The use of artificial intelligence in public broadcasting: A field study on TRT World and TRT Arabic

Artificial intelligence (AI) is rapidly reshaping global media workflows, yet evidence on organisational readiness, benefits, risks, and implementation pathways remains fragmented, particularly for public service broadcasters. By adopting a qualitative research methodology, this study aims to examine the use of artificial intelligence in public broadcasting: a field study on TRT World and TRT Arabic. Specifically, it seeks to examine the adoption level of using AI in TRT; to analyse the advantages, they could bring in implementing AI in TRT; to examine the challenges surrounding the implementation of AI in TRT; and to recommend the implementation of AI in TRT. The study is premised on the diffusion of innovation theory, which examines that AI adoption in media and willingness of journalists and other media personnel in TRT to integrate AI into their daily workflows. The data was collected through the library-based approach and twenty-two (22) semi-structured interviews with reporters and journalists, news producers, news editors, program director, craft editor, specialist in AI ethics, specialist in the quality department, creative video editor, interview producer, news producer, and director. Several methods of data analysis, such as critical and thematic analysis, were employed in analysing the data. The study began with the proposition that AI has potential within TRT. Findings indicate a heterogeneous but advancing state of AI adoption at TRT, most visible in automated/assisted journalism, search and retrieval, multilingual content workflows, and editing/summarisation tools. Reported advantages include measurable efficiency and productivity gains, cost-effectiveness at scale, enhanced content personalisation and audience engagement, improved fact-checking and verification, and acceleration of multilingual production. Challenges cluster around privacy and cybersecurity risks, opacity and explainability deficits, copyright and accountability uncertainties, bias and discrimination in algorithmic outputs, accuracy limitations that necessitate human review, and perceived threats to creativity and roles. Implementation requires coordinated investments in infrastructure and funding, comprehensive training and awareness programs, robust human-in-the-loop governance, and transparent legal and regulatory guardrails aligned with national and international frameworks. The study contributes an empirically grounded readiness index for media AI, a governance model for public broadcasters, and a phased roadmap for TRT's responsible AI deployment. It concludes that AI can augment, rather than replace, public service journalism, provided adoption is guided by transparent oversight, enforceable standards, and sustained capacity building.