Empowering Innovation: An Empirical Study on the Impact of Generative AI on Online Freelancers’ Performance

As generative AI largely redefines freelancer success in creative industry, we explore the impact of generative AI adoption on freelancers’ performance and its underlying mechanisms. Leveraging data from freelancers specializing in image creation, we employ empirical methods and deep learning tools to analyze image attributes. Our study presents three main findings. First, adopting generative AI improves freelancers’ performance in terms of popularity and various image attributes of their works. Second, the mechanism centers on a limited learning effect, which notably increases popularity and content diversity without altering the fundamental styles, except for those with relatively singular painting styles. Third, content diversity empowered by generative AI is a strong driver for freelancers’ popularity. Our research contributes to two critical areas: the implications of generative AI on creative content generation and expanding the application scenarios of image analysis within IS research. This research provides insights for stakeholders on adapting to the emerging technology.

Publication Details

Journal
Journal of the Association for Information Systems
Published
2024-12-15
Primary Topic
Open Source Software Innovations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empowering Innovation: An Empirical Study on the Impact of Generative AI on Online Freelancers’ Performance

Journal of the Association for Information Systems
Open Source Software Innovations
article

Empowering Innovation: An Empirical Study on the Impact of Generative AI on Online Freelancers’ Performance

article en

Abstract

As generative AI largely redefines freelancer success in creative industry, we explore the impact of generative AI adoption on freelancers’ performance and its underlying mechanisms. Leveraging data from freelancers specializing in image creation, we employ empirical methods and deep learning tools to analyze image attributes. Our study presents three main findings. First, adopting generative AI improves freelancers’ performance in terms of popularity and various image attributes of their works. Second, the mechanism centers on a limited learning effect, which notably increases popularity and content diversity without altering the fundamental styles, except for those with relatively singular painting styles. Third, content diversity empowered by generative AI is a strong driver for freelancers’ popularity. Our research contributes to two critical areas: the implications of generative AI on creative content generation and expanding the application scenarios of image analysis within IS research. This research provides insights for stakeholders on adapting to the emerging technology.

Journal of the Association for Information Systems
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Open Source Software Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.