When an SME founder asks ChatGPT, Perplexity, Claude or Google AI to recommend an accountant in Manchester, the system can only suggest firms it can read. We measured how readable 100 Manchester practices are across 250+ signals. This is what we found.
The leaderboard alone tells a partial story. The interesting data is in what almost every firm in Manchester is doing – or, more precisely, not doing.
A byline says "John Smith, Partner." A human reader knows who wrote what. But AI engines reading the same page can't tell if John is a senior chartered accountant, a junior writer, or a client quoted in a testimonial – because there's no Author Person schema attached. 67 Manchester firms display partner names. AI doesn't know who any of them are.
The same pattern appears in Birmingham: 78 firms display names, 8 label them for AI. This isn't a Manchester problem. It's a UK accountancy industry pattern.
Intertax (75.5) is the only firm in Manchester clearly visible to AI search. The drop from rank 1 to rank 2 is 7 points – bigger than any other gap in the top 30. The Manchester market for AI-discoverable accountants is unusually concentrated.
AI engines use LinkedIn presence as a credibility signal – verified partners, active engagement, recent posts. 70% of Manchester accountancy firms have voluntarily made themselves invisible to that layer of authority. Birmingham shows the same pattern (68/100).
Almost every firm has the human-facing visibility work done. Almost no firm has the AI-facing work done. The gap between rank 1 and rank 100 isn't the depth of the firm's expertise – it's whether that expertise is labelled for machines.
These are the 10 Manchester accountancy practices scoring highest on AI search visibility. They have specific technical foundations in place – schema, structured data, llms.txt, named credentials – that most of the field doesn't.
The only Manchester firm scoring 70+. Full schema stack deployed: Person, Organisation, multiple schema types, llms.txt, content hub structure. Author bios are labelled with Author Person schema – one of only five firms in the entire dataset doing this correctly.
Balanced performance across all three disciplines. Small business focus translates into clean, structured services pages that AI engines can extract cleanly.
Full top-to-bottom setup: Author Person schema deployed, llms.txt file in place, multiple schema types, content hub structure. One of three firms in the entire dataset with the complete AI-readability stack.
Strong SEO foundation translating cleanly to AI visibility. FAQ content deployed plus llms.txt – rare combination in the dataset. Content hub structure with consistent date markup.
Person schema deployed across the partner team. Author bios with Author Person schema – one of only five Manchester firms with both signals in place.
75+ years established, with the structural signals to match. Multiple schema types deployed, content hub structure, LinkedIn presence – a complete top-to-bottom setup that newer firms in the dataset don't yet have.
llms.txt deployed alongside Organisation schema and content hub structure. Strong AI-readiness despite a smaller SEO score than peers – a firm that's invested specifically in AI visibility.
Person schema, author bios, llms.txt, and content hub all deployed. The highest CRO score in the top 10 – AI traffic that lands on the site actually converts.
FAQ content deployed plus multiple schema types – one of only two firms in the dataset combining both. Structured services pages with consistent date markup.
The inverse pattern: weaker Google ranking, stronger AI visibility. Full AI-readiness stack – Person schema, Author Person schema, llms.txt, multiple schema types. Built for the next discovery layer before the previous one.
Top 10 named with consent. The remaining 90 firms anonymised – their data is included so the distribution is honest, but firms outside the top 10 are not identified publicly.
We've now audited 200 UK regional accountancy practices across two cities. The averages are essentially identical – and the underlying patterns are too. AI search invisibility isn't a regional quirk. It's a UK industry pattern.
Slightly higher average. Five firms cleared the 70 line. The author paradox affects 70% of firms.
More concentrated at the top – one firm clearly ahead of a tight pack. The same author paradox affects 67% of firms.
We started with a list of 110 Manchester-based accountancy practices identified from ICAEW directories, Companies House data, and local search results. Each firm was scored using the SearchScore audit framework – 250+ signals across AI search visibility (GEO), traditional search (SEO), and on-site conversion (CRO).
The benchmark publishes 100 firms after filtering: 10 firms failed to complete the audit (sites blocked automated crawling or returned errors), and 3 firms were excluded because they are part of national or international accountancy networks, rather than the independent SME firms this benchmark measures.
The top 10 firms are named with consent – each was contacted before publication and given the option to appear, be anonymised, or request a wording change. The remaining 90 firms are anonymised. Their score data is included so the distribution is honest, but firms below the top 10 are not identifiable.
The same audit framework was used for the Birmingham benchmark in Q2 2026, allowing direct cross-city comparison. The methodology is open and replicable – anyone can run the same audit on any URL at searchscore.io.
The free SearchScore audit takes 60 seconds and gives you the same scores published here. The AI Visibility Programme – limited to five UK accountancy firms at founding rates – ships the fixes for you.