Study 01 · Global Digital Authority Benchmark Series · Great Britain 2026

Nearly 2 in 5 British business websites with an observable crawler policy block the AI crawlers they need

A structured benchmark of 754 publicly identifiable British business websites (commercial operating entities) across 10 industry groups, measuring which AI search crawlers can — and cannot — access them.

Author Douglas Lord
Research instrument PTODA C01 Crawler v1.2 — deterministic robots.txt scanner
Commercial operator AUTHORITY44™
Scan date 17 June 2026, BST
Sample 754 domains · 10 sectors · 536 with readable robots.txt policy
39%
of British business domains with a readable robots.txt file block at least one AI retrieval crawler

Of 536 domains whose crawler policy could be directly observed, 208 — 38.8% — block at least one crawler used by AI search systems to discover and cite content.

We separate observable AI-crawler policy from infrastructure non-response. A block declared in robots.txt is a policy decision; a 403, timeout or unscannable response is an access outcome, not evidence of crawler policy. These are reported separately below.

Of the blocked sites, 88.9% are broad access restrictions catching AI crawlers incidentally rather than AI-specific decisions.

Key findings

The numbers at a glance

Policy-layer figures are based on 536 domains whose robots.txt was successfully retrieved and parsed. A further 218 domains returned no observable policy (66 access-denied, 152 unscannable) and are reported separately in the Infrastructure layer section. They are not counted as open or blocked.

61.2%
Open to all AI crawlers
328 of 536 policy-observed sites, with no robots.txt restriction preventing AI search discovery
33.4%
Fully blocked to all AI crawlers
179 sites block all tested retrieval crawlers
5.4%
Partially blocked
29 sites block some crawlers but not all
88.9%
Broad blocks — not targeted at AI
185 of 208 blocked sites also block Googlebot, so the block is a broad restriction rather than an AI-specific decision
11.1%
Deliberate AI-only blocks
23 sites specifically blocked AI crawlers while keeping Googlebot accessible
21
AI crawlers tested
14 retrieval (Group A) and 7 training (Group B) user-agents, the harmonised series crawler set

The central finding: Most blocked businesses are not actively choosing to exclude AI search. They have broad access restrictions set years ago that are now inadvertently catching AI crawlers. This is a configuration problem, not a strategic decision.

Infrastructure layer

Access outcomes — not crawler policy

We separate observable AI-crawler policy from infrastructure non-response. A block in robots.txt is a policy decision. A 403, timeout or unscannable response is an access outcome, not evidence of crawler policy. These 218 domains are reported here and excluded from every policy-layer figure. Great Britain has the largest number of unscannable domains in the series, and the highest unscannable rate among the large-market volumes.

66
Access denied (HTTP 403/401/429)
8.8% of the 754 domains approached. The edge refused the robots.txt request, so no crawler policy could be observed. Not counted as open or blocked.
152
Unscannable
20.2% of domains approached, and 152 domains in absolute terms — the largest unscannable count in the series. No readable response through connection failure, timeout or 5xx error. No policy observable.
536
Policy observed
71.1% of domains approached returned a readable robots.txt. This is the denominator for all policy-layer findings on this page.

Why this matters: a domain that denies the crawler at the infrastructure layer has not expressed an AI-crawler policy — it has prevented one from being read. Treating such a response as “open” would overstate access; treating it as “blocked” would overstate restriction. Reporting it separately keeps the policy-layer figures based only on directly observed robots.txt behaviour.

The Great Britain signature: infrastructure non-response. Great Britain is the mirror image of the United States. Where the US actively denies the crawler at the edge, Great Britain simply does not respond. Its 152 unscannable domains (20.2%, and the largest such count in the series) returned no readable robots.txt through connection failure or timeout, and they carry no managed-WAF signature: of those domains, 148 of 152 sit behind no identifiable managed CDN. This is passive non-response, not deliberate mitigation. The unscannable domains are spread across mainstream sectors (healthcare, building, accounting) rather than clustered in tech or challenger firms, so this is a feature of British business web infrastructure rather than an artefact of which businesses were sampled. How access is restricted, not only how much, differs by market.

