AI in Broadcast Media Management: Opportunities and Challenges

Abstract

The objective of this study is to explore the opportunities and challenges of implementing Artificial Intelligence (AI) in broadcast media management. This qualitative study utilized semi-structured interviews with 15 professionals involved in broadcast media management in Iran. Participants were selected through purposive sampling to ensure diverse representation from roles such as producers, directors, technical staff, and executives. The data collection continued until theoretical saturation was achieved. NVivo software was used for data analysis, which involved transcribing the interviews, coding the data, and conducting thematic analysis to identify key themes and subthemes related to AI opportunities and challenges. The study identified several opportunities provided by AI in broadcast media management, including enhanced content creation, improved audience engagement, increased operational efficiency, personalized advertising, data-driven decision-making, and innovative storytelling. However, it also highlighted significant challenges such as technical complexity, high costs of implementation, privacy concerns, resistance to change, skill gaps, ethical considerations, and regulatory issues. These findings are supported by existing literature and align with studies in related fields, demonstrating both the potential and the difficulties of AI integration in media. AI has the potential to revolutionize broadcast media management by improving efficiency, personalization, and innovation. However, its successful integration requires addressing technical, financial, ethical, and regulatory challenges. By understanding these opportunities and obstacles, media organizations can better navigate the complexities of AI adoption and leverage its capabilities to enhance their operations and audience engagement. Future research should expand the scope geographically and include quantitative analyses to further validate these findings.