Scotland · Baseline population 228,800
Official ONS figures for the region Aberdeen 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 Aberdeen-only figure.
UK average for the same period: unemployment 4.7%, employment 75.3%, inactivity 20.9%. Scotland ranks 7 of 12 UK regions and countries by unemployment rate.
108,760 people in Scotland were claiming unemployment-related benefits in September 2026, 3.9% of economically active residents, up 7,630 on September 2025. Among 16–24 year olds the count was 22,920, up 3,075 on the year. Not seasonally adjusted; this is an administrative count, not a survey estimate.
2,445,914 people were on a payroll in Scotland in September 2026, down 3,726 (0.15%) 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 Aberdeen events — the tracker records the country a layoff was reported in, not the town or city, so nothing here is attributed to Aberdeen.
| 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.
Aberdeen's economic story is defined by energy, and its AI resilience depends entirely on whether the energy transition creates enough new work to replace what's being lost. Professional and scientific services at 12.4% — the highest in the dataset outside Cambridge and Oxford — reflects the engineering consultancy, geological expertise, and project management capabilities built over fifty years of North Sea oil. These are skills that translate to offshore wind, hydrogen production, and carbon capture better than almost any other city's workforce. Health at 11.6% and education at 9.4% provide institutional stability. The vulnerability isn't in AI automation of existing roles — it's in whether the energy transition happens fast enough to absorb the oil and gas engineers before their specific expertise becomes obsolete. Aberdeen's skills are AI-adjacent, not AI-vulnerable, which is a significantly better position than most cities in this dataset.
Aberdeen retrained its oil workers as 'energy consultants' and accidentally built an AI-resistant economy, which is more strategic vision than the city intended and more lucky than it deserves. Professional and scientific at 12.4% — mostly petroleum engineers who now call themselves 'energy transition specialists' — creates a workforce that manages complex systems, makes judgement calls under uncertainty, and operates in environments where robots still struggle. The Granite City's weather is miserable and the architecture matches, but the economic profile is surprisingly modern: skills-heavy, service-oriented, and difficult to automate. The oil money built Union Street, the oil jobs built the middle class, and both are now quietly deteriorating while the transition to renewables proceeds at a pace that's either 'encouraging' or 'too slow,' depending on whether you work in offshore wind or still commute to a platform. The city centre looks like what happens when an oil boom ends and nobody repaints: grey buildings on grey streets under grey skies, with Primark occupying what used to be a department store. Aberdeen's resilience is specific to its skills base. Take away the energy expertise and you've got a mid-sized Scottish city with bad weather and a shopping centre that's seen better decades. Fortunately, the skills base is real, and the transition is happening. Unfortunately, it's happening at the speed of planning permissions and government subsidies, not the speed of AI deployment.
The energy transition is Aberdeen's once-in-a-generation opportunity — position the city as the global hub for North Sea decommissioning, offshore wind operations, hydrogen production, and carbon capture technology. The existing subsea engineering, drilling technology, and project management skills translate directly to these sectors; invest in the retraining bridge that ensures smooth workforce transfer. The new Energy Transition Zone should be scaled with urgency — every year of delay is a year of skills atrophy. Robert Gordon University and the University of Aberdeen should coordinate on energy technology programmes that serve the transition timeline. The city centre needs serious investment: Union Street's decline undermines the quality of life that retains skilled workers. Aberdeen has the chance to demonstrate that an energy city can transition successfully. Whether it does depends on speed.
They'll keep saying 'energy capital of Europe' and hope nobody notices it now means wind turbines instead of oil rigs. The Energy Transition Zone will be announced, master-planned, consulted on, debated, and partially built on a timeline that guarantees the first generation of wind engineers will have already been trained elsewhere. The oil majors will maintain Aberdeen offices that shrink by 5% a year while their PR departments talk about 'commitment to the North East.' Shell, BP, and TotalEnergies will all produce Aberdeen transition plans that are more investor relations than workforce development. Union Street will continue its decline, gain another 'regeneration framework,' and lose another independent retailer. The Bon Accord Centre will get a new owner who announces exciting plans that amount to a food court. RGU and Aberdeen Uni will compete for the same renewable energy research funding and produce separate, overlapping strategies. Someone will propose an 'Aberdeen Innovation Mile' from the beach to the Denburn that exists mainly as a line on a map. The granite will remain. The economic substance behind it will be determined by how fast the wind farms get built, which is not a decision Aberdeen gets to make.
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 |
|---|---|---|---|---|
| Professional, Scientific & Technical | 12.4% | 0.3 | low | 3.72 |
| Human Health & Social Work | 11.6% | 0.18 | low | 2.09 |
| Education | 9.4% | 0.15 | low | 1.41 |
| Retail | 8.4% | 0.8 | high | 6.72 |
| Administrative & Support Services | 8.2% | 0.85 | high | 6.97 |
| Construction | 6.8% | 0.28 | low | 1.9 |
| Accommodation & Food Services | 6.8% | 0.48 | medium | 3.26 |
| Manufacturing | 6.2% | 0.82 | high | 5.08 |
| Transport & Storage | 5.8% | 0.78 | high | 4.52 |
| Financial & Insurance Services | 5.8% | 0.75 | high | 4.35 |
| Public Administration & Defence | 5.8% | 0.22 | low | 1.28 |
| Information & Communication | 4.2% | 0.5 | medium | 2.1 |
| Wholesale | 3.4% | 0.55 | medium | 1.87 |
| Arts, Entertainment & Recreation | 3.0% | 0.2 | low | 0.6 |
| Real Estate | 1.4% | 0.4 | medium | 0.56 |
| Agriculture, Forestry & Fishing | 0.8% | 0.25 | low | 0.2 |
The vulnerability score is a weighted average of Aberdeen'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 61.6 means Aberdeen's workforce is significantly concentrated in higher-weighted sectors compared with other United Kingdom cities in this dataset; it does not state a 61.6% probability of displacement.