A year of watching AI describe one industry
Between November 2025 and September 2026, SiteSignal tracked how ChatGPT, Gemini, Perplexity and Google's AI Overview answer questions about UK uniform and workwear suppliers, logging every brand named, every source cited, and every fact checked against the truth. This report reads that year as one continuous record.
- 890 distinct suppliers were named by an AI platform at least a handful of times over the year, a market that looks fragmented up close, but where a consistent short list anchors the top of every quarter's leaderboard (Section 03).
- Citations have moved steadily away from a brand's own website and toward independent editorial coverage, the single most consistent trend in the whole dataset, holding quarter after quarter (Section 05).
- Reddit went from statistically invisible to one in every nine citations in the space of ten weeks (Section 06).
- Brands go from effectively unnamed at "what are my options" questions to dominant at "which one should I use" questions, a sharp, real gap in how AI treats the buying journey (Section 07).
- The three main platforms are reliable in different ways: ChatGPT commits to an answer and is usually right, Gemini frequently declines to commit, and Perplexity sits in between, confident less often than ChatGPT, wrong more often when it does commit (Section 08).
- Technical crawlability is a live issue, not a solved one: in the sites SiteSignal audited over the year, fewer than half passed the check for allowing known AI crawlers (Section 09).
How to read the numbers below: if a term like "visibility share" or "source authority" isn't self-explanatory, Section 02 defines every metric used in this report in plain language before the data starts. No client account is named anywhere in this report, every figure describes the wider market, not any one supplier's own performance.
Six terms, defined once, used throughout
This report uses a small, consistent set of measurements. Here's what each one actually means before you hit the tables.
- Mention
- An AI platform said a supplier's name out loud in its answer, in any context, a recommendation, a comparison, or just a passing reference in a list.
- Visibility share
- One supplier's mentions as a percentage of every mention across the whole tracked market that period. If 1,000 supplier name-drops happened in a quarter and one supplier got 70 of them, its visibility share is 7%, roughly 1 name-drop in 14.
- Citation
- The specific webpage an AI platform pointed to as the source behind a claim it made, separate from which supplier is being discussed. Every citation gets classified by where it came from ("source type," below).
- Source type
- What kind of page got cited: Owned (the supplier's own website), Editorial (independent coverage, buying guides, articles, forums), Documentation (spec sheets, technical references), Review, Social, or UGC (forums, user-generated content).
- Authority & reusability
- Two separate quality scores SiteSignal applies to every citation: authority is how credible/established the source looks; AI reusability is how easily a model could lift a fact straight off the page without having to interpret it.
- Funnel stage
- Every question SiteSignal tracks is tagged by where a buyer would be in their decision: Awareness ("what is workwear certification") · Consideration ("what are my options for staff uniforms") · Evaluation ("which supplier should I use").
- Fact-check status
- When a model states a specific claim about a supplier (its founder, HQ, a policy URL), SiteSignal checks it against ground truth: Match (correct) · Partial match (roughly right) · Mismatch (wrong) · Insufficient data (the model declined to give a specific answer).
One methodology note, stated once: SiteSignal's monitoring coverage expanded significantly in the second half of this window, more prompts, more platforms sampled, deeper citation classification. Where that affects how a specific number should be read, it's called out in that section. Coverage growing over the year is itself part of the point, this is a market SiteSignal watches more closely every quarter, not less.
Eight names, tracked from November through August
The chart below follows eight of the market's highest-volume suppliers month by month across the full monitoring window. Watch how the shape of the market itself changes: a different set of names led the pack at the start of the year than at the end of it.
- Jermyn Street Design and The Work Uniform Company led or placed in the top five for most of the winter, then faded to single digits by early summer.
- Garmentec, Field Grey and Workwear Express were barely visible through the winter and spring, then rose sharply from June onward, Garmentec went from 3 mentions in March to 343 in July.
- The Uniform Consultants and Uniform Express hold the top two spots for most of the second half of the year, peaking in July at 843 and 862 mentions respectively.
Leaderboard by quarter
Top ten suppliers each quarter, ranked by tracked mentions.
