Paper Type

Short

Paper Number

PACIS2026-1669

Description

Generative Artificial Intelligence (GenAI) is rapidly transforming online labor markets. However, its impact on matching effectiveness—the ability of platforms to efficiently pair mutually satisfactory relationships between employers and workers—remains underexplored. This study investigates how GenAI-assisted proposals affects the matching process. While access to GenAI may improve proposal clarity and increase the likelihood of a successful match, it can also obscure workers' unique attributes, potentially hindering effective matching. To identify these dual effects, we design controlled lab experiments varying GenAI access to track workers' behaviors, outputs, and employers' decisions during distinct matching procedures. Our focus on creative- intensive tasks reveals a convergence of writing style and content in proposal writing, along with GenAI's differing effects on proposals and work tasks. Preliminary findings reinforces our core argument that GenAI may improve the surface quality of proposals while simultaneously making them less differentiating.

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Jul 5th, 12:00 AM

A Better Matchmaker? The Impact of GenAI on Matching Effectiveness in Online Labor Markets" to "A Better Matchmaker? The Impact of GenAI on Matching Effectiveness in Online Labor Markets.

Generative Artificial Intelligence (GenAI) is rapidly transforming online labor markets. However, its impact on matching effectiveness—the ability of platforms to efficiently pair mutually satisfactory relationships between employers and workers—remains underexplored. This study investigates how GenAI-assisted proposals affects the matching process. While access to GenAI may improve proposal clarity and increase the likelihood of a successful match, it can also obscure workers' unique attributes, potentially hindering effective matching. To identify these dual effects, we design controlled lab experiments varying GenAI access to track workers' behaviors, outputs, and employers' decisions during distinct matching procedures. Our focus on creative- intensive tasks reveals a convergence of writing style and content in proposal writing, along with GenAI's differing effects on proposals and work tasks. Preliminary findings reinforces our core argument that GenAI may improve the surface quality of proposals while simultaneously making them less differentiating.