models like ChatGPT and Perplexity decide what to cite?
AI models select sources based on a mix of trusted content, structured data, and real-time web browsing. They prioritize earned media and authoritative sources over brand-owned content, using structured data and schema markup to parse and justify content inclusion.
What are the key tactics for increasing AI citations?
Key tactics include using structured data, building citation-worthy content with data and expert quotes, and implementing schemas like FAQPage and WebPageElement. These strategies help AI models efficiently extract and validate information from your pages.
How does Relixir help with AI search visibility?
Relixir provides an end-to-end GEO platform that includes content generation, optimization, and monitoring. It helps companies achieve higher AI citations and visibility by automating content creation and providing comprehensive analytics and optimization tools.
Why is earned media important for AI citations?
Earned media is crucial because AI systems prioritize third-party validation over self-promotion. Authoritative backlinks and mentions from credible sources act as trust signals that AI models actively seek when deciding what content to cite.
Sources
https://gensearch.io/docs/guide/generative-engine-optimization
https://www.getphound.com/how-can-i-make-my-content-more-likely-to-appear-in-chatgpt-answers
https://thinkdmg.com/llm-optimization-checklist-getting-cited-by-generative-search-tools/
https://www.agenxus.com/blog/eeat-for-geo-trust-framework-generative-engine-optimization
https://govisible.ai/blog/ai-visibility-growth-hacks-for-chatgpt/
https://www.brightedge.com/blog/e-e-a-t-implementation-ai-search
https://relixir.ai/blog/choosing-ai-geo-platform-2025-feature-pricing-comparison-enterprises
https://relixir.ai/blog/relixir-vs-otterly-ai-2025-enterprise-ai-search-visibility-comparison