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Audit13 min read

55 AI Search Statistics for Local Businesses in 2026

How often AI answers appear, who they cite, how fresh cited content has to be, and which optimization tactics the evidence actually supports — every figure traced to a named public study.

0%

Of local queries show an AI Overview

0%

Of consumers use AI for local recs

0%

Of AI citations are off-page sources

0%

Of llms.txt files never fetched

J
JadenFounder, Elev8 Operations
200+ contractor accounts managed13 min read · Updated 2026-07-25

Key Takeaways

  • AI Overviews now appear on 68% of local business-type queries, versus 39% for the traditional local pack (Whitespark, 2026).
  • 45% of consumers say they use ChatGPT or another generative AI tool for local business recommendations — up from 6% a year earlier (BrightLocal Local Consumer Review Survey 2026, n=1,002 US adults).
  • Roughly 77% of the sources cited in AI answers about a brand are off-page — directories, reviews, forums, video — not the brand's own website (Omniscient Digital analysis of 23,000+ citations).
  • Adding JSON-LD schema produced no measurable change in AI citations across 1,885 tracked pages, and none of the five major AI systems read JSON-LD when fetching a page live (Ahrefs, 2026).
  • 97% of published llms.txt files received zero requests in May 2026 across 137,210 domains (Ahrefs, 2026).

AI answers now sit above the results for most local searches. AI Overviews appear on 68% of local business-type queries against 39% for the local pack, 45% of consumers report using a generative AI tool to find local businesses, and roughly 77% of the sources those answers cite are off-page rather than the business's own website. The 55 statistics below are grouped by the decision each one should inform, and every figure names the study it came from.

How to read this page: each figure names the organization whose research produced it. Where a number reached us through an aggregator rather than the original report, the aggregator is named too. Nothing here is Elev8 proprietary data — we have no AI-citation dataset of our own and won't pretend otherwise. Statistics we could not trace to a named, checkable source were left off this page rather than rounded up.

How often do AI answers appear in local searches?

Prevalence is the first question and the one with the clearest data. AI answers are not an edge case in local search — they are the default surface for anything phrased as a question.

  • AI Overviews appear on 68% of local business-type queries — Whitespark, 2026 (reported via Search Engine Journal).
  • The traditional local pack appears on 39% of those same searches — a 29-point gap in favour of the AI answer — Whitespark, 2026.
  • 92% of informational local queries trigger an AI Overview — Whitespark, 2026.
  • 97% of hybrid-intent local searches — part question, part 'who does this near me' — trigger one — Whitespark, 2026.
  • Simple transactional local queries trigger AI Overviews least often and still favour the local pack — Whitespark, 2026.
  • Over 88% of all searches that trigger an AI Overview carry informational intent — Semrush, 2025.
  • Over 68% of the terms that trigger AI Overviews get 100 or fewer monthly searches — Semrush, 2025.
  • Google AI Overviews reach roughly 2 billion monthly users — Google, 2025 (cited by Semrush).
  • Across 10M+ tracked keywords in 2025, AI Overview prevalence rose from ~6.5% in January to a ~24.6% peak in July before settling near 15.7% in November — Semrush, 2025.

The 68% and 88% figures together explain a pattern contractors keep noticing: 'how much does a new roof cost' gets swallowed by an AI answer, while 'roofer near me' still returns a map pack and a phone number. Informational content is where the exposure is. Booking intent is where it is not — yet.

Are homeowners actually using AI assistants to find contractors?

Prevalence in the results page is one thing; consumer behaviour is another. The strongest data point here is BrightLocal's annual survey, which asks US adults directly rather than inferring from traffic.

