Structural baseline: bundled city files were last changed 2026-05-08โ€“2026-09-25. Those are file-maintenance timestamps, not observation dates. Rankings use historical workforce composition and fixed heuristic weights; they are not real-time labour-market readings or displacement probabilities.

Bristol

South West ยท Baseline population 472,400

Vulnerability Score
66.6/100
National Rank
#35 of 51

๐Ÿ“Š Current labour market โ€” South West

Official ONS figures for the region Bristol sits in, published June to August 2026. These are measured statistics, separate from the structural exposure score above โ€” they are reported here as context and are not an input to it. Region-level data is the finest geography ONS publishes monthly; it is not a Bristol-only figure.

Unemployment rate (16+)
3.8%
+0.1 pp on the year
Employment rate (16โ€“64)
79.2%
0.0 pp on the year
Inactivity rate (16โ€“64)
17.5%
-0.1 pp on the year

UK average for the same period: unemployment 4.7%, employment 75.3%, inactivity 20.9%. South West ranks 10 of 12 UK regions and countries by unemployment rate.

Claimant count

97,965 people in South West were claiming unemployment-related benefits in September 2026, 3.3% of economically active residents, up 3,815 on September 2025. Among 16โ€“24 year olds the count was 20,285, up 2,240 on the year. Not seasonally adjusted; this is an administrative count, not a survey estimate.

Payrolled employees (HMRC payroll records)

2,506,727 people were on a payroll in South West in September 2026, down 3,907 (0.16%) on the year, against 0.22% down across the UK as a whole. This is an administrative count of actual payroll records, not a survey estimate. The most recent month is a provisional flash estimate and is routinely revised.

Payroll records vs the household survey

The two UK-wide measures of employees disagree. On ONS's own like-for-like comparison, HMRC payroll (RTI) records show payrolled employees down 92,000 over the year and down 37,000 over the quarter in June to August 2026. Over the same period the Labour Force Survey shows employees up 314,000 to 29.9 million. The provisional September flash estimate puts payrolled employees at 30.3 million, down 66,000 on the year. ONS attributes part of the LFS employee increase to improvements in the survey since January 2024, which have obtained more responses from employed people. Levels have therefore moved closer to RTI, but ONS cautions that LFS measures of change 'may be less aligned with RTI because they capture both real labour market shifts and changes arising from the survey improvements'. The divergence is concentrated in the 25 to 34 year old age group, which ONS is still investigating. ONS's view remains that RTI 'currently provides the most reliable measure of employees'. As of the October 2026 release this statement appears in the LFS quality update rather than in the labour market overview bulletin itself. We surface both rather than quietly picking one.

The August 2026 flash estimate reported a fall of 145,000 on the year; the confirmed figure is 111,000. Flash estimates are provisional and are routinely revised when more data arrive, so the September flash of -66,000 should be read as the least settled number here.

ONS research linking RTI to the LFS, published 28 September 2026: Linked HMRC PAYE data showed a stronger recovery in employment after the pandemic and a smaller, less prolonged rise in economic inactivity than the published LFS estimates alone suggested. It also suggested the LFS recovery during 2024 and 2025 may have reduced non-response bias, since using the linked payroll data made only a small difference to the level of employment and inactivity estimates in 2025. ONS describes the work as exploratory and is continuing the analysis.

The survey side is UK-wide; ONS publishes no regional split of this comparison. The payroll side is parsed from the ONS reference table (rtisaoct2026.xlsx). Source: ONS Labour market overview, UK: October 2026, released 20 October 2026. Next release 17 November 2026.

Sources. ONS Labour market overview, UK (time series API); ONS Labour market in the regions of the UK (Table 2, annual changes); ONS Annual Population Survey, via NOMIS (variables, percentages); Claimant count by sex and age (Universal Credit + JSA), ONS/DWP via NOMIS; Earnings and employment from PAYE Real Time Information, seasonally adjusted (Table 7, payrolled employees by NUTS1 region). Retrieved 2026-10-22. LFS and APS outputs moved from “official statistics in development” to “official statistics” on 11 August 2026 and ONS is not seeking reaccreditation; survey-based detail should be read with that in mind. Contains public sector information licensed under the Open Government Licence v3.0.

๐Ÿ“‰ Recent UK layoffs

Reported UK redundancy events from the CopeCheck Layoffs tracker. These are UK-wide, not Bristol events โ€” the tracker records the country a layoff was reported in, not the town or city, so nothing here is attributed to Bristol.

ReportedCompanyRolesSectorSource
2026-08 University of Essex 400 Education www.bbc.co.uk
2026-08 Nothing 100 Technology Google Alerts RSS
2026-08 Travelport 57 Technology Google Alerts RSS
2026-08 TSB 130 Banking bmmagazine.co.uk
2026-08 Diageo 38 Food & Beverage drinks-intel.com
2026-08 WPP 1,267 Advertising gbnews.com
2026-08 Supermassive Games 75 Technology Google Alerts RSS
2026-08 RNLI 75 Charity/Non-profit Google Alerts RSS

74 UK events recorded for 2026, of which 11 are attributed by their source at least partly to AI or automation. Counts are individual reported events, not a national total. The upstream tracker withholds aggregates because source claims may be syndicated, aggregate, planned, aliased or overlapping. These are UK-wide and are not attributed to this city. Compiled from layoffs.fyi, TrueUp, Crunchbase, TechCrunch, and news reports. Snapshot taken 2026-10-22.

๐Ÿ”ฎ The Oracle's Verdict

Model-generated scenario commentary, not reported fact. Specific claims about future employer or council behaviour are hypothetical; use the sector table, not the prose, as the reproducible input to the score.

