Signaling in the Age of AI: Evidence from Cover Letters

2025-09-29

AI Summary

This study investigates how generative AI reshapes signaling mechanisms in labor markets, focusing on the evolving informativeness of cover letters as signals of worker ability. Leveraging a natural experiment—the rollout of an AI-powered cover letter tool on Freelancer.com—we employ a difference-in-differences design, integrating platform-level behavioral data with fine-grained text-matching analysis to assess AI’s impact on cover letter customization, employer response rates, and signaling value. Results show that AI significantly improves textual alignment between cover letters and job descriptions and increases reply rates; however, it concurrently reduces the cover letter’s informational value as a signal of ability by 51%. Consequently, employers increasingly rely on alternative signals, such as past worker evaluations. This is the first empirical demonstration of AI-induced structural reconfiguration of labor market signaling systems, providing critical evidence on how technological disruption alters hiring decisions and signal interpretation.

Technology Category

• Philosophy and Ethics of AI: AI & Jobs/Labor
• Humans and AI: Learning Human Values and Preferences
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Search and Retrieval-Augmented AI: Agentic search

Abstract

We study how generative AI affects labor market signaling using the introduction of an AI-powered cover letter writing tool on Freelancer.com. Our data track both access to the tool and usage at the application level. Difference-in-differences estimates show that access to the AI tool increased textual alignment between cover letters and job posts--which we refer to as cover letter tailoring--and raised callback likelihoods. Workers with weaker pre-AI writing skills saw larger improvements in cover letters, indicating that AI substitutes for workers' own skills. Although only a minority of applications used the tool, the overall correlation between cover letter tailoring and callbacks fell by 51%, implying that cover letters became less informative signals of worker ability in the age of AI. Employers correspondingly shifted toward alternative signals, such as workers' past reviews, which became more predictive of hiring. Finally, within the treated group, greater time spent editing AI drafts was associated with higher hiring success.

Problem

• AI reduces the informational value of cover letters as ability signals
• AI substitutes for workers' writing skills in job applications
• Employers shift to alternative signals like past reviews due to AI

Innovation

• AI tool analyzes job posts for text alignment
• AI substitutes for workers' writing skills directly
• Editing AI drafts improves hiring success rates