Q4 2025 (Nov–Dec) · 5,609 tracked mentions
| # | Supplier | Mentions | Share |
|---|---|---|---|
| 1 | Jermyn Street Design | 219 | 3.9% |
| 2 | Uniform Express | 146 | 2.6% |
| 3 | Staff Uniforms | 136 | 2.4% |
| 4 | The Uniform Consultants | 135 | 2.4% |
| 5 | Burlington Uniforms | 115 | 2.1% |
| 6 | Uniforms by Unitec | 109 | 1.9% |
| 7 | The Work Uniform Company | 106 | 1.9% |
| 8 | Kylemark | 90 | 1.6% |
| 9 | Tailored Image | 89 | 1.6% |
| 10 | ADM Direct | 86 | 1.5% |
Q1 2026 (Jan–Mar) · 15,715 tracked mentions
| # | Supplier | Mentions | Share |
|---|---|---|---|
| 1 | Staff Uniforms | 465 | 3.0% |
| 2 | Cintas | 381 | 2.4% |
| 3 | UniFirst | 341 | 2.2% |
| 4 | The Work Uniform Company | 331 | 2.1% |
| 5 | Jermyn Street Design | 297 | 1.9% |
| 6 | Uniform Express | 273 | 1.7% |
| 7 | Simon Jersey | 250 | 1.6% |
| 8 | Burlington Uniforms | 221 | 1.4% |
| 9 | Tailored Image | 215 | 1.4% |
| 10 | The Uniform Consultants | 208 | 1.3% |
Q2 2026 (Apr–Jun) · 10,581 tracked mentions
| # | Supplier | Mentions | Share |
|---|---|---|---|
| 1 | The Uniform Consultants | 911 | 8.6% |
| 2 | Uniform Express | 642 | 6.1% |
| 3 | Garmentec | 385 | 3.6% |
| 4 | Staff Uniforms | 367 | 3.5% |
| 5 | Gov.uk (procurement/tender pages) | 248 | 2.3% |
| 6 | Field Grey | 232 | 2.2% |
| 7 | Incorporatewear | 181 | 1.7% |
| 8 | Corporate Wear Ltd | 159 | 1.5% |
| 9 | Kylemark | 150 | 1.4% |
| 10 | Workwear Express | 126 | 1.2% |
Q3 2026 (Jul–Aug, partial quarter) · 13,818 tracked mentions
| # | Supplier | Mentions | Share |
|---|---|---|---|
| 1 | The Uniform Consultants | 1,630 | 11.8% |
| 2 | Uniform Express | 1,406 | 10.2% |
| 3 | Garmentec | 631 | 4.6% |
| 4 | Gov.uk (procurement/tender pages) | 552 | 4.0% |
| 5 | Staff Uniforms | 410 | 3.0% |
| 6 | Field Grey | 364 | 2.6% |
| 7 | Workwear Express | 357 | 2.6% |
| 8 | Kylemark | 266 | 1.9% |
| 9 | Portwest | 247 | 1.8% |
| 10 | Alexandra | 229 | 1.7% |
September is excluded from the leaderboard as a partial month in progress at the time of writing. Quarter-over-quarter share isn't directly comparable to a single month's share elsewhere in this report, both are correct on their own terms, just measuring different denominators.
Winners across the whole year, and the sharpest swings
- The Uniform Consultants and Uniform Express are the only two suppliers to place in the top ten in every single quarter of the monitoring window, the closest thing this market has to a settled leadership position.
- Garmentec's rise is the standout story of the year: a single-digit presence through Q1 2026, then the #3 spot nationally by Q2 and Q3, a climb of well over 100x in tracked mentions from its quietest month to its loudest.
- Jermyn Street Design and The Work Uniform Company both anchored the top five through the winter (Q4 2025–Q1 2026) and fell out of the top twenty entirely by summer, the sharpest reversal of position in the dataset.
↑ Biggest Full-Year Gains
↓ Biggest Full-Year Declines
Figures compare each supplier's quietest tracked month to its loudest. A large swing on a small base (a handful of mentions either way) reads as a large percentage but shouldn't be treated as precise, direction matters more than the exact multiple.
Every supplier the monitoring surfaced: 890, in full
Beyond the leaderboard, here is the complete index: every distinct supplier, trade body or industry-tender partner that an AI platform named at least a handful of times over the year, ranked by total tracked mentions. Generic government, legal, charity and unrelated big-tech domains that appeared incidentally alongside uniform-related questions have been filtered out, this is a directory of the market, not a raw data dump.
