‘They’ll lose their humanity’: Dartmouth professor says he’s surprised just how scared his Gen Z students are of AI

Dartmouth professor Scott Anthony reports that many MBA students are fearful of AI since the arrival of ChatGPT, worrying that overreliance on tools will atrophy critical thinking; he references an MIT study on cognitive decline and has redesigned assessments to require exposure of students' working process. For investors, the story highlights potential human-capital and productivity frictions as firms and business schools adapt training and assessment methods, implying modest demand for education and assessment solutions but little immediate market disruption.

Analysis

Market structure: The immediate beneficiary set are AI infrastructure and platform incumbents (NVDA, MSFT, GOOGL) that own chips, cloud and model-delivery stacks; commoditized content and low-value EdTech (e.g., CHGG, COUR) are most exposed as AI can replicate rote outputs cheaply. Expect pricing power to concentrate with vertically integrated players and hyperscalers; high-end GPU/cloud capacity demand should outstrip supply near term, putting upward pressure on unit economics for compute providers.

Risk assessment: Tail risks include rapid regulatory clampdowns (data/academic integrity rules) or a GPU supply-chain shock; either could knock 15-40% off short-term consensus valuations in exposed names. Near-term (days–weeks) volatility will be driven by regulatory headlines and earnings; medium-term (3–12 months) by enterprise LLM rollouts and adoption metrics; long-term (2+ years) by whether human-skills premium sustains demand for costly, in-person/executive education.

Trade implications: Core actionable plays are concentrated long positions in NVDA (compute), MSFT (enterprise AI distribution) and selective short exposure to CHGG/Coursera-style commoditized learning platforms. Use options to express convexity: buy 3–6 month ATM call spreads on NVDA/MSFT sized to 1–3% portfolio risk; short CHGG equity or buy 6–9 month puts as a hedge. Rotate capital from small-cap EdTech into data-center/semiconductor suppliers and Accenture (ACN) for training/consulting tailwinds.

Contrarian angles: Consensus overweights pure-play AI software while underestimating a durable premium for human-validated credentials and executive education; boutique consultancies and certifiers could see 10–25% revenue upside if credentialing tightens. The market may be underpricing the re-bundling of education as a services/verification market — consider small tactical longs in public professional-services names and watch for mispricings in EdTech survivors post any >30% sell-offs.

Key Decisions for Investors

• Establish a 2–3% long position in NVDA via a 6-month ATM call spread (debit), sizing max loss to 1% of NAV; target 30–80% upside over 6–12 months driven by continued GPU scarcity and enterprise LLM demand.
• Allocate 1–2% long to MSFT (buy shares or 6-month call spread) to capture enterprise AI monetization; plan to trim 25% of this position if MSFT outperforms by +20% within 3 months.
• Initiate a 1–2% short position in CHGG (or buy 9-month puts) reflecting high susceptibility to AI-driven commoditization and academic-policy headwinds; cover if CHGG falls >30% or new regulation restricts AI usage (monitor 60-day window).
• Rotate 2–3% from small-cap EdTech into ACN (1–2% long) and select data‑centre suppliers (e.g., AMAT, LRCX) over the next 4–12 weeks to capture re-skilling/consulting demand and hardware spend; rebalance after next two quarterly earnings.
• Use a hedge: buy 3–6 month protection (5–10% notional) via index puts (QQQ or XLK) if AI/regulatory headlines spike; remove hedge if tech volatility (VIX) falls below 18 for 10 consecutive trading days.