Generative AI and the Reconfiguration of the Digital Gig Economy: An Integrative Review Centered on Content-Generation Workers

• Yongze Zhao

  Author

Generative artificial intelligence is transitioning from a general production tool to the infrastructure of digital labor platforms, driving the digital gig economy to broaden from physically demanding services such as delivery and mobility to knowledge-based services. Drawing on analyses of digital gig work, algorithmic management, and AI-related employment governance, this paper further synthesizes the formation of content-creation labor, the restructuring of the labor process, and the associated risks. Synthesizing existing literature indicates that generative AI, owing to its low cost, openness, and efficient information-processing capabilities, lowers the entry barriers to tools for knowledge-production services and, in conjunction with the supply-demand matching mechanisms of corresponding platforms, provides technical support for the expansion of the knowledge-based gig economy. Meanwhile, automation of standardized content creation, task fragmentation, and algorithmic evaluation may intensify deskilling and value pressures on mid- to low-skilled content labor, driving changes in the cognitive labor value chain, occupational skills structure, and human–machine collaboration work paradigms. Future governance should be enhanced in areas such as data rights, competency certification, social protection, and income distribution.

• JAESD000015.pdf