Content Length: SEO and AI Disagree

The average top-ranking blog post is 1,447 words. The average page cited in AI Overviews is 1,282 words. The

By Conor Healy

June 11, 2026

The average top-ranking blog post is 1,447 words. The average page cited in AI Overviews is 1,282 words. The optimal length for AI recommendations is 3,000 words.

Three numbers. Three different systems. Three different answers to the same question.

The Scientific Institute for Generative Intelligence (SIGI) studies how large language models evaluate and recommend content. Their research on content depth sits alongside years of SEO ranking studies and newer data on AI Overview citations. The rules that worked for Google don’t translate to AI.

SEO Rewards Length

Backlinko’s analysis of top-ranking content found an average of 1,447 words. Semrush recommends 1,500 to 2,500 words for competitive keywords. Pillar pages push into the 3,000 to 5,000 range.

The logic holds up. Longer content allows more keywords, more internal links, more semantic coverage. Posts over 2,000 words earn more backlinks. Google’s algorithm treats length as a proxy for depth, and depth accumulates ranking signals.

For traditional search, “write the most comprehensive piece on the topic” remains solid advice.

AI Overviews Reward Brevity

Ahrefs analysed 174,000 pages cited in AI Overviews. The results break from SEO orthodoxy.

Pages cited averaged 1,282 words. More than half of all citations went to pages under 1,000 words. The correlation between word count and citation position was 0.04. Essentially zero.

AI Overviews extract answers. A 3,000-word guide may contain the answer somewhere in paragraph twelve, but a 600-word page that answers the question in sentence one gets cited instead. Precision beats comprehensiveness when the machine is summarising.

AI Recommendations Have a Ceiling

SIGI’s research found something different again.

For AI recommendation language (how models describe and endorse content when users ask questions directly) the sweet spot sits around 3,000 words. Content at this length triggered the strongest positive signals.

But at 5,000 words, a negative inversion occurs. AI sentiment declines. The models appear to treat excessive length as a signal of padding or diminished focus. The pattern matches other SIGI findings: optimal ranges exist, and exceeding them backfires.

3,000 words appears to be the ceiling for AI recommendation value. Going longer helps traditional SEO but may hurt how AI systems talk about your content.

The Practical Split

Different content, different targets.

Standard blog posts: 1,500 words with direct answers in the first paragraph. This balances SEO requirements with AI extractability. Structure matters more than hitting a word count.

How-to guides: 1,700 to 2,500 words when the process is genuinely complex. SIGI’s data suggests staying below 3,000 unless depth is unavoidable.

Pillar pages: Traditionally 3,000 to 5,000 words for SEO dominance. But SIGI’s ceiling suggests diminishing returns past 3,000 for AI visibility. The extra length may win Google rankings while losing AI citations.

Landing pages: Concise. Neither SEO nor AI research supports padding conversion-focused pages. Clear and specific beats comprehensive.

Product descriptions: A few hundred words of genuine information. Filler hurts both systems.

Structure Beats Length

Word count is only part of the equation. How content is structured affects whether AI systems cite it at all.

Semrush’s research on AI citation patterns found that AI systems surface what’s easiest to parse, not necessarily what’s most comprehensive. A well-structured 800-word page can outperform a sprawling 2,500-word guide if the shorter page answers the question in the first paragraph.

The structural practices that improve AI citation:

Answer in the first 50 words. AI systems scan for fragments they can extract directly. Burying the answer in paragraph three means it may never get found. The same principle drove featured snippet optimisation for years. It now applies across ChatGPT, Perplexity, and AI Overviews simultaneously.

Keep paragraphs short. Research suggests 40 to 60 words per paragraph for optimal extractability. Each paragraph should contain one idea that can stand alone if pulled into a summary.

Use headings as questions. Headings framed as “What is X?” or “How does Y work?” mirror how users query AI systems. The paragraph immediately following becomes the extractable answer.

Update regularly. Seer Interactive found that 85% of AI Overview citations came from content published in the last two years. 44% came from 2025 alone. Freshness signals matter more for AI citation than for traditional SEO.

Add FAQ schema. FAQPage markup explicitly flags question-and-answer content for AI extraction. It remains the most direct path to appearing in AI Overviews for question-based queries.

None of this replaces depth. But depth without structure gets ignored. A 3,000-word article with answers buried in the middle loses to a 1,200-word article that leads with clarity.

Two Games, One Page

SEO and AI optimisation are diverging.

SEO rewards covering everything. AI rewards answering something. SEO benefits from length as a signal of authority. AI treats excessive length as noise.

A page can perform in both systems. Put the direct answer first for AI extraction. Add depth after for SEO signals. Stop before 3,000 words unless the topic demands it.

Longer stopped being automatically better the moment AI started choosing what to cite.