How should I format headers for AI? Been told question-based H2s are the way but is that actually true?

I’ve tested this extensively. Here’s what the data shows.

The experiment:

200 articles across 3 months:

• 100 with question-based H2s
• 100 with statement-based H2s
• All other factors controlled

Results:

The insight:

Question headers do perform better, but not dramatically. The 7% difference is meaningful but not game-changing.

What mattered more:

1. Clarity - Clear headers of any style > confusing question headers
2. Query matching - Headers that match actual search queries
3. Hierarchy - Logical H2 → H3 nesting
4. Direct answers - Content following headers that directly answers

My recommendation:

Use question headers where natural, but don’t force it. Clarity and structure matter more than rigid format.

Adding research context to this discussion.

Why question headers help:

1. Query matching - AI systems match questions to similar questions
2. Clear intent signal - Tells AI exactly what the section answers
3. Extraction clues - AI knows the following text is “the answer”

What research shows about AI extraction:

AI systems identify answer-worthy content by looking for patterns:

• Question followed by direct statement
• “What is X” followed by “X is…”
• Clear definition structures

Question headers create these patterns naturally.

But clarity trumps format:

A clear statement header with a direct answer beats a confusing question header.

Good: “Common Implementation Challenges” Bad: “What About When Things Go Wrong With Your Implementation And You Need To Fix Them?”

The forced question is worse than the clear statement.

The rule:

Match natural language queries where possible. Prioritize clarity always.

Technical documentation perspective.

What works for technical content:

Question headers work for conceptual content:

• “What is [concept]?”
• “How does [feature] work?”
• “Why use [approach]?”

Statement headers work for procedural content:

• “Prerequisites”
• “Installation Steps”
• “Configuration Options”
• “API Reference”

Our testing results:

The pattern:

When users are asking “what/why/how” → question headers When users are following steps or looking up info → statement headers

AI citations by type:

• Conceptual content (question headers): 42% citation rate
• Procedural content (statement headers): 35% citation rate
• Reference content (statement headers): 18% citation rate

The content type matters more than header format.

Agency perspective from hundreds of client articles.

What we’ve standardized:

Not a rigid format, but principles:

Principle 1: First H2 should be a question

• “What is [topic]?”
• “How does [topic] work?”
• Sets up the foundational definition

Principle 2: Use mixed headers throughout

• Questions for answer-focused sections
• Statements for lists, overviews, examples

Principle 3: Match “People Also Ask”

• Research PAA for your topic
• Use exact or similar phrasing as H2s
• These are proven query patterns

Principle 4: Keep headers scannable

• 5-10 words typically
• Front-load important terms
• Avoid filler words

The template:

H2: What is [Topic]?
H2: Why [Topic] Matters
H2: How to [Action] with [Topic]
H2: [Topic] Best Practices
H2: Common [Topic] Mistakes
H2: [Topic] FAQ

This performs consistently well across clients.

Data analysis perspective.

What correlates with AI citation:

Analyzed 500 cited articles vs 500 non-cited articles.

Header characteristics of cited content:

• Average H2 length: 7.2 words
• Question-format H2s: 45% of all H2s
• H2s matching PAA: 62% overlap
• Logical H2→H3 hierarchy: 89%

Header characteristics of non-cited content:

• Average H2 length: 4.1 words
• Question-format H2s: 28% of all H2s
• H2s matching PAA: 31% overlap
• Logical hierarchy: 54%

The correlations:

The insight:

Matching PAA queries and maintaining logical hierarchy are stronger signals than question format alone.

My recommendation:

Research PAA, match those patterns, ensure logical structure.

AI-specific perspective.

How AI systems use headers:

1. Navigation - Understanding content structure
2. Topic identification - What each section covers
3. Answer extraction - Finding relevant sections to cite

What helps AI extract effectively:

• Clear section boundaries
• Descriptive header text
• Consistent hierarchy
• Headers that signal content type

Format matters less than you think because:

AI models are trained on diverse content. They understand various header styles. What they need is clarity about:

• What this section is about
• Where one topic ends and another begins
• Which section answers which question

The minimum viable header optimization:

1. Use H1 for main title
2. Use H2 for major sections
3. Use H3 for subsections
4. Make headers descriptive (not “Introduction” or “Part 1”)
5. Match natural query patterns where logical

Editorial perspective - balancing SEO and readability.

The tension:

SEO/AI optimization says: use question headers matching queries Readability says: use natural, varied headers that flow

How we balance:

1. Primary articles (pillar content): Lean toward question headers
2. Supporting content: Use natural headers
3. Always: Prioritize readability within SEO constraints

Reader experience matters:

If every header is a question, the content feels like an FAQ, not an article. That affects engagement, time on page, and ultimately… what readers share and link to.

Our hybrid approach:

• Start with question header (definition section)
• Mix questions and statements throughout
• End with FAQ section (all questions)

This serves both AI extraction and human reading.

The readability test:

Read your headers out loud. Do they sound natural? If they feel forced, they probably are.

Great practical advice from everyone. My conclusions:

The answer:

Question headers help (7% improvement) but clarity and structure matter more.

What I’m implementing:

1. First H2 = question - Sets up definition/core answer
2. Mix throughout - Natural blend of questions and statements
3. Match PAA patterns - Research actual queries people ask
4. Keep headers descriptive - 5-10 words, front-load key terms
5. Maintain hierarchy - Logical H2 → H3 nesting

What I’m NOT doing:

• Forcing every H2 into question format
• Using single-word or vague headers
• Ignoring readability for SEO

The template I’ll follow:

H2: What is [Topic]? (question)
H2: Key Benefits of [Topic] (statement)
H2: How do you [Action]? (question)
H2: [Topic] Best Practices (statement)
H2: FAQ (question section)

Next step:

Use Am I Cited to track which header formats correlate with better citations for our specific content.

Thanks everyone!