Content cited by ChatGPT, Gemini, Claude, and Perplexity often shares key structural traits. A new HubSpot and AirOps study reveals which formats boost visibility in AI-generated answers.
As AI-powered search tools like ChatGPT, Gemini, Claude, and Perplexity become more influential in how audiences discover information, content creators face new challenges in structuring material for maximum visibility. A recent study by HubSpot and AirOps analyzed which content formats are most frequently cited in AI-generated responses, offering practical guidance for publishers and marketers aiming to appear in these answers.
The research found that the structure of a text, rather than its writing style, plays a decisive role in whether AI systems select it for citation. HubSpot refers to this approach as Answer Engine Optimization (AEO), while the broader industry sometimes uses Generative Engine Optimization (GEO), though the latter can cause confusion with geo-targeting terminology. Regardless of the label, marketers worldwide are working to decode how large language models (LLMs) choose and present content, and what this means for content marketing strategies.
One key recommendation is to use question-based headlines that mirror the queries users might ask an AI. For example, instead of a generic headline like “Benefits of a heat pump,” HubSpot suggests phrasing it as “What are the benefits of a heat pump?” The study found that such question headlines are cited by AI systems about 2.8 times more often than traditional ones. However, some critics warn that this approach could make headlines less distinctive and more interchangeable across sites.
Another effective tactic is placing a concise answer at the very start of a section, often called a TL;DR block. This allows both readers and AI models to quickly grasp the main point before diving into supporting details. While this format increases utility for time-pressed readers and makes it easier for AI to extract key information, it can also risk oversimplifying complex topics if overused.
Classic question-and-answer blocks are also recommended. Each common user question should have its own heading and a clear, direct answer. This structure, reminiscent of FAQ pages, now appears within longer articles and helps AI systems quote content more easily. The downside is that such articles may feel fragmented or lose narrative flow.
Definitions should be highlighted in separate boxes, with brief explanations of two to three sentences. These are easily recognized and extracted by AI, and help readers quickly understand key terms. However, there is a risk of oversimplification when dealing with nuanced subjects.
For comparisons, HubSpot advises using tables instead of narrative text. Tables make differences between products, methods, or providers more immediately clear, both for readers and AI. Yet, tables are less suited for nuanced analysis or subjective evaluation.
Step-by-step guides, rankings, and checklists should be formatted as numbered lists. According to HubSpot, these are among the most frequently cited formats by AI. Lists help readers scan for information and allow AI to extract individual points, but forcing content into list form can sometimes feel artificial.
Each paragraph should be self-contained, answering a single question and making sense without reference to other sections. Phrases like “as mentioned above” or “this method” should be avoided, as they hinder AI’s ability to quote paragraphs in isolation. This style is less compatible with traditional essays or narrative journalism.
Short, clear sentences with the main point at the beginning are preferred. This improves readability and helps AI systems process content more efficiently. Literary or complex journalistic styles with intricate sentence structures are less likely to be favored by AI.
HubSpot also recommends building topic clusters rather than relying on standalone articles. A foundational piece should be supported by glossaries, specialized articles, and case studies, all interlinked. This approach boosts a site’s topical authority but requires more editorial resources to maintain comprehensive knowledge areas.
Finally, the use of structured data, such as Schema.org markups like “Article,” “FAQPage,” “Person,” or “Organization,” is advised. These make content machine-readable for both search engines and AI systems, increasing the likelihood of accurate citation. However, this requires careful technical implementation and ongoing maintenance.
These recommendations reflect a shift from traditional SEO toward optimizing for AI-driven search and answer engines. While many of these formats enhance clarity and accessibility, some experts question whether widespread adoption could erode the individuality of online content. Still, for those seeking to appear in AI-generated answers, these structural strategies are becoming increasingly important. Recent research has also highlighted how AI-generated answers can reduce publisher traffic, as seen in this analysis of user behavior after receiving AI responses.
HubSpot, founded in 2006 and headquartered in Cambridge, Massachusetts, is a leading provider of inbound marketing and sales software. As of 2025, the company reported over 7,400 employees and served more than 184,000 customers worldwide, reflecting its significant influence in the digital marketing and content optimization sector.
