Yorkshire and the Humber · Baseline population 556,500
Official ONS figures for the region Sheffield 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 Sheffield-only figure.
UK average for the same period: unemployment 4.7%, employment 75.3%, inactivity 20.9%. Yorkshire and the Humber ranks 3 of 12 UK regions and countries by unemployment rate.
145,635 people in Yorkshire and the Humber were claiming unemployment-related benefits in September 2026, 5.3% of economically active residents, up 4,060 on September 2025. Among 16–24 year olds the count was 33,835, up 3,330 on the year. Not seasonally adjusted; this is an administrative count, not a survey estimate.
2,398,254 people were on a payroll in Yorkshire and the Humber in September 2026, down 7,956 (0.33%) on the year, against 0.22% down across the UK as a whole — Yorkshire and the Humber is shedding payrolled jobs faster than the national average. 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 Sheffield events — the tracker records the country a layoff was reported in, not the town or city, so nothing here is attributed to Sheffield.
| 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.
Sheffield's post-steel economy has done something genuinely impressive: built a knowledge-sector base around two major universities that together employ and educate a significant chunk of the city's working population. Education at 11.4% and health at 11.8% anchor over 23% of the workforce in resilient sectors. The Advanced Manufacturing Research Centre (AMRC) is a nationally significant asset that gives Sheffield genuine credibility in the automation conversation — this is a city that's not just exposed to automation but actively developing it. But manufacturing at 8.6%, retail at 9.8%, and admin at 9.4% still account for nearly 28% of employment, and these sectors don't benefit from the university halo. Sheffield is really two cities: one built around knowledge, research, and healthcare that's well-positioned for the AI era, and one built around retail, admin, and remaining industrial work that faces the same pressures as everywhere else.
Sheffield forged steel, then forged a university economy out of the ruins, and honestly it's one of the better post-industrial pivots in the country. It's also a pivot that benefits about a third of the population — the students, the academics, the health professionals, the AMRC engineers — while the rest work in retail, admin, and manufacturing that's as automatable in Sheffield as it is in Stoke. Education at 11.4% and health at 11.8% sound great until you realise they're that high partly because everything else shrank. The AMRC is brilliant, Boeing and McLaren have facilities there, and it employs roughly the same number of people as the Meadowhall food court. Speaking of Meadowhall — Sheffield's out-of-town retail monument to the 1990s is still standing, still pulling footfall from the city centre, and still pretending that physical retail has a future that involves as many humans. The city centre has improved dramatically — the Moor is actually pleasant now — but improved city centres don't create employment, they redistribute it. Sheffield's problem is that its success stories (universities, AMRC, Kelham Island's hipster renaissance) are small-scale, while its vulnerabilities (retail, admin, manufacturing) are economy-wide.
The AMRC is a national asset — ensure its innovations create local jobs, not just research outputs. Build a commercial ecosystem around it: firms that commercialise AMRC research, maintain the automated systems it develops, and train the workforce that operates them. Sheffield's two universities should coordinate on a shared AI skills programme that serves local employers at scale. The health sector should be actively developed as a health-tech cluster: Sheffield Teaching Hospitals plus university research plus medical device companies equals a potential ecosystem that could rival Leeds or Manchester. The city centre's improvement should continue with workspace and residential conversion that attracts knowledge workers and creative professionals. Kelham Island and Neepsend show what's possible when former industrial space gets repurposed — extend that model.
They'll keep name-dropping the AMRC at every opportunity — every conference presentation, every council meeting, every bid document — while the actual manufacturing jobs continue their steady decline unremarked and unassisted. Boeing and McLaren will maintain their AMRC partnerships for the research, not for the Sheffield workforce. The universities will produce AI researchers who immediately move to London, San Francisco, or Cambridge for twice the salary and ten times the opportunity. Meadowhall will get a 'leisure extension' that adds a cinema and a trampoline park, delaying its decline by roughly the length of a lease agreement. The city centre will continue gentrifying along the Kelham Island axis while Attercliffe and the east end continue in the opposite direction. Someone will announce a 'Sheffield Innovation District' connecting the universities to the AMRC via a corridor that mostly consists of the tram route. The students will keep coming, keep graduating, and keep leaving. Sheffield's pitch is that it's 'the outdoor city' — a quality of life play that works for people who already have good jobs and means nothing to people whose jobs are being automated.
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 | 11.8% | 0.18 | low | 2.12 |
| Education | 11.4% | 0.15 | low | 1.71 |
| Retail | 9.8% | 0.8 | high | 7.84 |
| Administrative & Support Services | 9.4% | 0.85 | high | 7.99 |
| Manufacturing | 8.6% | 0.82 | high | 7.05 |
| Accommodation & Food Services | 6.4% | 0.48 | medium | 3.07 |
| Financial & Insurance Services | 6.2% | 0.75 | high | 4.65 |
| Professional, Scientific & Technical | 5.8% | 0.3 | low | 1.74 |
| Public Administration & Defence | 5.8% | 0.22 | low | 1.28 |
| Construction | 5.4% | 0.28 | low | 1.51 |
| Transport & Storage | 5.2% | 0.78 | high | 4.06 |
| Information & Communication | 4.4% | 0.5 | medium | 2.2 |
| Arts, Entertainment & Recreation | 4.3% | 0.2 | low | 0.86 |
| Wholesale | 4.2% | 0.55 | medium | 2.31 |
| Real Estate | 1.0% | 0.4 | medium | 0.4 |
| Agriculture, Forestry & Fishing | 0.3% | 0.25 | low | 0.07 |
The vulnerability score is a weighted average of Sheffield'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 67.2 means Sheffield's workforce is significantly concentrated in higher-weighted sectors compared with other United Kingdom cities in this dataset; it does not state a 67.2% probability of displacement.