Goldman Sachs (Briggs and Kodnani), 2023
300 million full-time jobs exposed globally.
Exposed at task level, not displaced. Goldman's own paper estimates 25-50% of workload of exposed occupations could be replaced.
Source paperIndependent reference / Last verified April 2026
Will AI replace my job?
An independent, source-cited calculator on AI job displacement. Updated for 2026. Independent, source-cited estimates of AI exposure by occupation. With the part nobody else shows: what is growing in your role.
78Mnet new roles by 2030WEF Future of Jobs Report 2025 / 170M created against 92M displaced
The data the calculator returns is calibrated against this projection and the underlying ILO, Brookings, and BLS sources. Most other tools show only the displacement side.
This calculator uses OECD, ILO 2025, Brookings 2024, BLS 2024-2034, and WEF Future of Jobs Report 2025 data. The methodology is published in full at /methodology/. The calculator does not predict your individual job; it reports aggregated research findings.
Or see what the calculator returns for these
Section / 01
How to read the result
Three short notes on what the three panels mean and what they do not mean.
Panel 1 (Exposure) gives the ILO 2025 generative AI exposure gradient for the matched occupation. Exposure measures the share of tasks current AI can technically perform. It is not a prediction that the role will be displaced; the same data shows very few high-exposure occupations in actual decline through mid-2025 (Brookings 2025).
Panel 2 (Tasks) shows the top five tasks for the occupation per O*NET 30.2, each tagged Displaceable / Changing / Growing using the Brookings 2024 task-level rubric. The task list is research-derived. It is not an audit of what you personally do. If your role differs, the within-occupation variation is real and the gradient cannot resolve it.
Panel 3 (What is growing) shows the BLS Employment Projections 2024-2034 outlook for the matched occupation plus the top three growing skills relevant to the role from the WEF Future of Jobs Report 2025. The growth panel is occupation-family-level, not your specific employer's plans.
Section / 02
Why this calculator is different
The reframe. Three structural differences from every other AI job calculator currently in the SERP.
01 / The reframe
Other calculators show what is at risk. This one also shows what is growing. The growth panel uses BLS 2024-2034 and WEF 2025 data and is rendered alongside the risk score, not buried. See the full reframe page.
02 / Sourced score
Other calculators publish a single percentile (often Frey-Osborne 2013 derived). This one publishes the ILO 2025 four-band exposure gradient with the source paper linked. The band-based output reflects the source data, not invented precision. See the full bibliography.
03 / Methodology in full
Other calculators do not state their methodology. This one publishes the full methodology, including a separate page pre-empting every reasonable challenge to the approach. See the methodology or how to argue with the calculator.
Section / 03
The most-cited statistics, in calibrated context
Five widely-quoted figures on AI and jobs, each with the source paper and the calibrated note on what the figure does and does not show.
McKinsey Global Institute, 2024
30% of current hours worked could be automated by 2030.
Midpoint scenario. McKinsey publishes a low and a high band; the 30% figure is the central estimate, not a prediction.
Source paperBrookings Institution, 2024
Over 30% of workers could see at least 50% of their tasks disrupted.
Task-level disruption, not whole-job displacement. Brookings's 2025 follow-up finds aggregate-labour-market data does not yet show mass displacement.
Source paperWorld Economic Forum Future of Jobs Report 2025
78 million net new jobs by 2030 (170M created, 92M displaced).
Aggregate, family-level. The transition is not symmetrical; people displaced from one category do not automatically move to the new category.
Source paperLinkedIn Economic Graph, April 2026
Hiring is down approximately 20% since 2022.
LinkedIn states it has not seen AI as the demonstrable cause. Multiple drivers (post-2022 normalisation, rates, sector cycles) overlap.
Source paperSection / 04
What this calculator does not do
The honest disclaimers. The calculator is a research synthesis, not a personal advisor.
It does not predict whether you specifically will lose your job.
It does not advise you on career changes. Consult a qualified career advisor for personal decisions.
It does not factor in your individual employer's plans, your geographic market, your salary, or your seniority within the role.
It does not assume the ILO 2025 score is the only valid measure. Cross-references and limitations are at /methodology/.
It is not personalised. It is occupation-family-level research synthesis. A marketing manager at a SaaS company and a marketing manager at a regional non-profit get the same gradient.
Section / 05
Continue reading
/jobs-ai-will-replace/
Jobs AI will replace
The highest-exposure occupations per ILO 2025.
/ai-proof-jobs/
AI-proof jobs
The lowest-exposure occupations per ILO 2025.
/whats-growing/
What is growing
BLS 2024-2034 plus WEF 2025 skills outlook.
/methodology/
Methodology
Sources, algorithm, limitations, last-verified.
/how-to-argue-with-this/
How to argue with this
Eight pre-empted challenges, with responses.
/sources/
Sources
Full bibliography with classifications.
/glossary/
Glossary
Every term defined and deep-linkable.
/faq/
FAQ
The fifteen most-asked questions, with sourced answers.
Section / 06
Will AI replace the role you do?
The 30 priority occupations published at launch. Each is a deep dive with the ILO 2025 gradient, top tasks tagged via Brookings 2024, BLS 2024-2034 projection, and pre-rendered share card.
Marketing ManagersSoftware DevelopersAccountants and AuditorsParalegals and Legal AssistantsRadiologistsCustomer Service RepresentativesGraphic DesignersRegistered NursesFinancial AnalystsProject Management SpecialistsWriters and AuthorsSales Representatives, Wholesale and ManufacturingLawyersSecondary School TeachersHeavy and Tractor-Trailer Truck DriversAdministrative AssistantsCashiersInterpreters and TranslatorsData ScientistsBookkeeping, Accounting, and Auditing ClerksNews Analysts, Reporters, and JournalistsInsurance UnderwritersHuman Resources SpecialistsTalent Acquisition RecruitersArchitects, Except Landscape and NavalCivil EngineersPharmacistsAutomotive Service Technicians and MechanicsConstruction LaborersChefs and Head Cooks
From the cluster
Methodology and corrections. Every claim on this site links to a primary source. The full methodology is at /methodology/. Pre-empted challenges to the approach are at /how-to-argue-with-this/. Need an independent assessment of AI workforce impact for your organisation? Contact Digital Signet.