Goldman just looked at 40 years of data on the ‘scarring’ effects of technological disruption and finds Gen Z isn’t the most at risk

Goldman Sachs economists warn AI could displace ~6%–7% of U.S. workers over the next decade; technology-displaced workers experience nearly 10 percentage points less real earnings growth over 10 years (and ~5pp less than other displaced workers). Displaced workers take ~1 month longer to find jobs and suffer >3% larger real earnings losses on reemployment; recession-timed displacement adds ~3 weeks of unemployment and raises the risk of returning to unemployment and exiting the labor force by ~5pp each. Younger, college-educated workers fare better — cumulative earnings losses roughly half as large and retraining within three years post-displacement boosts 10-year cumulative wage growth by ~2pp and lowers the chance of returning to unemployment by ~10pp.

Analysis

AI-driven displacement will not be a uniform shock; the durable economic effect comes through frictions in occupational mobility and balance-sheet timing rather than instantaneous unemployment alone. Workers with narrow, location-anchored skillsets are most likely to experience multi-year income and housing delays because their assets (human and physical) are harder to redeploy, which compresses demand for entry-level home purchases and raises downstream credit vulnerability.

That pattern creates a clear sectoral bifurcation: firms selling reskilling, staffing and HR-technology see structurally higher addressable markets and potentially higher margin expansion as employers buy shorter, targeted talent solutions; conversely, businesses whose economics rely on continuous first-time homebuyer churn or mortgage origination fees face persistent headwinds. A recession or tighter credit cycle acts as an accelerant — it both increases firm incentives to automate and reduces the wage/credit cushion that would otherwise help displaced workers retrain or buy homes.

Policy and corporate responses are the main levers that could re-price this outlook. Subsidized retraining programs, tax incentives for skill-upgrading, or large employer-led apprenticeship programs would shorten scarring and reallocate demand away from rental housing toward ownership; absent those, expect a multi-year tail to consumer demand shifts, higher stress in certain bank portfolios, and durable growth for training and staffing vendors. Monitoring early enrollment and corporate training spend, regional mortgage application flows, and staffing utilization rates gives advance read on whether the structural shift is accelerating or reversing.

Key Decisions for Investors

• Long MAN (ManpowerGroup), 6–12 months — buy for exposure to elevated demand for contingent labor and employer-paid retraining; target a 20–30% upside if utilization and contract staffing rates rise, stop-loss at 12% for cyclic downside (recession risk).
• Long COUR (Coursera), 9–18 months — take a core position (or call spread) to play scaling enterprise skilling and professional certificates; reward: substantial revenue multiple expansion if corporate partnerships accelerate, risk: competition and slower enterprise adoption — cap downside with a 20% position size.
• Pair trade: Long EQR (Equity Residential) / Short PHM (Pulte), 12–24 months — go long urban rental REIT exposure benefiting from delayed home purchases while shorting entry-level homebuilder cyclicality; expected asymmetric payoff if first-time buying remains weak (30–40% relative outperformance); key risk is a rapid decline in mortgage rates reversing the trade within 6 months.
• Short RKT (Rocket Companies), 6–18 months — express view that lower first-time buyer volume and tightened credit standards will compress origination volumes and margins; use puts or a small outright short (target 25–35% downside) with tight risk controls if housing finance normalizes quickly.