Paper Type
Complete
Abstract
Digital labor platforms have reshaped how labor demand and supply engage in the labor market by matching employers with a global pool of skilled freelancers. These platforms enable scalable, digitally mediated collaboration and access to specialized talent across a wide range of domains. In the GenAI era, these platforms face new pressures related to output quality, accountability, expertise signaling, and dispute risk, as AI-assisted production changes how work is created and evaluated. This study offers novel insights into how these platforms sustain effective coordination and trustworthy exchange in the GenAI era. We apply a five-boundary-condition framework to platform success, digitality, the value-network paradigm, centralized governance, contractual work, and knowledge work, and develop propositions on how these conditions shape coordination efficiency, trust, and exchange reliability under GenAI-related uncertainty. We also outline a comparative design that links each boundary condition to observable platform features and digital trace measures to support cross-platform tests.
Paper Number
1721
Recommended Citation
Wu, Tong and Kim, Tae Hun, "Digital Labor Platforms in the GenAI Era: Addressing the Key Boundary Conditions for Platform Success" (2026). AMCIS 2026 Proceedings. 11.
https://aisel.aisnet.org/amcis2026/sigcnow/sigcnow/11
Digital Labor Platforms in the GenAI Era: Addressing the Key Boundary Conditions for Platform Success
Digital labor platforms have reshaped how labor demand and supply engage in the labor market by matching employers with a global pool of skilled freelancers. These platforms enable scalable, digitally mediated collaboration and access to specialized talent across a wide range of domains. In the GenAI era, these platforms face new pressures related to output quality, accountability, expertise signaling, and dispute risk, as AI-assisted production changes how work is created and evaluated. This study offers novel insights into how these platforms sustain effective coordination and trustworthy exchange in the GenAI era. We apply a five-boundary-condition framework to platform success, digitality, the value-network paradigm, centralized governance, contractual work, and knowledge work, and develop propositions on how these conditions shape coordination efficiency, trust, and exchange reliability under GenAI-related uncertainty. We also outline a comparative design that links each boundary condition to observable platform features and digital trace measures to support cross-platform tests.
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