MIT AI expert warns automating Gen Z entry-level jobs could backfire—and cost companies their future workforce

This is less an earnings story than a signal about how AI value accrues: firms that preserve entry-level hiring are effectively buying optionality on future managers, AI translators, and internal power users. That matters most for IBM, CRM, and AMZN, where implementation quality and workflow adoption will drive the next leg of productivity gains; cutting the apprenticeship layer may save a little SG&A now but can impair execution and product intuition later. The market should assign a modest quality premium to companies proving they can scale AI without hollowing out the talent funnel.

The second-order risk is not broad labor collapse but a delayed leadership bottleneck. If companies automate too aggressively, they may discover 12-24 months later that mid-level bench depth and institutional knowledge are weaker, which shows up as slower rollout velocity, more consulting spend, and higher attrition costs. For consumer-facing names, the first macro impact would be softer discretionary spend from 22-27 year-olds, but that is a months-long issue and likely too small to matter unless the weakness broadens.

Contrarian take: the market is probably over-indexing on “AI kills entry-level jobs” headlines and underappreciating that younger cohorts are usually the fastest to re-skill and the most willing to adopt new tools. Goldman’s mobility evidence argues this is not yet a structural demand shock. The thesis breaks if college-grad unemployment stays elevated through the next two prints and hiring dashboards keep deteriorating; at that point the story shifts from culture to cash flow.