Isomorphism through AI? Exploring Journalistic AI via Industry Awards (I-JAI)

• Applicant: Professorin Dr. Juliane Lischka
• Subject Area: Communication Sciences
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 559725957

The project "Isomorphism through AI? Exploring Journalistic AI via Industry Awards (I-JAI)" investigates the transformative role of artificial intelligence (AI) in journalism and examines whether the adoption of AI in news organizations follows patterns of institutional isomorphism. Institutional isomorphism refers to the process by which organizations within the same field, such as journalism, become increasingly similar over time due to external pressures, including regulatory, competitive, and professional influences. This project seeks to analyze how AI technologies, particularly those recognized and celebrated through global industry awards, are being integrated into newsroom practices, and whether these technologies are primarily driven by the pursuit of operational efficiency or are aligned with normative journalistic values such as autonomy, accuracy, accessibility, relevance, timeliness, transparency, and diversity. By focusing on global journalism industry awards, the project identifies the AI use cases that are deemed most legitimate and exemplary within the field. Industry awards not only recognize technological innovation but also serve as field-configuring events that set benchmarks for other organizations to follow. Through a mixed-methods approach, the project examines whether these award-winning AI implementations lead to a convergence of practices within journalism, contributing to the homogenization of AI use cases, or whether varying market and organizational conditions allow for a more diverse set of AI applications to emerge. The research explores the role of institutional intermediaries such as industry associations, which act as gatekeepers by influencing which AI use cases gain legitimacy and widespread adoption. The project also considers how news organizations, depending on their size, market position, and geographic location, respond to institutional pressures and whether they conform to or diverge from dominant industry trends. By examining the submissions for global AI awards in journalism, the project evaluates the extent to which operational efficiency is prioritized over other normative principles, and how this emphasis affects the diversity of AI use cases over time. Therefore, the project contributes to the field of organizational journalism research. It investigates whether the institutionalization of AI in journalism encourages innovation or stifles it by promoting a narrow set of use cases. The findings will enhance our understanding of how journalism, as a crucial institution in democratic societies, can leverage AI to improve its performance without compromising core journalistic values. Through this comprehensive analysis, the project aims to inform both academic debates and industry practices.

• DFG Programme: Research Grants