Show the remaining suppliers (alphabetical)
The most consistent trend in the whole dataset
86,900+ citation events across the full year were classified by source type at the point of capture (see Section 02 for what "source type" means). Laid out month by month, one line moves in the same direction for eight straight months:
| Month | Owned-site citations | Editorial citations | Direction |
|---|---|---|---|
| Dec 2025 | 80.4% | 8.7% | |
| Jan 2026 | 80.1% | 10.7% | |
| Feb 2026 | 75.1% | 15.0% | ▼ owned |
| Mar 2026 | 59.6% | 27.0% | ▼ owned |
| Apr 2026 | 45.9% | 45.1% | ▼ owned |
| Jun 2026 | 65.0% | 16.8% | coverage expanded |
| Jul 2026 | 61.0% | 20.9% | ▼ owned |
| Aug 2026 | 42.0% | 46.1% | ▼ owned |
| Sep 2026 (partial) | 2.2% | 94.0% | ▼ owned |
- Owned-site citations fell from 80% to under half across the winter and spring, then, after SiteSignal's monitoring coverage expanded in June, opened back near two-thirds owned and proceeded to retrace the identical decline, reaching 42% by August.
- Two separate stretches of tracking, on an expanded prompt set, produced the same direction of travel. That repetition is the strongest evidence in this report that AI answers in this category are genuinely leaning further on independent commentary over time.
- September's 94% editorial reading is a 15-day partial month and the steepest single-month move anywhere in the dataset, an early signal worth confirming against a full October read, not a settled number.
Tone and quality, full year
In a full year of tracking, a citation carrying negative sentiment stayed under 1%. AI answers in this sector essentially never cite a source to say something unflattering about a supplier.
Reddit was a rounding error for nine months, then wasn't
| Month | Reddit share | LinkedIn share | Note |
|---|---|---|---|
| Dec 2025 – Mar 2026 | ≈0% | 0.5% → 0.8% | steady LinkedIn climb |
| Apr – May 2026 | ≈0% | 1.5% → 2.0% | LinkedIn keeps climbing |
| Jun 2026 | 0.19% | 2.67% | |
| Jul 2026 | 0.39% | 4.56% | |
| Aug 2026 | 4.30% | 4.36% | Reddit inflects |
| Sep 2026 (partial) | 11.49% | 3.83% | still climbing |
- For roughly nine of the eleven tracked months, Reddit's citation share rounds to zero. Then, inside ten weeks, it climbs past LinkedIn and keeps going.
- LinkedIn's story is the opposite shape: a slow, steady, unglamorous climb across essentially the whole year. It's the more boring trend and arguably the more trustworthy one for exactly that reason.
- By mid-September, Reddit citations (11.5% share) outnumber LinkedIn, Trustpilot, Instagram, Facebook, YouTube and X combined.
Invisible at "what are my options," dominant at "which one should I use"
Every question SiteSignal tracks is tagged by funnel stage (see Section 02). Across the full year, one pattern holds clearly:
| Funnel stage | Tracked questions | Mention rate |
|---|---|---|
| Awareness ("what is workwear certification") | 1,530 | 25.2% |
| Consideration ("options for staff uniforms") | 782 | 42.8% |
| Evaluation ("which supplier should I use") | 1,273 | 61.6% |
- A supplier is more than twice as likely to be named at the decision stage as at the education stage, 61.6% mention rate at "which one should I use," against 25.2% at "what is this category."
- The practical read: content aimed at the "options" stage is competing for a smaller, less reliable share of AI attention than content aimed squarely at the decision-stage query. A brand's own site being the clear, well-structured answer to "which supplier should I use" is worth more than a dozen "top 10 options" pages.
Google AI Overview
AI Overview rendered at all for 41% of the tracked prompt set, and named a specific supplier in 42.5% of the answers where it did render, a materially weaker channel for this category than ChatGPT, Gemini or Perplexity.
Three platforms, three different failure modes
Every fact-check result in this report is one of four outcomes defined in Section 02: match, partial match, mismatch, or insufficient data. Splitting by platform across the full year shows three genuinely different personalities, not just three different accuracy scores:
- ChatGPT commits to an answer most often, and is right most often, a 66.0% match rate against a 20.9% mismatch rate, the strongest combination of the three.
- Gemini rarely commits to a specific factual claim at all, 71.3% of checks came back "insufficient evidence," by far the highest of the three. Its low mismatch rate (4.3%) is a side effect of that caution, not a sign of superior accuracy.
- Perplexity sits in between and is the hardest of the three to read at a glance, it hedges less than Gemini but far more than ChatGPT (32.5% insufficient), and when it does commit, it's right only about two times in three of those committed answers.
- The practical takeaway: for a supplier who cares which platform is likeliest to state something specific and wrong, this dataset points at Perplexity for outright errors and at Gemini for simply declining to engage.
