What 5,771 AI-assisted blog posts actually did in Google

Most debates about AI content are opinions. This one is 1.3 million days of Search Console data.

We followed 5,771 AI-assisted blog articles across dozens of brands in 11 industries from June 2025 to October 2026. Each article was measured from its own publish date. Every comparison below ranks an article against the same brand's other articles, so a strong domain never makes a format look good.

Key findings

• The median article earned 1 click in its first 90 days. 49% earned none.
• The top 10% of articles took 73% of all clicks. The top 1% took 22%.
• Decision content wins. Rules explainers, best-of lists and "X vs Y" comparisons became a brand's top performers most often. Case studies and "why choose us" posts almost never did.
• Keyword difficulty mattered; search volume did not. KD under 10 was the only band with an edge.
• Articles win topics, not keywords. 74% of an article's clicks came from searches it never targeted.
• One topic cluster usually carried 37% of a brand's clicks.

Which formats win

Share of each format that landed in its brand's top 20% by clicks. Chance is 20%.

Format	Became a top-20% article
Rules, regulations and schemes	32%
Best-of / ranked lists	30%
X vs Y comparisons	27%
A specific problem and its fix	26%
Cost and pricing breakdowns	26%
How-to guides	17%
Explainers ("what is")	17%
Generic tips listicles	15%
Case studies	9%
"Why choose us" posts	3%

54% of all the articles were explainers, how-tos and tips lists. Most of the budget went to the median formats.

Keywords: difficulty, not volume

Planned keyword difficulty	Became a top-20% article
0 to 9	26%
10 and above	14 to 19%

Planned search volume had no measurable relationship with how an article did against its siblings. Only 14% of articles ranked for their exact target keyword, and 74% of clicks came from close variants. The focus keyword is a label, not the prize.

Core updates hit generic content hardest

On the same set of established articles, the May 2026 core update cut clicks by 27%. Buying guides lost nothing, cost pages lost 13% and rules explainers 15%. Explainers and how-tos lost 36 to 37%. The December 2025 core update went the other way: +69%.

AI tools are already searching these pages

Some queries in these brands' Search Console data are full prompts from AI tools, in a fixed template: "context: location: … do not include location references in your response. question: …". We found 119 of them across 84 articles, at an average position of 3.8, with zero clicks. They are the literal questions buyers ask AI, and they cluster on comparison and buying-guide pages. Filter your Search Console queries for context: or for queries over 10 words to see yours.

What to do with it

1. Make decision content the core of the calendar: comparisons, best-of lists, cost breakdowns, rules explainers, specific fixes.
2. Pick low-difficulty, specific topics over high-volume head terms.
3. Give each close variant of the question its own section. That is where most clicks come from.
4. Review clusters at 90 days and put new articles into the winners.
5. Report clicks, not impressions (see the note below).

CiteCycle tracks the questions your buyers ask AI, pulls the AI prompts out of your Search Console, and ranks what to write next using these findings.

Method and limits

• Articles: AI-assisted posts with Search Console tracking, published June 2025 to September 2026 across dozens of brands. Articles were drafted with AI; some were revised after human feedback. Brand names are withheld.
• Windows: clicks over fixed windows from each article's publish date. An article counts only if its whole window was observed. Brands with tracking breaks are cut at the break, and articles that never got an impression are excluded.
• Formats: each title was classified into one of 16 formats from the title, target keyword and brand context.
• Google confirmed that Search Console misreported impressions, CTR and average position from 13 May 2025 to 27 April 2026. Clicks were unaffected, so every finding here is click-based.
• We publish aggregates only.