AI search volume vs Google search volume: what 600 real keywords show

A developer built a keyword research tool on Apify that adds AI search volume estimates, then compared 600 real keywords across US and French markets against Google search volume. For the median keyword, AI volume was 3.7% of Google volume in the US and 2.5% in France, and the data appears grouped by topic, so summing raw AI volumes overstates totals by 42% in the US unless variants are deduplicated. Keywords with AI Overviews in Google results showed a median AI share of 5.9% versus 2.3% for others.

AI-generated: an AI agent drafted this post from real runs of a keyword tool I built with it. All the numbers come from those runs, on 23 October 2026. Some searches now start in ChatGPT, Perplexity or Gemini instead of Google. SEO tools have started to estimate how often a keyword comes up there, which they call "AI search volume". I added it to my keyword tool this week, then looked at what it says for two real keyword sets: Each row has Google's average monthly searches over the last 12 months and DataForSEO's AI search volume for the last month. For the median keyword, AI volume was 3.7% of Google volume in the US and 2.5% in France. 19 US keywords had no AI volume at all. "running shoes for men", "mens running shoes" and "running shoes men" have different Google volumes: 33,100, 40,500 and 18,100. They have the same AI volume, 1,973, with the same 12-month history. The AI data seems to be grouped by topic. That is also why "on the run shoes" shows 79,303 AI searches against 4,400 Google searches: it shares its number with "on running shoes". This matters as soon as you add numbers up. Summing AI volume over the US list gives 268,544. Counting each shared series once gives 155,220, 42% less. In France the gap was about 10%. Group variants before you sum them: the core keyword field catches many of them, and grouping identical 12-month AI histories catches more. Keywords whose Google results show an AI Overview had a median AI share of 5.9% in the US. The other keywords had 2.3%. Each group held about 150 keywords. In France the gap was smaller: 3.4% against 2.5%, with only 50 keywords showing an AI Overview. In the US, the 66 keywords starting with "best", "how", "what", "why", "which", "is", "are", "can" or "do" had a median AI share of 6.2%. "running shoe brands" stands out, with 8,100 Google searches and 3,891 AI searches: 48%. Asking which brands are good is exactly the kind of question people put to an assistant. Searches for a product type or one brand's range often stay almost entirely on Google: | Keyword | | AI | AI share | |---|---|---|---| | neutral running shoes | 49,500 | 459 | 0.9% | | altra running shoes | 49,500 | 230 | 0.5% | | marathon racing shoes | 18,100 | 65 | 0.4% | | running sneakers for men | 18,100 | 31 | 0.2% | Two sets of 300 keywords in two niches are not a study, and AI volume is an estimate. Google's figure is a 12-month average while the AI figure is last month's, so seasonal keywords can tilt the ratio. Treat these numbers as directions, not facts. The rows come from Keyword Research API https://apify.com/gaelasao/keyword-research-api , an Apify Actor I built. It returns one row per keyword with: The US run used this input: { "mode": "ideas", "keywords": "running shoes" , "location": "US", "maxIdeas": 300 } It cost $0.61: 300 keywords at $0.002, plus $0.01 for the run. AI search volume is included. From an AI agent, connect https://mcp.apify.com/?tools=gaelasao/keyword-research-api OAuth in Claude, Cursor and VS Code , then ask: Get 300 keyword ideas for "running shoes" in the US with Google and AI search volume, and add a column with the AI share. How the tool is built, and what I learned along the way: Keyword research for AI agents: search volume, CPC and difficulty over MCP https://dev.to/gal gerard 5a39555b810e9/keyword-research-for-ai-agents-search-volume-cpc-and-difficulty-over-mcp-bdf .