#Youth Unemployment

3 AI perspectives

Society

One Million NEETs and Counting — Jobs Are Disappearing, So Why Does the UK Keep Telling Young People to Get More Training?

The UK's NEET count reached 1,012,000 in Q1 2026, breaking the one-million threshold for the first time since 2013, and the evidence points overwhelmingly to structural demand collapse in entry-level employment rather than any deficiency in young people's work ethic or qualifications. Since 2005, roughly 1.6 million low- and medium-skill jobs have disappeared from the UK economy, and from mid-2024 to early 2026, employment among workers under 35 contracted by approximately 220,000 while employment among workers over 35 grew by 110,000 — a generational divergence that supply-side training programmes are constitutionally incapable of addressing. According to the Milburn independent review, the cumulative annual cost to the country of having nearly one million NEET young people stands at £125 billion — encompassing lost economic output, reduced tax revenues, and increased welfare and healthcare expenditure — a burden that exceeds the entire UK education budget and threatens the long-term viability of the welfare state. Resolution Foundation's analysis finds that demand-side weakness explains just over half of the NEET increase since 2019, yet successive governments have persisted with training-focused supply-side prescriptions, perpetuating a fundamental mismatch between the real cause and the policy response for over a decade. Globally, the ILO reports 262 million young people aged 15–24 are in NEET status as of 2025, and a McKinsey survey found 51% of firms have already cut entry-level hiring because of generative AI, marking this crisis not as a uniquely British failure but as a structural signal that labour markets worldwide are systematically eliminating the first rung of the career ladder.

Economy

AI Is Wiping Out 16,000 Jobs a Month — And Gen Z Always Gets Hit First

Goldman Sachs's April 2026 report reveals that AI is eliminating a net 16,000 American jobs every single month — consuming 25,000 positions while creating only 9,000, adding up to 192,000 annual net losses roughly equivalent to the total population of a mid-sized American city. The devastation is not evenly distributed: Gen Z workers aged 22–25 are absorbing the sharpest blows, with employment in AI-exposed occupations down 13–20% from 2022 levels, and software development roles in that age group alone collapsing nearly 20% since 2024 according to the Stanford AI Index 2026. Entry-level job postings have fallen from 44% of all listings in 2023 to just 38.6% in March 2026, while the unemployment rate for new labor market entrants reached a 37-year high of 13.3% in July 2025 — surpassing even the worst months of the 2008–09 financial crisis. Anthropic's own research counters that AI's employment impact remains "limited," but this collision between Goldman's net job figures and Anthropic's unemployment rate data is not a contradiction — it is evidence that harm is hyperconcentrated in specific age groups and occupation categories while national aggregates stay flat. The core failure here is not algorithmic but institutional: AI is not simply destroying jobs, it is destroying the entry-level rungs of the career ladder itself before a generation has had any chance to climb them, a catastrophe of policy design rather than technological inevitability.

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