  • 45% of consumers say they use ChatGPT or other generative AI tools for local business recommendations — BrightLocal Local Consumer Review Survey 2026 (n=1,002 US adults).
  • That is up from 6% in the prior year's survey — a 7.5x increase in twelve months — BrightLocal, 2026.
  • 97% of consumers read online reviews for local businesses — BrightLocal, 2026.
  • 41% now say they 'always' read reviews when browsing for a business, up from 29% — BrightLocal, 2026.
  • ChatGPT reports roughly 700 million weekly active users — OpenAI, 2025 (cited by Semrush).
  • Roughly half of ChatGPT's cited links point to business and service websites rather than publishers — Semrush, 2025.

What does AI search traffic do once it lands on a site?

The volume of clicks coming out of AI answers is small. The quality of those clicks is not — which is the most consistently repeated finding across 2025–2026 measurement work.

  • The average AI-search visitor is worth 4.4x more than a traditional organic search visitor — Semrush, 2025.
  • AI referral visits show a 27% lower bounce rate than non-AI traffic on retail sites — Adobe, 2025.
  • AI referral visits run 38% longer and involve more page views — Adobe, 2025.
  • ChatGPT users click an average of 1.4 external links per visit, against 0.6 from a Google session — Momentic, 2025.
  • Only about 19% of users click through to the sources cited in an AI Overview — Exploding Topics, 2025.
  • Being featured as an AI Overview source raised click-through rate from 0.6% to 1.08% — Seer Interactive, 2024 (cited by Semrush).

Read those two clusters together before drawing a conclusion. Fewer people click, but the ones who do arrive further along. For a contractor that maps onto a real pattern: fewer casual readers on a cost guide, roughly the same number of people who actually want a quote.

Which sources do AI answers actually cite?

This is the statistic set that should reshape a local marketing budget. Your own website is a minority of the citation surface for questions about your own business.

  • Roughly 77% of citations on branded queries come from off-page sources rather than the brand's own site — Omniscient Digital, analysis of 23,000+ citations (reported via Search Engine Journal).
  • Only about 23% of citations on branded queries are the brand's own content — Omniscient Digital.
  • Reddit accounts for about 21% of AI Overview citations — Averi.ai research (reported via Search Engine Journal).
  • YouTube accounts for about 18.8% of citations in the same analysis — Averi.ai.
Surface
What it leans on most
What a local business controls
Google AI Overviews
The regular Search index, plus Business Profile and review data on local intent
Ranking pages, profile completeness, review velocity
Google AI Mode
Same index, longer multi-step reasoning chains
Same, plus depth of topical coverage
ChatGPT search
Live web fetch; ~50% of cited links are business or service sites
Whether pages render without JavaScript; clear on-page facts
Perplexity
Live web fetch with heavy forum and review weighting
Third-party presence — Reddit, directories, reviews
Local pack / Maps
Proximity, Business Profile signals, reviews
Profile, reviews, NAP consistency

How fresh does content have to be to get cited?

Freshness is one of the few levers where independent measurements agree, and it is cheap to act on.

  • AI-cited content is 25.7% fresher on average than the content ranking in classic Google organic results — Ahrefs analysis of 17 million citations.
  • ChatGPT showed the strongest recency preference of the engines measured — Ahrefs, 2026.
  • 74% of consumers specifically seek out reviews written in the last three months — BrightLocal, 2026.
  • Engagement and behavioural signals — recent posts, photos, review cadence — continue to climb in importance on Whitespark's 2026 practitioner panel — Whitespark, 2026.

Freshness means the substance changed, not the timestamp. Rewriting a cost guide with current numbers is a refresh. Editing dateModified on unchanged content is not, and it is the single most common way businesses waste the freshness signal.

What content features are shown to increase citation?

The academic baseline here is the Princeton and Georgia Tech paper that named the field. It is worth quoting precisely, because the number gets inflated in secondary coverage.

  • Optimizing content along the paper's dimensions boosted visibility in generative engine responses by up to 40% — Aggarwal et al., 'GEO: Generative Engine Optimization', KDD 2024.
  • The tactics that produced those gains were adding authoritative citations, direct quotations, and relevant statistics — Aggarwal et al., 2024.
  • Keyword stuffing was among the tactics the same paper found ineffective — Aggarwal et al., 2024.

