Do AI Expectations Reduce Unemployment in the United States? Evidence from an AI Attention Index

Erdinc Akyildirim, Suzan Bekci and Giray Gozgor

No 12653, CESifo Working Paper Series from CESifo

Abstract: This paper constructs an AI Attention Index from LexisNexis news coverage and embeds it within an augmented Phillips curve framework. It then examines the relationship between AI attention and unemployment in the United States using monthly data from January 2000 to December 2025. We find that greater AI attention is associated with lower unemployment. Nonlinear estimates reveal a U-shaped relationship, indicating diminishing marginal effects within the observed data range. The relationship weakens after the onset of COVID-19, with both linear and nonlinear effects reduced. These findings indicate that labour market effects of AI-related expectations are sensitive to macroeconomic regime shifts.

Keywords: artificial intelligence; AI; unemployment; Phillips Curve; nonlinearity; economic policy uncertainty; COVID-19 (search for similar items in EconPapers)
JEL-codes: D84 E24 E31 O33 (search for similar items in EconPapers)
Date: 2026
New Economics Papers: this item is included in nep-ain
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