What kind of content is more likely to be surfaced by AI tools?

One evening, a graduate student sat in a café trying to finish a paper on climate change. She opened Perplexity AI and typed: “What are the leading causes of carbon emissions in cities?” Within seconds, she got a neatly structured answer citing recent articles from the International Energy Agency, Bloomberg, and MIT Technology Review. She scanned through, pulled the figures she needed, and closed her laptop.

It was striking how certain sources—those with up-to-date, well-structured, and authoritative content—were chosen by the system, while countless others covering the same topic never appeared. That moment explains why brands and publishers are rethinking how they create content. If an article can’t be easily cited by generative search tools, it risks being invisible to the people who now rely on them.

Why surfacing matters now

Generative tools like ChatGPT, Claude, Perplexity, and You.com are no longer niche. In 2024, Pew Research reported that one in three U.S. adults had used a generative search tool. By 2026, Gartner projects traditional search queries will fall by 25%, with users turning instead to AI assistants.

The challenge is that these assistants don’t show dozens of blue links. They synthesize answers and surface only a handful of sources. That means the content they pick gets disproportionate visibility and authority.

What AI tools look for

Researchers and industry analysts have begun to map out the factors that influence which content makes it into AI-generated answers.

• Clear, structured answers. Analytics Insight notes that Perplexity favors pages with concise definitions, bullet-pointed data, and headings phrased as questions.
• Authority signals. A 2023 arXiv study on Generative Engine Optimization (GEO) found that AI systems are more likely to reuse phrasing from authoritative, canonical sources.
• Freshness. Forbes highlighted that Perplexity reached a $1B valuation in early 2025 largely because users value its ability to pull in current references. If your article hasn’t been updated in years, it will likely be skipped.
• Technical accessibility. Search Engine Land stresses that schema markup, clean HTML, and crawlable site structures help ensure AI systems can ingest content.
• Trustworthy citations. The New York Times has reported that one of the biggest challenges in AI search is ensuring tools cite reliable sources. Pages that themselves cite strong references are more likely to be surfaced.

Types of content that perform well

Question-driven explainers

People query AI assistants the way they’d ask another person. That makes FAQ-style content and explainers highly referenceable. SEO.com has found that Perplexity often selects direct Q&A formats because they map neatly to how users phrase queries.

Data-rich reports

AI models look for specific statistics to strengthen answers. Industry surveys, original research, and case studies are attractive because they contain concrete numbers. McKinsey’s 2024 global AI adoption report is a frequent citation example in AI responses.

Up-to-date trend coverage

Tools like You.com and Perplexity refresh constantly, pulling in current developments. Timely posts—such as Forbes’ 2025 reporting on Perplexity’s valuation or MIT Technology Review’s coverage of AI search visibility—are far more likely to surface than evergreen articles without updates.

Authoritative think pieces

Opinionated, shallow posts are often skipped. But authoritative analysis backed with references—like articles in Bloomberg or the NYT—show up because they balance clarity with trustworthiness.

Structured guides

Step-by-step guides, how-tos, and structured advice pieces are attractive because they combine clarity with practical value. Digital Marketing Blueprint notes that schema-backed guides stand a higher chance of being cited.

Case studies

• MarketMuse and Monday.com: By reorganizing content into structured topic clusters, MarketMuse helped Monday.com increase organic traffic by 1,570%. That same clarity makes the content easier for AI assistants to surface.
• Perplexity’s rise: With its $1B valuation, Perplexity has become a case study in user demand for clear, current, citation-heavy content.
• Academic research: A 2024 arXiv paper showed that phrasing and structure influence whether AI models recommend certain products or pages. That insight is already guiding how companies frame their copy.

Where Contently makes the difference

Writing content that both engages readers and surfaces in AI tools is a tall order. It requires clarity, constant updating, authoritative sourcing, and technical precision. Many teams don’t have the resources to maintain that at scale.

Contently helps fill the gap. Its marketplace of 160,000+ vetted freelancers produces content that:

• Poses and answers real user questions
• Embeds authoritative sources to signal trust
• Is refreshed regularly with current data
• Retains brand storytelling while ensuring machine readability

This blend is what makes content both human-friendly and referenceable for AI tools.

Looking forward

As AI assistants become the first stop for answers, the kinds of content they surface will shape public knowledge and consumer behavior. Unlike Google, where dozens of results compete, these systems highlight only a few. That makes the prize higher—and the rules stricter.

Brands that focus on structured, updated, and authoritative content will find themselves repeatedly cited. Those that rely on outdated blogs or vague commentary will fall out of view. With partners like Contently, companies can build a steady pipeline of content designed not just for SEO, but for the next generation of search itself.

Conclusion

The question for content creators is no longer just how to rank on page one of Google. It’s how to write material that AI assistants will surface when asked for answers.

Content that is clear, structured around questions, rich in data, current, and supported by reliable citations is far more likely to be chosen. For companies, this means treating content as a living asset that needs constant care. With Contently’s support, that challenge becomes manageable—and the reward is visibility in the very places where people now turn first.

Sources

1. Pew Research – Generative search adoption
2. Gartner – Forecast of 25% decline in search volume
3. Analytics Insight – Perplexity ranking factors
4. arXiv – Generative Engine Optimization research (2023)
5. Forbes – Perplexity valuation
6. Search Engine Land – Technical optimization for AI search
7. New York Times – On AI search trust
8. MIT Technology Review – AI search visibility
9. SEO.com – How to appear in Perplexity answers
10. Digital Marketing Blueprint – Practical guide to Perplexity SEO
11. arXiv – Strategic text sequences (2024)
12. MarketMuse – Monday.com case study