Two practices are widely recommended on top of that and are worth adopting because they cost nothing, though we have not found a controlled study behind either: answering the question directly in the opening paragraph, and giving each section a heading phrased the way someone would actually ask it. This page is built that way. Treat them as reasonable defaults, not as measured effects.

Does schema markup or llms.txt actually move the needle?

Two tactics get sold hard to local businesses. Both now have direct experimental evidence against them, worth quoting precisely rather than relying on either the hype or the backlash.

  • Ahrefs analysed 6 million URLs and tracked 1,885 pages that added JSON-LD between August 2025 and March 2026 — Ahrefs, 2026.
  • Adding JSON-LD produced no measurable change in citations from Google AI Overviews, Google AI Mode, or ChatGPT in the 30 days afterwards — Ahrefs, 2026.
  • AI-cited pages were nearly 3x more likely to already carry JSON-LD — a correlation Ahrefs attributes to better-maintained sites, not to the markup itself — Ahrefs, 2026.
  • When Ahrefs tested whether ChatGPT, Claude, Perplexity, Gemini, and Google AI Mode read schema on live fetch, none of them did — all five extracted only visible HTML — Ahrefs, 2026.
  • Ahrefs checked 137,210 domains with traffic in May 2026; 38,360 of them (28%) published a valid llms.txt — Ahrefs, 2026.
  • 97% of those llms.txt files received zero requests that month — nothing fetched them at all — Ahrefs, 2026.
  • 96% of the requests that did arrive came from automated crawlers, and no AI bot proactively looked for the file where it did not exist — Ahrefs, 2026.
  • Google has confirmed Search does not use llms.txt, and that AI Overviews and AI Mode draw on the same index as classic ranking — Google, 2026.

This is not an argument for removing schema. Correct structured data still earns rich results, still describes your business entity to Google's own systems, and costs nothing once implemented. It is an argument against paying a premium for 'AI schema', and against believing an llms.txt file bought you visibility.

What do the local ranking factor weights look like in 2026?

Whitespark's annual survey of local search practitioners is the closest thing the field has to a consensus estimate. The 2026 edition's headline is that local and AI signals have converged.

  • Whitespark's 2026 Local Search Ranking Factors report draws on 47 local search practitioners — Whitespark, 2026.
  • Proximity to the searcher accounts for roughly 55% of the local ranking outcome — Whitespark, 2026.
  • Google Business Profile signals account for roughly 32% of the controllable weight — Whitespark, 2026.
  • On-page signals account for roughly 19% — Whitespark, 2026.
  • Review signals account for 16–20%, with velocity, response rate, and total count weighted most heavily — Whitespark, 2026.
  • Social engagement was confirmed as a measurable ranking factor for the first time in the 2026 edition — Whitespark, 2026.
  • Whitespark's 2026 conclusion is that local search signals and AI search signals have effectively merged — the same inputs drive visibility across Google, Maps, ChatGPT, and Perplexity — Whitespark, 2026.

What does all this mean for a contractor's marketing budget?

The honest synthesis: the highest-leverage work is off your website, the on-site work that matters is content and entity accuracy rather than markup, and paid channels are unaffected by any of it.

  • Roughly 77% of the citation surface is off-page, so reviews, directory accuracy, and third-party presence outrank on-site tinkering — Omniscient Digital.
  • 47% of consumers will not use a business with fewer than 20 reviews — BrightLocal, 2026.
  • 31% will only use a business rated 4.5 stars or higher — BrightLocal, 2026.
  • 80% say they are more likely to use a business that responds to all its reviews — BrightLocal, 2026.
  • 19% now expect a response to their review the same day, up from 6% a year earlier — BrightLocal, 2026.
  • Paid channels sit outside the AI answer entirely: Home & Home Improvement lead campaigns on Meta averaged a $41.26 cost per lead — WordStream, Apr 2024 – Jun 2025.
  • The same category on Google Search averaged a $90.92 cost per lead — WordStream, Apr 2025 – Mar 2026.
  • For context, the all-industry averages in those same datasets were $27.66 on Meta lead campaigns and $66.69 on Google Search — WordStream.

