% of displaced workers re-absorbed into new AI-driven roles
💬 What Leaders Say
Jobs Displaced
—
GVA Loss
—
Exchequer Loss/yr
—
Net Fiscal Cost/yr
—
Jobs displaced by sector
Thousands of workers (net, after creation offset)
Annual fiscal breakdown
£ billions per year
📊 Detailed Fiscal Analysis — OBR Methodology
Sector
Employment
Displaced (net)
GVA Loss (£bn)
Tax Loss/yr (£bn)
DWP Cost/yr (£bn)
Net Fiscal/yr
📋 OBR Scenario Context
"AI creates a £90 billion fiscal swing between our optimistic and downside scenarios by 2030–31."
OBR · Economic & Fiscal Outlook · March 2026
"UK firms report 8% net job losses — highest among major economies, double the international average."
Morgan Stanley / Bloomberg · Jan 2026
"Up to 7.9 million UK jobs at risk; 59% of all tasks automatable in the second wave."
IPPR · March 2024
Scenario Comparison
Your sidebar settings are Scenario A. Pick a second scenario to compare side by side.
Scenario B:
🔵 Scenario A — Current settings
🟢 Scenario B — Severe
Side-by-side: Jobs displaced by sector
Thousands of workers (net)
Regional Impact Detail
ONS sectoral employment shares by region, adjusted for London/SE finance and tech concentration. Click any region for a full breakdown.
📍 Selected Region Detail
Click a region above to see its detailed breakdown.
Regional jobs displaced comparison
Thousands of workers, all UK regions
MP Constituency Impact Lookup
Enter a postcode prefix (e.g. M1, SW1, CB2) or constituency name to see the estimated AI employment impact based on your current scenario settings.
Example constituencies
ℹ️ About This Data
Constituency estimates use ONS Business Register and Employment Survey (BRES) sectoral data, scaled to constituency workforce size and adjusted for local economic mix. London constituencies are weighted for finance and professional services; northern and Midlands seats for manufacturing and public sector.
MP party data reflects the 2024 General Election result. Figures are illustrative estimates based on regional ONS data.
Share This Scenario
Your settings are encoded in the URL — anyone who opens it sees your exact scenario.