North West · Baseline population 141,818
Official ONS figures for the region Preston sits in, published June to August 2026. These are measured statistics, separate from the structural exposure score above — 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 Preston-only figure.
UK average for the same period: unemployment 4.7%, employment 75.3%, inactivity 20.9%. North West ranks 6 of 12 UK regions and countries by unemployment rate.
202,445 people in North West were claiming unemployment-related benefits in September 2026, 5.5% of economically active residents, up 7,895 on September 2025. Among 16–24 year olds the count was 44,785, up 4,480 on the year. Not seasonally adjusted; this is an administrative count, not a survey estimate.
3,318,448 people were on a payroll in North West in September 2026, down 6,259 (0.19%) 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.
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.
Reported UK redundancy events from the CopeCheck Layoffs tracker. These are UK-wide, not Preston events — the tracker records the country a layoff was reported in, not the town or city, so nothing here is attributed to Preston.
| Reported | Company | Roles | Sector | Source |
|---|---|---|---|---|
| 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.
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.
Preston has earned national and international attention for its community wealth building model — an approach to local economic development that redirects procurement and investment toward local institutions and businesses. It's genuinely innovative, and it's operating on top of an economic structure where manufacturing at 8.8%, admin at 10.4%, and retail at 10.2% create significant automation vulnerability. Health at 10.6% and education at 9.8% provide institutional anchors, and the public sector plays a large role. The question for Preston isn't whether the community wealth building approach has value — it clearly does — but whether it can address a structural transformation of the kind that AI displacement represents. Redistributing spending within an economy is different from restructuring the economy itself, and Preston may need both.
Preston won prizes for community wealth building, which is genuinely impressive and genuinely insufficient for what's coming. The model works by getting anchor institutions to spend locally, which is smart when the local economy has businesses that can absorb that spending. What happens when those businesses automate? You're redistributing a shrinking pie with increasing efficiency, which is better than not redistributing it at all, but it doesn't change the size of the pie. Manufacturing at 8.8%, admin at 10.4%, retail at 10.2% — the sectors that the Preston Model was designed to support are the sectors that AI is designed to shrink. UCLan is a genuine asset that produces graduates who... largely leave Preston, because the local economy doesn't generate the kind of jobs that retain them. The Harris Quarter development sounds promising on paper, and Preston's papers tend to be better than its outcomes. The town has become a case study that other councils visit, which is flattering and ultimately useless if the visiting councils implement no more than Preston does. The Harris Museum is beautiful. The bus station is brutalist and listed. The economy is automatable and unstratified. Preston's innovation is real. The question is whether innovation in economic governance can outrun structural economic decline.
The community wealth building approach is genuinely innovative — extend it to include automation preparedness by requiring anchor institutions to fund retraining programmes and prioritise AI-resilient sectors in their procurement. UCLan's campus expansion and the Harris Quarter development should be oriented toward digital skills, AI literacy, and technical apprenticeships that serve the existing workforce, not just incoming students. Partner with the NHS Trust and the council's own operations to pilot AI tools with staff retraining rather than staff replacement. Preston should become a national demonstrator for how local government can manage AI transition at city scale — the institutional relationships built by the community wealth approach are exactly the foundation needed.
They'll write more papers about the Preston Model, give more conference talks at CLES events, and win more awards while the manufacturing base that the model was designed to support quietly automates itself out of existence. UCLan will launch a Harris Quarter campus that's architecturally impressive and produces graduates who still leave for Manchester at the first opportunity. The council will extend the community wealth approach to AI — 'community AI building' or similar — write a framework, get some academic interest, and implement it at a pace that's meaningful in journal terms and invisible in employment terms. Someone will propose that Preston become a 'responsible AI testbed' and apply for Innovate UK funding that takes two years to arrive. The Harris Museum will reopen beautifully. The Fishergate Centre will continue its existential drift. The actual manufacturing workers, admin staff, and retail employees will experience the future of work through reduced hours, changed contracts, and agency phone calls that never come, not through any innovative governance model. Preston's tragedy isn't that it lacks ideas. It's that the ideas operate at a speed and scale that structural economic change doesn't respect.
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 | 10.6% | 0.18 | low | 1.91 |
| Administrative & Support Services | 10.4% | 0.85 | high | 8.84 |
| Retail | 10.2% | 0.8 | high | 8.16 |
| Education | 9.8% | 0.15 | low | 1.47 |
| Manufacturing | 8.8% | 0.82 | high | 7.22 |
| Financial & Insurance Services | 7.2% | 0.75 | high | 5.4 |
| Public Administration & Defence | 7.2% | 0.22 | low | 1.58 |
| Construction | 5.8% | 0.28 | low | 1.62 |
| Accommodation & Food Services | 5.8% | 0.48 | medium | 2.78 |
| Transport & Storage | 5.4% | 0.78 | high | 4.21 |
| Professional, Scientific & Technical | 5.4% | 0.3 | low | 1.62 |
| Wholesale | 5.1% | 0.55 | medium | 2.81 |
| Information & Communication | 3.8% | 0.5 | medium | 1.9 |
| Arts, Entertainment & Recreation | 2.9% | 0.2 | low | 0.58 |
| Real Estate | 1.0% | 0.4 | medium | 0.4 |
| Agriculture, Forestry & Fishing | 0.6% | 0.25 | low | 0.15 |
The vulnerability score is a weighted average of Preston's sector employment shares. Each broad sector carries a CopeCheck heuristic exposure weight (0.0–1.0). 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 0–100 scale. A score of 71.6 means Preston's workforce is significantly concentrated in higher-weighted sectors compared with other United Kingdom cities in this dataset; it does not state a 71.6% probability of displacement.