If you take one implication off this page: get past 20 reviews at 4.5 stars, reply to all of them within a day, keep your listings identical everywhere, and publish honest cost content that answers the question in its first paragraph. Every study cited here supports that sequence. None of them supports buying 'AI schema'.

Put these numbers to work

Sources

The public studies behind the figures on this page, with what each one was used for. Last verified 2026-07-25.

  1. 1
    AhrefsWe Analyzed 137K Sites: 97% of llms.txt Files Never Get Read

    2026 · 137,210 domains with traffic; May 2026 server-log and bot analytics. Source for every llms.txt figure on this page.

  2. 2
    AhrefsWe Tracked 1,885 Pages Adding Schema. AI Citations Didn't Move.

    2026 · 6M URLs analysed; 1,885 pages adding JSON-LD Aug 2025 – Mar 2026. Source for the schema findings and the live-fetch test across five AI systems.

  3. 3
    BrightLocalLocal Consumer Review Survey 2026

    2026 · Representative SurveyMonkey panel of 1,002 US adult consumers. Source for all consumer review and AI-adoption percentages.

  4. 4
    WhitesparkLocal Search Ranking Factors 2026

    2026 · Survey of 47 local search practitioners. Source for the ranking-factor weights and the local/AI signal convergence finding.

  5. 5
    Search Engine JournalAI Overviews Now Answer Most Local Searches — How To Get Your Business Cited

    2026. Reporting vehicle for the Whitespark prevalence data, the Averi.ai citation shares, and the Omniscient Digital off-page citation split.

  6. 6
    Semrush26 AI SEO Statistics for 2026 + Insights They Reveal

    2026. Source for AI Overview intent mix and AI visitor value, and the vehicle for the Google, OpenAI, Adobe, Momentic, Seer Interactive and Exploding Topics figures cited through it.

  7. 7
    Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan & DeshpandeGEO: Generative Engine Optimization (KDD 2024)

    2024 · GEO-bench, a large-scale benchmark of user queries across multiple domains. Peer-reviewed origin of the 'up to 40% visibility' figure and the citations/quotations/statistics finding.

  8. 8
    WordStreamFacebook Ads Benchmarks: New Data by Industry

    Apr 2024 – Jun 2025 · 554 US traffic campaigns and 726 US lead campaigns. Source for the Meta Home & Home Improvement and all-industry cost-per-lead figures.

  9. 9
    WordStreamGoogle Ads Benchmarks 2026: Competitive Data for Every Industry

    Apr 2025 – Mar 2026 · 13,474 US-based search advertising campaigns. Source for the Google Search Home & Home Improvement and all-industry cost-per-lead figures.

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13 min read · Updated 2026-07-25

Frequent Questions. Short Answers.

68% of local business-type queries return an AI Overview, against 39% that show the traditional local pack, according to Whitespark's 2026 analysis. The rate is higher for informational phrasing — 92% of informational local queries and 97% of hybrid-intent searches trigger one — and lowest for simple transactional queries, which still favour the map pack.

45% of US consumers report using ChatGPT or another generative AI tool for local business recommendations, according to BrightLocal's Local Consumer Review Survey 2026, based on a representative panel of 1,002 US adults. The prior year's figure was 6%, making this one of the fastest behavioural shifts that survey has recorded.

Mostly other sites. Omniscient Digital's analysis of more than 23,000 citations found roughly 77% of the sources cited on branded queries were off-page — directories, review platforms, forums, video — and only about 23% were the brand's own content. Your site matters, but it is a minority of what an assistant reads about you.

