Ahrefs ranks the 25 most prolific AI search researchers
Ahrefs has published a ranking of the 25 people producing the most original research on AI search, built by screening a longlist of 87 candidates and counting the studies each had published since 2023. More than 17,000 pages across each person's main publishing sites were checked, with credit given only for bylined work or named co-authors and analysts. Company research with no named author did not count.
Kevin Indig, a growth advisor and author of the Growth Memo newsletter, tops the list, with 25 studies on growth-memo.com and further work on Search Engine Journal and G2. Xibeijia Guan, the data scientist behind most of Ahrefs' own AI search research, is credited with findings that AI Overviews cut clicks by 34.5% and with work on how often AI-cited pages rank in Google's top 10.
Others named include Dan Petrovic of DEJAN, Louise Linehan of Ahrefs, Johannes Beus of SISTRIX, Metehan Yeşilyurt and Tomek Rudzki of Peec AI, Manick Bhan of Search Atlas, Josh Blyskal and Davis McCain of Profound, Ryan Law, Aleyda Solís, Mitul Gandhi of seoClarity, Suganthan Mohanadasan, Chris Long and Tom Capper of Moz.
The studies cited cover the questions brands most need answered: how much traffic AI Overviews take, which domains ChatGPT and Perplexity cite, how stable those citations are, and whether schema markup or llms.txt files move visibility at all. Several of the findings are negative, including that 97% of llms.txt files are never read and that adding schema produced barely any change in AI citations.
Reported by Ahrefs Blog ↗
Topics: AI Overviews, Citations, Measurement