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Searcherries Announces AI Search Stats Report

58.7% report that AI search has reduced or replaced their use of traditional search engines.

SACRAMENTO, CA, UNITED STATES, March 4, 2026 /EINPresswire.com/ — Searcherries today announced the release of its new report, “AI Search Statistics: Survey, Research & Trends,” examining how AI search tools are reshaping information-seeking habits—and how citations surface in AI-generated responses.

Key findings

78.0% of respondents use AI search multiple times per week, including 54.1% who use it daily.

58.7% say AI search has reduced or replaced their use of traditional search engines.

27.5% report they never open source links after receiving an AI answer.

The most common use cases are quick fact-checking (67.0%) and deep research/topic synthesis (52.3%).

The leading reason for choosing AI search is speed (68.8%), followed by personalized advice (40.4%).

What users do after receiving an AI answer

When asked what they do next, the most frequent response was opening one or two links (34.9%) to verify information or learn more. Another 17.4% said they cross-check results using traditional search, while 10.1% continue the interaction by asking follow-up questions. Smaller segments save or copy answers into notes (7.3%), and 27.5% say they do not click sources at all.

How citations appear in AI search results

The report also includes a citations analysis based on a dataset of 24,069 multi-turn sessions across 13 AI search models, covering 72 languages and more than 171,000 citations. In this dataset, 71.2% of answers included at least one citation, averaging 3.7 citations per answer, while roughly 29% contained none.

The analysis also highlights a pronounced “long-tail” effect: 64.3% of cited domains appeared only once, even as a small group of domains received a disproportionate share of citations.

Methodology

The U.S. survey polled 1,090 respondents in February 2026 and covered usage frequency, tasks, motivations, post-answer behavior, and the impact of AI search on traditional search habits. The citations analysis draws from a compiled dataset of multi-turn AI search sessions and the citations observed within AI-generated answers.

About Searcherries

Searcherries builds an AI visibility platform that helps brands measure and improve how they appear in AI-generated answers.

Linda Marriott
Searcherries
linda.m@searcherries.com
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