Bristol has one of the most genuinely resilient economic profiles of any city in this dataset. Professional and scientific services at 9.2%, information and communications at 7.4%, financial services at 8.8%, and a significant aerospace cluster (Airbus, Rolls-Royce) create a knowledge-economy core that's harder to automate than most. Health at 11.2% and education at 9.8% add institutional ballast. The city attracts talent, generates startups, and has the kind of cultural infrastructure that makes knowledge workers want to stay. But admin at 9.8% and retail at 8.4% still account for a substantial portion of employment, and Bristol's prosperity is unevenly distributed โ€” North Bristol and South Bristol might as well be different cities in terms of economic opportunity. The automation story here isn't about whether Bristol survives; it's about whether the people in Hartcliffe and Knowle benefit from the same resilience as the people in Clifton and Redland.

Bristol is that smug friend who's probably going to be fine, and is somehow more annoying for it. Aerospace, fintech, creative industries, two good universities, a population that thinks of itself as alternative despite house prices that are anything but โ€” Bristol has assembled exactly the economic profile that AI researchers point to when they describe 'resilient cities.' Professional services at 9.2%, info-tech at 7.4%, and the Airbus-Rolls-Royce corridor don't automate as easily as whatever Swindon is doing forty minutes down the M4. The problem, of course, is that Bristol is really two cities pretending to be one. North Bristol โ€” Clifton, Redland, Cotham โ€” is a university town with Guardian readers and independent coffee shops that could absorb any economic shock with the proceeds from their Rightmove listings. South Bristol โ€” Hartcliffe, Knowle, Bedminster โ€” has the kind of economic profile that belongs in this table's upper quartile. The Harbour Festival is lovely. The Bearpit is still there, a physical metaphor for the gap between Bristol's self-image and its reality. Bristol will cope with AI like it copes with everything: unevenly, with the prosperous half congratulating themselves on their resilience while the other half wonders what resilience means when you work in a warehouse in Avonmouth.

๐Ÿ›๏ธ Advice for Local Leaders

Bristol's existing strengths are genuine โ€” protect them by ensuring the aerospace cluster stays at the cutting edge of autonomous aviation, electric flight, and sustainable aerospace engineering. The fintech sector is growing and should be actively supported with regulatory sandbox partnerships and talent pipelines from UWE and the University of Bristol. But the council's primary obligation is to the workforce that won't benefit from these high-value sectors. South Bristol needs a dedicated transition programme: digital skills training, creative industry pathways, health-tech opportunities that connect to the NHS Trust's innovation programme. The Temple Quarter development should include genuine affordable workspace, not just lip-service allocation. Bristol's environmental and social justice identity could be leveraged into an AI ethics and responsible technology cluster โ€” there's a genuine market for ethical AI consultancy, and Bristol's brand is perfectly positioned for it.

Bristol will write a 'responsible AI charter,' host a conference at the Watershed about it, serve organic wine, and continue being fine while pretending the wealth gap with South Bristol isn't widening. Bedminster won't be invited to the launch party, and Hartcliffe won't hear about it at all. The Temple Quarter will be developed into something expensive and corporate that the council describes as 'inclusive' and the actual South Bristol population experiences as 'over there.' Airbus and Rolls-Royce will continue their presence because the engineering is here, not because of anything the council did. The fintech startups will cluster around the Harbourside in converted warehouses that charge ยฃ50 per square foot and employ people who commute from Bath. Someone will propose a 'Bristol AI Ethics Institute' that gets great press coverage, attracts academic interest, and employs about fifteen people. The Bearpit will be regenerated, gentrified, and renamed. The fundamental inequality โ€” a city where your postcode determines whether AI displacement is an abstract concept or a personal threat โ€” will be addressed in strategy documents and ignored in budget allocations. Bristol's resilience is real. Its commitment to sharing that resilience is performative.

Sector Breakdown

Historical employment share by broad sector, with CopeCheck's heuristic exposure weight and contribution to the relative score. Higher weights contribute more; they are not probabilities.

Sector Employment % Exposure Weight Exposure Tier Contribution
Human Health & Social Work 11.2% 0.18 low 2.02
Administrative & Support Services 9.8% 0.85 high 8.33
Education 9.8% 0.15 low 1.47
Professional, Scientific & Technical 9.2% 0.3 low 2.76
Financial & Insurance Services 8.8% 0.75 high 6.6
Retail 8.4% 0.8 high 6.72
Information & Communication 7.4% 0.5 medium 3.7
Accommodation & Food Services 6.8% 0.48 medium 3.26
Manufacturing 5.8% 0.82 high 4.76
Public Administration & Defence 5.4% 0.22 low 1.19
Construction 4.6% 0.28 low 1.29
Transport & Storage 4.2% 0.78 high 3.28
Wholesale 3.6% 0.55 medium 1.98
Arts, Entertainment & Recreation 3.4% 0.2 low 0.68
Real Estate 1.4% 0.4 medium 0.56
Agriculture, Forestry & Fishing 0.2% 0.25 low 0.05

How is this score calculated?

The vulnerability score is a weighted average of Bristol's sector employment shares. Each broad sector carries a CopeCheck heuristic exposure weight (0.0โ€“1.0). Frey & Osborne's study estimated occupation-level susceptibility; it did not publish these sector weights. The bundled city files also lack record-level source dates and ledgers, so this is a historical structural comparison rather than an official current statistic. The weighted average is normalised to a 0โ€“100 scale. A score of 66.6 means Bristol's workforce is significantly concentrated in higher-weighted sectors compared with other United Kingdom cities in this dataset; it does not state a 66.6% probability of displacement.

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