Goldman Sachs strategist Ben Snider told investors on Monday that uncertainty tied to artificial intelligence (AI)-driven disruption will suppress growth stock valuations for quarters, possibly years, and that broad exposure to the sector is no longer a viable strategy.
Key Takeaways:
Goldman Sachs strategist Ben Snider warned April 13 that AI disruption fears could weigh on growth stocks for years. Servicenow fell 48% and Salesforce dropped 36% YTD as per-seat licensing models face AI-driven “seat compression,” according to Yahoo Finance author Brian Sozzi’s reporting. Meta, Amazon, and Alphabet are positioned to recover first as Goldman targets selective exposure heading into 2027. AI Fears Drive Software Stock Collapse in 2026, Goldman Sachs Strategist Warns No Quick Rebound The ‘SaaSpocalypse’ and What Goldman Is WatchingThe broader Magnificent Seven, however, is struggling, the Yahoo Finance report explains. JPMorgan strategist Mislav Matejka, quoted in Sozzi’s editorial, says the group is no longer performing its historical safe-haven role relative to the S&P 500. Only Amazon and Alphabet are marginally positive year-to-date. Tesla is down roughly 23%.
Capital is rotating toward sectors with physical assets, including data centers and infrastructure, where exposure to pure software disruption is lower, and AI infrastructure spending remains a direct tailwind.
Public Skepticism Adds Pressure Beyond Wall StreetOpposition to AI data centers is also hardening. 75% of Americans oppose having one built in their community, with 72% of opponents citing higher electricity costs and 64% pointing to water consumption. That local resistance is producing real project delays at a time when hyperscalers are still pushing capital expenditure projections higher for 2026.
The tension the Quinnipiac data captures is real: personal AI tool usage is climbing, with 51% of respondents reporting they have used AI for research, up from 37% in 2025. But adoption is running well ahead of trust. That gap, combined with Goldman’s call for prolonged valuation pressure on growth stocks, suggests the AI cycle is entering a phase where skepticism, not enthusiasm, drives the narrative.
















