AI search statistics 2026: original research with source context

Key statistics at a glance

These figures describe different questions and populations. They are not interchangeable estimates, and a reported association does not prove that AI alone caused a commercial outcome.

How buyers use AI during a purchase

The AI Buyer Journey Report 2026 surveyed 770 respondents in Q2 2026: 350 B2B buyers and 420 consumers, with 60% based in the US and 40% in the UK.

The report records AI use during purchasing among 91% of the B2B group and 84% of the consumer group. Among B2B AI users, 90% said they researched vendors before speaking with a company. These findings point to activity before a sales conversation, within the survey's defined sample.

For consumer product research, 59% reported using AI as a first step for recommendations. The report also states that 56% of B2B respondents asked AI for contact details or links and used them directly. These are survey responses, not a logged measure of every visit or transaction.

The practical implication is to examine the information prospects encounter before they make contact. It does not follow that every company should move the same budget or that every AI mention produces qualified demand.

Trust and reported influence

The buyer study reports that 97% trusted information provided by AI platforms, 85% had changed their mind because of an AI recommendation, and 94% would stop considering a company if AI presented negative information about it.

Keep the wording attached to the question. A stated hypothetical response is different from an observed purchase, and trust in information does not mean every AI statement is accurate. These findings should motivate checking the public account of the business rather than repeating unsupported AI claims.

For marketing teams, the useful task is to inspect important descriptions and evidence. Are the products, service areas, qualifications, limitations, and comparisons correct? A positive tone can still conceal a material factual error.

What AI gets wrong about businesses

The AI Business Accuracy Report 2026 evaluated 250 companies across 20 industries using ChatGPT, Claude, Gemini, and Perplexity. It is a company evaluation, not a consumer survey.

The report states that 46% received consistent recommendations across all four platforms. It also records important product or service omissions in 28% of responses and says local businesses were four times as likely to be misunderstood as nationally recognized brands under its study definitions.

Source observations included company websites in 40% of responses and Reddit in 35% of recommendation responses. Those figures describe the tested material. They are not weights in a universal algorithm or instructions to prioritize one channel for every business.

Use the study as a reason to maintain accurate facts and examine cross-platform differences. Do not transform an observational comparison into a claim that a particular optimization activity caused an outcome.

Legal services: discovery, trust, and shortlists

The AI Legal Consumer Report 2026 surveyed 871 US adults in Q2 2026 who had recently used legal services or expected to do so soon.

It reports that 96% trusted AI to recommend law firms, 62% used AI during discovery, and 84% would not trust a firm that did not appear in AI results. Legal consumers using AI considered an average of 2.3 firms, as defined by the report.

These are findings about that sample, not a statement about all US adults or every legal practice. A law firm's response should focus on accurate practice, jurisdiction, professional, and office information with appropriate legal review. See GEO and AEO for law firms.

SaaS: AI can influence renewal as well as discovery

The AI SaaS Churn Report 2026 surveyed 804 B2B software decision-makers in the US and UK. It examines renewal and cancellation decisions, a different context from initial purchase discovery.

The report states that 67% used AI during a renewal or cancellation decision, 49% changed a renewal decision because of information provided by AI, and 23% cancelled or downgraded a product after consulting AI. It also reports that 88% never told the incumbent vendor AI influenced the decision.

Do not turn these survey findings into an exact forecast of churn for a particular vendor. They show why accurate public pricing, features, integration details, and comparisons deserve attention across the customer lifecycle. Read the full report for the question context and methodology.

Methodology and sources

This roundup summarizes separate studies. The buyer and legal reports identify Q2 2026 collection periods. The accuracy and SaaS reports are labeled 2026, but an exact fieldwork period is not established in this summary. Do not replace that uncertainty with the date this page was checked.

The reported survey sample counts are 770, 871, 804, and 198. Their sum is 2,643, but the studies have different audiences and may not represent unique individuals across reports. No pooled percentage is calculated here. The 250-company accuracy study remains separate.

Reported findings should be read alongside the original wording, sample selection, and limitations. Survey responses are not the same as behavioral click data. A study of answer accuracy is not an estimate of consumer adoption. A case study is not a population survey.

Sources checked November 11, 2026 where accessible. The remaining figures can be traced through the original reports linked in each section.

How to cite these statistics

Name the original report, the relevant population, the study period where stated, the finding, and the source link. Cite the original study for a statistic rather than imply this roundup collected a new combined sample.

Suggested citation format: LLM Listed, AI Buyer Journey Report 2026, Q2 2026, 770 US and UK respondents. Then include the specific finding and report URL.

For the accuracy study, write 250 companies evaluated across 20 industries, not 250 respondents. For an exact claim, preserve the segment or denominator specified in the original report. Do not remove a limitation merely to make a headline shorter.

Journalists and researchers can contact hello@llmlisted.com for source questions. Use the full-report links above for methodology. A downloadable roundup should preserve the same source and sample notes rather than separate figures from their context.

A useful check before quoting a figure

Ask what the number counts, who was included, when the information was collected, and which question produced it. Confirm whether it is a reported behavior, a hypothetical intention, or an observed answer outcome. If the source does not establish a detail, leave that detail uncertain rather than infer it from the headline.

What should businesses do with the evidence?

Use the findings to identify a question worth investigating. A business with material factual errors may need information maintenance first. A business missing from a relevant shortlist may need a deeper examination of buyer fit, sources, and accessibility.

Our AI search guide explains a practical process. The zero-click search article distinguishes survey influence from observed clicks. Neither replaces the need for evidence about your own business.