Generative AI & Changing Work: Systematic Review of Practitioner-led Work Transformations through the Lens of Job Crafting

TL;DR

This systematic review explores how practitioners are transforming their work with Generative AI, highlighting new task management, collaboration shifts, and the need to adapt existing job frameworks to these technological changes.

Contribution

The paper provides a comprehensive synthesis of practitioner-led work transformations due to GenAI, emphasizing the need to update job crafting frameworks for AI-driven changes.

Findings

Professionals delegate routine tasks to GenAI to focus on core work.

Practitioners engage in AI managerial labor to monitor and refine outputs.

Work collaborations are restructured, sometimes bypassing traditional peer interactions.

Abstract

Widespread integration of Generative AI tools is transforming white-collar work, reshaping how workers define their roles, manage their tasks, and collaborate with peers. This has created a need to develop an overarching understanding of common worker-driven patterns around these transformations. To fill this gap, we conducted a systematic literature review of 23 studies from the ACM Digital Library that focused on workers' lived-experiences and practitioners with GenAI. Our findings reveal that while many professionals have delegated routine tasks to GenAI to focus on core responsibilities, they have also taken on new forms of AI managerial labor to monitor and refine GenAI outputs. Additionally, practitioners have restructured collaborations, sometimes bypassing traditional peer and subordinate interactions in favor of GenAI assistance. These shifts have fragmented cohesive tasks into piecework creating tensions around role boundaries and professional identity. Our analysis suggests that current frameworks, like job crafting, need to evolve to address the complexities of GenAI-driven transformations.