Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Coordinating GenAI into Collaborative Newswork

Paper Title

Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Coordinating GenAI into Collaborative Newswork

Publication Info

• Topic area: Integration of Generative AI (GenAI) into collaborative workflows in journalism.
• Keywords: Generative AI, collaborative newswork, journalism, newsroom workflows, organizational coordination, editorial standards, cultural norms, human-AI collaboration.

Background and Problem

• Problem / challenge: GenAI use in journalism is currently fragmented and individualized, with no established mechanisms for integrating it into collaborative workflows. This creates uncertainties, inefficiencies, and risks for editorial standards and organizational credibility.
• Significance: Journalism is inherently collaborative, and GenAI's potential to enhance productivity and creativity remains untapped without proper coordination. Missteps in GenAI adoption could undermine public trust and professional norms.
• Motivation and related work: Prior studies have focused on individual GenAI use, highlighting its task-level affordances and risks (e.g., factual inaccuracies, bias). However, little is known about how GenAI can be integrated into team-based workflows, particularly in high-stakes domains like journalism.

Solution

• Proposed approach: A qualitative study exploring how GenAI can transition from individual use to collaborative integration in newsrooms, based on interviews with 27 Chinese journalists, editors, and managers.
• Novelty:
  1. Empirical evidence showing the gap between individual experimentation and collaborative coordination of GenAI in newsrooms.
  2. Identification of structural and cultural barriers hindering GenAI integration into collaborative workflows.
  3. Proposals for design and policy interventions to support transparent, accountable, and team-based GenAI use.
• Procedure and key techniques:
  • Conducted 27 semi-structured interviews with newsroom professionals in China.
  • Thematic analysis to identify patterns in GenAI use, challenges, and envisioned solutions.
  • Focused on three research questions: effects of individual GenAI use on collaboration, challenges in coordination, and visions for future integration.

Results

• Concrete findings:
  • GenAI use is widespread but highly individualized, informal, and often invisible to colleagues.
  • Journalists use GenAI for tasks like brainstorming, drafting, and summarizing but face uncertainties about how it aligns with team workflows.
  • Structural barriers include lack of organizational incentives, inadequate technical infrastructure, and heightened public scrutiny.
  • Cultural barriers include stigma, secrecy, and fears of professional devaluation.
• Advantage over baselines:
  • Provides a nuanced understanding of the socio-technical and cultural dynamics of GenAI adoption in collaborative settings, going beyond prior studies focused on individual use.
• Experiments / evaluation:
  • In-depth qualitative analysis of interviews with journalists, editors, and managers from Chinese newsrooms engaged in early GenAI adoption.
  • Data analyzed through reflexive thematic analysis to identify challenges and opportunities for collaborative GenAI integration.
• Limitations and future work:
  • Study is limited to Chinese newsrooms, which operate under unique institutional and political conditions.
  • Sample may overrepresent journalists open to GenAI experimentation.
  • Future research could include cross-cultural comparisons, deployment-based studies, and perspectives from non-editorial roles.

Summary

This study examines the challenges and opportunities of integrating GenAI into collaborative newswork, focusing on Chinese newsrooms. While GenAI is widely used individually for tasks like drafting and summarizing, its adoption into team workflows is hindered by structural and cultural barriers, such as lack of coordination mechanisms and fears of professional devaluation. The study proposes design and policy interventions to support transparent, accountable, and collaborative GenAI use, emphasizing the need for shared norms, technical infrastructure, and cultural shifts. These findings contribute to understanding how GenAI can enhance collaboration in high-stakes, institutionally-bound domains like journalism.