Lost in Translation? How Structural, Individual, and Professional Factors Hinder AI Adoption in Investigative Journalism

Abstract

This study investigates the shifting role of AI in Dutch investigative journalism, examining the structural, individual, and professional factors shaping its adoption. Through semi-structured interviews with 25 national, regional and local Dutch news media organisations, including newspapers, magazines and broadcasters, and using the lens of the Diffusion of Innovations Theory, we identified key factors hindering adoption. The interviewed investigative journalists expressed uncertainty in selecting and utilising AI tools, emphasising the complexity of these technologies. Communication issues with IT professionals further impede AI adoption, highlighting the need for clearer collaboration mechanisms. Additionally, resource constraints, such as time, personnel, AI literacy and technical guidance, limit experimentation and the full adoption of AI methods. Our findings suggest that AI adoption is not merely a technological transition but a broader cultural shift in investigative journalism’s professional culture and editorial structures. Also, to facilitate AI adoption in investigative journalism—identified as a special kind of journalism—, organisations should address these structural and knowledge-based barriers while fostering a more collaborative, interdisciplinary culture within newsrooms.