The AI Layoff Trap: Why Competition Traps Firms in Excessive Automation

ArticleBrett Hemenway Falk, Gerry TsoukalasResearch

A theoretical economics paper by Brett Hemenway Falk and Gerry Tsoukalas models why rational firms cut more jobs with AI than is collectively optimal. A demand externality drives the trap: each firm captures all the cost savings from automation but absorbs only a fraction of the resulting demand loss, shifting the rest onto competitors.

Key points

  1. Firms capture the complete cost savings of AI automation while offloading most of the resulting reduction in consumer demand onto rivals.
  2. This demand externality locks rational firms into an automation arms race, displacing workers beyond the collective optimum.
  3. The aggregate loss reduces profits and welfare, harming both workers and business owners.
  4. Market competition and more capable AI amplify the imbalance; wage flexibility and free entry do not fix it.
  5. Universal basic income, upskilling, capital income taxes, worker equity, and Coasean bargaining fail to prevent excess displacement, whereas a Pigouvian automation tax can.

Why it matters

The study outlines a fundamental coordination failure: even when executives recognise that AI layoffs erode the consumer purchasing power sustaining their industries, individual competitive pressures compel them to cut labor anyway.

Analysis

Falk and Tsoukalas examine AI adoption as a prisoner's dilemma rather than a technological inevitability. Because an individual company cannot internalise the macroeconomic demand drop caused by its own layoffs, inaction guarantees elimination by competitors. The paper emphasizes that post-displacement safety nets or retraining do not alter competitive cost incentives, making pre-emptive policy measures such as Pigouvian automation taxes theoretically necessary to align private incentives with macroeconomic stability.

Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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