Human–AI Collaboration in Broadcast Journalism within Nigerian Public Media - Isah Sani Yusuf; Anthony I. Igyuve; Anthony Ogande (PT Agung Media Publisher, 2026)
The increasing adoption of artificial intelligence (AI) technologies has transformed contemporary journalism by fostering new forms of collaboration between human journalists and intelligent systems. However, empirical evidence regarding human–AI collaboration within public broadcasting institutions in developing countries remains limited. This study examines the nature, extent, and challenges of human–AI collaboration in broadcast journalism within Nigerian public media, using the News and Current Affairs Department of the Nasarawa Broadcasting Service (NBS), Lafia, as a case study. The study employed a mixed-methods research design combining quantitative and qualitative approaches. Quantitative data were collected through structured questionnaires administered to 54 journalists and production personnel, while qualitative data were obtained through in-depth interviews with six senior editorial staff and departmental managers. Data were analyzed using descriptive statistics and thematic analysis. The findings reveal that awareness of artificial intelligence technologies among journalists was relatively high, with 70.4% of respondents reporting familiarity with AI applications; however, only 29.6% had received formal AI-related training. The study further found that human–AI collaboration remained limited and task-specific, with AI primarily utilized for transcription (74.1%), translation (57.4%), audio editing (44.4%), and content summarization (38.9%), while editorial decision-making remained under human control. Organizational and professional barriers, including inadequate training (42.6%), insufficient technological infrastructure (29.6%), ethical concerns (18.5%), and limited institutional support (9.3%), significantly constrained AI integration.