AI search is fundamentally transforming how users discover and engage with information. Unlike in the past, when Google dominated the search landscape, users now turn to multiple AI platforms—such as ChatGPT, Perplexity, and Gemini—alongside or even in place of traditional search engines. This fragmentation of search behaviour requires content creators and marketers to rethink where and how their content is surfaced.
In this blog post, we will discuss factors that impact whether your content appears on AI overviews and tools, as well as strategies for better placement.
Key takeaways
AI search is fragmenting discovery – Users no longer rely solely on Google; they use multiple AI platforms like ChatGPT, Perplexity, and Gemini, meaning brands must optimize for visibility across a wider ecosystem.
AI ranks content differently than traditional SEO – Factors like brand mentions, originality, credibility, and freshness now weigh heavily, while backlinks and keyword density play a smaller role.
Authority and trust are central to AI inclusion – Brands that are consistently referenced by reputable sources and demonstrate expertise are more likely to appear in AI-generated summaries.
Structured, citation-rich content wins – Clear formatting, schema markup, expert quotes, statistics, and original data make it easier for AI models to extract and feature your content.
Adaptation requires active monitoring – Tracking your AI visibility, brand mentions, and referral traffic from AI tools helps identify gaps and opportunities for improving presence in AI responses.
Content must serve both AI and humans – Formats like tutorials, FAQs, original research, and use case pages are highly AI-friendly, but their success still depends on delivering genuine value to human readers.
Structure of search results
The structure of search engine results is evolving. Instead of presenting a list of blue links, AI platforms and search engines now provide synthesized responses that often include citations or embedded brand mentions. These AI-generated summaries provide direct answers, frequently eliminating the need for users to visit websites.
The introduction of AI engines has also changed how websites and their pages are ranked. Ranking is no longer driven solely by backlinks or technical SEO. Instead, visibility within AI responses depends on factors such as content clarity, authority, and the frequency with which your brand or product is mentioned across credible sources.
AI search ranking factors
AI-driven search prioritizes content structure, quality and credibility. One of the most influential factors is brand mentions. Brands that are frequently referenced in reputable online sources have a higher likelihood of being cited by AI tools in their responses and recommendations.
Equally important is content quality and originality. AI models are designed to favour material that showcases true expertise, unique insights, and genuine value over content that is merely keyword-stuffed or SEO-optimized. Pages that reflect real-world experience, thought leadership, and expert understanding are more likely to stand out.
Quotes, citations, and statistics also carry significant weight. Content that includes original data, expert quotes, or properly referenced information is more likely to be surfaced by AI. These signals enhance credibility and help AI systems determine the trustworthiness of responses when assembling them.
From a technical standpoint, content structure and markup are essential. Well-formatted pages, featuring clear headings, summaries, FAQs, and schema markup, enable AI models to more easily interpret and extract relevant information.
Content freshness is a key ranking factor. Recently updated or time-relevant content is more likely to be surfaced by AI, especially by tools that rely on real-time retrieval models. Keeping your content up to date ensures it remains competitive in a fast-moving information landscape.
Adapting to AI search
To rank better on AI searches, start with auditing and tracking your AI visibility. Begin by monitoring prompts where your brand is mentioned, analyzing referral traffic from AI tools, and evaluating your pipeline using self-reported attribution. These insights help reveal your footprint in AI-powered environments.
Next, focus on increasing your probability of appearing in AI outputs. There are three key paths: Be the source of information, be cited or included within trusted sources, or replace existing sources by offering higher-quality or more up-to-date content. Each path helps improve your brand’s likelihood of being referenced in LLM-generated answers.
But AI inclusion isn’t just about tactics — it’s about reputation. To truly succeed in the long run, you need to build a brand that is worth mentioning. That means investing in foundational elements like authority, trust, and expertise. These qualities don’t just help you in search rankings — they position your brand for future relevance across any form of AI output.
Examples of content to create
Search engines and large language models (LLMs) are increasingly surfacing authoritative, well-structured resources that directly address user intent. The table below maps high-impact content formats to each stage of the customer journey, showing how they can be optimized not only for traditional SEO but also for visibility and credibility in AI-powered search results.
Format | Short Description | Customer Journey Stage |
Listicles | “Best X” or “Top Tools” lists | MOFU / BOFU |
Step-by-Step Tutorials | Instructional, actionable guides that solve a specific problem; LLMs often reference these in “how-to” answers. | MOFU / BOFU |
Checklists | Simple, scannable lists that help users validate readiness or follow a process; highly shareable and AI-friendly. | MOFU |
Webinars & Transcripts | Recorded sessions with transcripts optimized for search, allowing AI to pull key takeaways and quotes. | MOFU/BOFU |
Product Reviews and Comparisons | In-depth pros and cons, feature breakdowns, and product comparisons. | BOFU |
API Documentation | Technical reference material designed for developer audiences; rich in structured data and examples. | BOFU |
Documentation / KB | Technical or product guides that become authoritative sources. | BOFU |
Product Pages | Clear details on what you sell, tailored by persona, use case, and industry. | BOFU |
Persona / Use Case Pages | Content is directly mapped to the ideal customer profile (ICP), jobs-to-be-done and context of use. | MOFU / BOFU |
Industry Pages | Pages showing category relevance and vertical expertise. | MOFU / BOFU |
Proof of success from customers | BOFU | |
Interactive Tools / Calculators | Templates, libraries, calculators, tools, and pain-point content that map to needs. | TOFU / MOFU |
Original Data and Research | Proprietary insights, reports, or benchmarks that give you “information gain.” | TOFU / MOFU |
FAQs / Q&A Hubs | Structured, concise answers to common customer questions; easy for LLMs to extract and cite. | TOFU / MOFU |
Glossaries & Definitions | Industry- or product-specific terminology explained in plain language; boosts authority and featured snippet potential. | TOFU |
Stay focused on AI outputs
As AI search continues to reshape how people discover, evaluate, and choose solutions, your content strategy must evolve beyond traditional SEO checklists. Success in this new landscape comes from creating resources that are not only optimized for algorithms but also genuinely valuable for human readers.
By consistently producing authoritative, well-structured, and reference-worthy content, you increase your chances of being cited, quoted, and embedded within AI-generated answers. If you are looking to improve your visibility to AI tools, give us a call.