Block origin

Intentional vs infrastructure-imposed

Of the 208 sites blocking AI retrieval crawlers, the source of the block was classified into three categories.

53.4%
Explicit — author-set
111 sites. Block is in the site's own robots.txt. May be intentional or legacy configuration.
39.4%
Indeterminate
82 Cloudflare-hosted sites without a managed-robots signature. Likely explicit blocks — cannot be confirmed by automated analysis alone.
7.2%
Infrastructure-imposed
15 sites. Block originates from Cloudflare's managed robots.txt feature — a platform default the owner may never have consciously set.

The infrastructure-imposed subset is the most commercially significant finding: these site owners may be blocking AI search discovery without ever having made that decision. The indeterminate category — 82 Cloudflare-hosted sites — most likely represents explicit blocks, but the configuration path cannot be confirmed by automated means alone.

Sector analysis

Block rates by industry

Block rates vary across the 10 sectors. Real Estate and Education & Training are highest; Healthcare lowest. Rates are computed on policy-observed domains per sector (readable robots.txt only).

% blocking ≥1 retrieval crawler (of policy-observed domains per sector)
Real Estate
59.3%
Education & Training
58.2%
Retail & Ecommerce
53.2%
Technology & SaaS
48.3%
Legal
35.0%
Hospitality & Tourism
30.4%
Professional Services
27.9%
Building & Trades
26.7%
Accounting & Finance
25.5%
Healthcare
20.9%

Real Estate at 59.3% and Education & Training at 58.2% are the highest-blocking British sectors. Education is notably high, driven by university and college domains running deliberate, managed robots.txt policies. Technology & SaaS at 48.3% continues the cross-market pattern of AI-aware sectors blocking heavily. Healthcare at 20.9% is the most open, the lowest healthcare rate in the series.

Per-crawler analysis

Which crawlers are blocked most

Group A (retrieval/citation crawlers) drives the headline finding. Group B (training crawlers) is reported separately, because blocking training crawlers is often a deliberate and legitimate content-protection decision.

Group A — Retrieval & Citation Crawlers (14 tested)
ClaudeBot Anthropic37.9%
GPTBot OpenAI37.7%
Claude-User Anthropic36.2%
Perplexity-User Perplexity36.2%
MistralAI-User Mistral36.2%
anthropic-ai Anthropic36.0%
ChatGPT-User OpenAI35.6%
Googlebot baseline34.5%
Group B — Training Crawlers (7, separate)
Amazonbot Amazon38.8%
Bytespider ByteDance39.0%
Applebot-Extended Apple38.4%
CCBot Common Crawl38.2%
Google-Extended Gemini training37.9%
meta-externalagent Meta37.7%
FacebookBot Meta36.6%

The Googlebot parity finding holds in Great Britain. Googlebot is blocked at 34.5%, right alongside the AI retrieval crawlers (ClaudeBot 37.9%, GPTBot 37.7%). Most British AI-crawler blocks are broad restrictions, not targeted AI decisions. The 14 retrieval crawlers cluster tightly (34.5%–37.9%), indicating that where AI is blocked, it is typically blocked uniformly across operators rather than selectively.

Platform analysis

CMS correlation

Block rates by content management system among policy-observed domains. WordPress and Drupal have usable bases in the British sample; the others rest on small samples and should be read with caution.

Block rate by detected CMS (policy-observed domains)
WordPress
25.6% (n=82)
Drupal
7.7% (n=26)

Most sites return no identifiable CMS signature, so platform-level rates are based on the minority that do. WordPress at 25.6% (n=82) sits below the overall British sample average. Drupal at 7.7% (n=26) is markedly lower again, consistent with its heavy public-sector and enterprise skew, where robots.txt tends to be deliberately and conservatively managed. Shopify (n=9), Webflow (n=5), Joomla (n=2) and Squarespace (n=1) have too few domains in this sample to report a meaningful rate.

