BusinessModels

NYU's Damodaran warns an AI crash could be worse than the dot‑com bust

NYU finance professor Aswath Damodaran says in a podcast that an AI sector downturn could be more painful than the 2000 dot‑com collapse.

In detail

  • Thesis: AI requires large physical infrastructure and substantial debt financing, making a correction potentially systemic.
  • Scaling issue: AI incurs compute costs per use, so costs don't naturally fall toward zero like some software models.
  • Economic risk: If AI replaces entire jobs, large white‑collar unemployment could follow; margins may erode due to competition (e.g., Chinese firms like Deepseek).
  • Investor view: Damodaran now focuses on capital expenditures and depreciation for formerly capital‑light tech companies.

Why it matters

A sharp correction in AI capital intensity would affect lenders, suppliers and employment, not just shareholders; businesses should reassess how reliant their models are on ongoing cheap compute and investor financing.

For you Audit your exposure to compute cost increases and supplier concentration, and model downside scenarios where access or price of compute tightens.

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