Community and video platforms dominate. Reddit holds around 21% of AI Overview citations and YouTube around 18.8% in Averi.ai's research, reported by Search Engine Journal. For a contractor that means a handful of genuine Reddit answers and a few real job-site videos can outweigh months of on-site tinkering.

The direct evidence says no. Ahrefs tracked 1,885 pages that added JSON-LD between August 2025 and March 2026 and found no measurable citation change in the following 30 days on Google AI Overviews, AI Mode, or ChatGPT. When they tested whether ChatGPT, Claude, Perplexity, Gemini, and Google AI Mode read schema on a live fetch, none did — all five extracted only visible HTML.

Confounding. Ahrefs found AI-cited pages were nearly 3x more likely to carry JSON-LD, but attributes that to the kind of site that implements schema: better maintained, more technically competent, publishing stronger content and earning more links. The markup is a symptom of quality rather than the cause of the citation.

Yes, for reasons other than AI citations. Correct schema still drives rich results in classic search, still describes your business entity to Google's systems, and costs nothing once it is in place. What the evidence rules out is paying a premium for AI-specific markup or expecting schema alone to change how often assistants name you.

There is no evidence it does. Ahrefs checked 137,210 domains with traffic in May 2026: 38,360 had published a valid llms.txt, and 97% of those files received zero requests that month. 96% of the few requests that did arrive came from automated crawlers, and no AI bot went looking for the file where it was absent. Google has separately confirmed Search does not use it.

Fresher than what ranks organically. Ahrefs' analysis of 17 million citations found AI-cited content averages 25.7% fresher than the content ranking in classic Google results, with ChatGPT showing the strongest recency preference. The practical read is to genuinely revise your highest-value pages on a schedule — substantive updates, not date changes.

Little, but it converts. Roughly 19% of users click through to sources cited in an AI Overview (Exploding Topics, 2025), and Seer Interactive measured being cited as lifting click-through from 0.6% to 1.08%. On the other side, Semrush puts the average AI-search visitor at 4.4x the value of a traditional organic visitor, and Adobe found AI referral visits bounce 27% less and run 38% longer.

The peer-reviewed answer comes from Aggarwal et al., 'GEO: Generative Engine Optimization' (KDD 2024), which reported visibility gains of up to 40% from adding authoritative citations, direct quotations, and relevant statistics — and found keyword stuffing ineffective. Answer-first paragraphs and question-shaped headings are widely recommended on top of that, but we have not found a controlled study behind either, so treat them as sensible defaults rather than measured effects.

They are appearing above it far more often, not replacing it. The 68% versus 39% gap Whitespark reports means AI answers now show on many queries where no local pack appears at all — mostly informational ones. Transactional 'near me' searches still resolve to a map, a rating, and a phone number, which is where booked jobs come from.

Twenty is the practical floor. BrightLocal's 2026 survey found 47% of consumers will not use a business with fewer than 20 reviews and 31% will only use one rated 4.5 stars or higher. Since review platforms are a large share of the off-page citation surface, the threshold that governs consumer trust also governs what an assistant finds when it looks you up.

It matters for both consumers and ranking. 80% of consumers say they are more likely to use a business that responds to all its reviews, and 19% now expect a same-day response — up from 6% the previous year (BrightLocal, 2026). Whitespark's 2026 panel weights response rate alongside velocity and count within the 16–20% of local ranking attributed to review signals.

Fixing the off-page surface, because that is where roughly 77% of citations come from. In practice: get past 20 reviews at 4.5+ stars, reply to all of them quickly, and make your name, address, phone, hours, and service area identical across every listing. Conflicting listing data is the most common reason an assistant hedges or names a competitor instead.

No. Every figure on this page comes from a named third-party study, listed with a link in the Sources section below. We manage paid campaigns and hold no AI-citation dataset of our own. Statistics we could not trace back to a named, checkable source were left off the page rather than included with vague attribution.

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