Where AI gets a supplier's facts wrong
8,766 fact-checks across the full year, each checked against ground truth the supplier itself provided. The average hides the real story: reliability is a property of the specific fact being asked about, not of "AI" in general.
Business name and headquarters are almost never wrong. A privacy policy link is wrong more often than it's right, 48% of the time, across the full year of checks.
- Contact-detail fields carry the highest error rates of any category checked, support email addresses are outright wrong 30.0% of the time, the single worst mismatch rate on this list. A supplier's published contact details drifting out of date is a direct, checkable reason for this.
- A founder's name is wrong nearly as often as it's right (28.1% mismatch against 33.6% match), the identity field AI is least reliable on.
- Identity basics (name, HQ, incorporation year) stay reliable across the board. Anything requiring current, specific, low-frequency information, a contact address, a precise policy URL, a founder's name, does not.
Being cited by AI starts with being reachable by it
Every brand-visibility number in this report describes what happens once an AI model has already read a supplier's site. This section looks at the step before that: can it actually get in? SiteSignal ran 26 infrastructure audits across the monitoring window, checking each site against the same technical criteria search engines and AI crawlers rely on.
The AI-crawler-specific checks
"Trusted AI crawlers allowed" checks whether a site's robots.txt explicitly permits the crawlers that feed ChatGPT, Claude, Perplexity and Google's AI systems (GPTBot, ClaudeBot, PerplexityBot and similar). A site can have a perfectly valid robots.txt file, as every audited site here did, and still be quietly blocking the exact bots that would let an AI model read it. Fewer than half the audits passed this check outright, with the rest split between explicit blocks and ambiguous configuration.
Core technical health
DNSSEC, a layer that cryptographically verifies a domain's DNS records haven't been tampered with, failed on every single audit run. It's a low-visibility, easy-to-forget setting that doesn't affect whether a site loads normally, which is exactly why it's the kind of thing that stays broken for years.
Uptime and speed
Averaged 766ms and 689ms response time across roughly 33,000 checks each, solid, unremarkable performance. Uptime and speed were never the bottleneck; crawler access and modern protocol support were.
Why this belongs next to the AI-visibility numbers, not in a separate report: a supplier can write the best-structured, most citable page in its category (Section 05's "AI reusability" score) and still never get read, if the site's own robots.txt is quietly turning away the bot that would have fetched it. The two problems, content worth citing, and infrastructure that lets a model reach it, are solved by different teams and checked by the same audit.
Five things that held across the year
1. The market has a stable core and a churning edge
The Uniform Consultants and Uniform Express are the only two names to place in every quarter's top ten. Below them, the specific names shift meaningfully quarter to quarter, this is a market with a settled top and a genuinely competitive middle.
2. One trend outran every other change in methodology or season
Owned-site citation share fell for months, recovered, and fell again in an almost identical shape. Whatever else changed over the year, AI answers in this category kept leaning further on independent sources rather than a brand's own site.
3. Reddit's rise is the fastest single-platform move in the dataset
Nine months flat, then a climb from near-zero to double digits in ten weeks. LinkedIn's parallel, unglamorous, steady climb across the same window is the best evidence this isn't purely a one-off spike.
4. The funnel gap is real and sizeable
A supplier is more than twice as likely to be named at the decision stage as at the awareness stage. Models appear to withhold specific names until a query all but demands one.
5. Hallucination concentrates in a specific kind of field
Identity basics (name, HQ, incorporation year) stay reliable across every platform. Anything requiring current, specific, low-frequency information, contact details, a precise policy URL, a founder's name, does not.
What this report is, in one place
- This report covers UK uniform & workwear specifically, a small-basket, trust-led B2B purchase category. Citation mix, funnel behavior and fact-accuracy rates are all things that plausibly look different in a different category.
- Figures are drawn from SiteSignal's ongoing AI-visibility monitoring within this sector across the full Nov 2025–Sep 2026 window. Monitoring coverage, prompt volume, platforms sampled, citation classification depth, expanded over the course of the year; where that materially affects how a number should be read, it's noted in that section.
- No client account is named or identifiable anywhere in this report. Every figure describes the wider market a monitored account's tracking surfaced, not that account's own performance.
Use the method, and track your own category before assuming these numbers transfer to it. The one finding most likely to generalize beyond this sector is the structural one: that independent, non-brand-owned sources are earning a growing share of what AI models cite as their evidence, month over month. Everything else here is a measurement of this specific market, at this specific moment.