Methodology

How this study was conducted

Study specification

Methodology version
PTODA C01 Crawler Methodology (v1.2, June 2026). Citeable, versioned specification covering sample criteria, the 21-user-agent crawler list, classification logic, and the policy/infrastructure layer split.
Research instrument
PTODA C01 Crawler v1.2 — a deterministic robots.txt scanner. Same input produces the same result; the study is reproducible by re-running the instrument against the published sample.
Sample
754 publicly identifiable British business websites (commercial operating entities) across 10 industry groups, sourced from named public directories. Portals, aggregators, government, industry bodies, research institutes and not-for-profits are excluded under the harmonised series entity-type rule. No client sites. No sites selected by outcome.
Sectors
Retail/Ecommerce, Real Estate, Legal, Healthcare, Building/Trades, Accounting/Finance, Hospitality/Tourism, Education/Training, Technology/SaaS, Professional Services
Measurement
Public robots.txt parsed per user-agent across 21 AI crawlers (14 retrieval, 7 training). Homepage meta robots and X-Robots-Tag headers examined. CMS and CDN/host detected from homepage signals.
Bot identity
PTODA-C01-Crawler/1.2 — identified honestly in every request. robots.txt respected; polite rate limits applied.
Scan date
17 June 2026, BST. Point-in-time snapshot.
False positive prevention
WordPress /wp-admin/ disallows, Crawl-delay directives, and sitemap declarations explicitly excluded from blocked classification. Validated against 14 fixture tests before batch ran.
URL structure
Root-level domains only. Businesses whose primary British presence is a sub-path of an international domain were replaced with root-domain equivalents. Some businesses that would otherwise qualify are not included.
Policy vs infrastructure layers
Of 754 domains approached, 536 returned a readable robots.txt policy (the policy-layer denominator). 218 returned no observable policy and are reported separately: 66 access-denied (HTTP 403/401/429 at the edge) and 152 unscannable (connection failure, timeout or 5xx — the largest unscannable count in the series). Access-denied and unscannable domains are never counted as open or blocked.

Series freeze reference

Dataset version
AI Crawler Access Study Series v1.2 — frozen 17 June 2026. The authoritative dataset for the Australia, United States, Great Britain and Singapore comparative analysis. All figures on this page derive from the v1.2 series master; figures published under v1.0 are superseded.
Limitations

Caveats

Disclosure & Intellectual Property

Roles. This study is published by the Periodic Table of Digital Authority (PTODA), the methodology owner. It was conducted using the PTODA C01 Crawler v1.2, a deterministic robots.txt reference instrument, under PTODA C01 Crawler Methodology v1.2. AUTHORITY44 provided technical infrastructure and execution support as commercial operator. Douglas Lord is the founder of both PTODA and AUTHORITY44; this relationship is disclosed in full. The sample was constructed from named public directories with no reference to commercial relationships. The methodology is fully documented and reproducible. This study publishes aggregate, anonymised findings only. No named individual site results are published.

Attribution chain: Douglas Lord (researcher, author) · Periodic Table of Digital Authority (publisher & methodology owner) · PTODA C01 Crawler v1.2 (research instrument) · AUTHORITY44™ (commercial operator) · Digital Dominator Pty Ltd ABN 28 616 931 116 (operating entity).

Intellectual property notice: This study, its methodology, findings, data, and all associated content are the original work of Douglas Lord and the property of Digital Dominator Pty Ltd (ABN 28 616 931 116). The Periodic Table of Digital Authority™ is a coined framework and trade mark pending (TM 2644497). AUTHORITY44™ is a trade mark pending (TM 2643932). All rights reserved.

You may cite findings from this study with appropriate attribution identifying the author (Douglas Lord), the publisher (Periodic Table of Digital Authority — periodictableofdigitalauthority.com), and the research instrument (PTODA C01 Crawler v1.2). You may not reproduce this study in full, present these findings as your own research, or use the framework name or trade marks without prior written consent. Use of this research is subject to the Terms of Use.