"Create great content" is useless advice when your audience is an AI model deciding which brands to recommend. Pages optimized for Google - keyword density, internal linking, featured snippets - don't automatically translate to AI recommendations.
Based on analyzing thousands of AI citations, here's what content actually gets recommended, and what doesn't.
What gets cited
Original data
Nothing beats proprietary data. When AI needs to support a claim, it looks for concrete numbers it can reference. "We analyzed 10,000 responses and found..." is citable. "We believe our product is the best" is not.
Action: Conduct one original research piece per quarter. Survey your customers, analyze your product data, or benchmark your industry. Publish with clear, quotable statistics.
Direct answers to specific questions
When someone asks "What is X?" or "Best Y for Z?", AI needs a source that answers clearly and specifically. Not a 500-word introduction before the answer. Not hedging language. A direct answer in the first paragraph, with supporting detail below.
Instead of: "When it comes to project management, there are many factors to consider..." Write: "The best project management tools for remote teams are Asana, Linear, and Monday.com. Here's why..."
Honest comparison content
Comparison queries ("X vs Y", "best X for Y") are high-intent, and AI handles them by recommending specific brands. If you don't provide comparison context, AI relies on third-party sources that may not position you favorably.
Action: Create balanced comparisons. Acknowledge competitor strengths while highlighting your differentiation. AI can detect one-sided sales content and ignores it.
Expert-attributed content
Content with named expert perspectives gets weighted more heavily. "According to [Name], [Company]..." provides credibility AI models recognize.
Action: Build your team's thought leadership. Get quoted in media, speak at events, publish bylined articles.
What doesn't work
Keyword-stuffed SEO content - AI detects content optimized purely for search engines and ignores it.
Vague, hedging language - "It depends" and "results may vary" without specifics doesn't help AI make recommendations.
Pure sales content - "Why We're the Best" won't get cited. AI looks for informative content, not ads.
Outdated information - AI platforms with real-time search deprioritize stale content. Keep dates and statistics current.
Anonymous content - Generic "content marketing" without author attribution lacks the authority signals AI looks for.
Structure matters as much as substance
Question-based headers - When your H2 matches what users ask, you're more likely to be cited. "How Much Does CRM Software Cost?" beats "Pricing Overview."
Quotable statistics - Give AI specific numbers: "67% of buyers...", "brands see an average 34% improvement..." AI loves data it can reference.
Clear definitions - Start explanatory content with a bolded term and direct definition. This format is citation-friendly.
It's not just your blog
AI evaluates your brand across the entire internet, not just your website:
- Reviews (G2, Capterra, Trustpilot) - Heavily influence recommendations. Volume, recency, and sentiment all matter.
- Media coverage - Even unlinked mentions in reputable publications build brand authority.
- Community discussions - Reddit, forums, organic user advocacy. You can't fake this.
- Expert content - Guest posts, contributed articles, podcast appearances extend your brand footprint.
Your website is one input among many. For some brands, it's not even the most influential one.
Measuring what works
Traditional metrics (traffic, rankings) don't capture AI content success. Track:
- Citation rate - What percentage of AI queries cite your content?
- Recommendation position - When AI recommends you, are you first or last?
- Content attribution - Which specific pieces get cited? Double down on those formats.
- Competitive share - How does your citation rate compare to competitors?
The shift from SEO-first to AI-aware content is already underway. The brands that adapt now will own their category in AI recommendations.
AEOscope tracks which content AI actually cites across every major platform - so you know what's working.
