Artificial Intelligence and the Media Workforce: Redundancy, Reinvention, and the Rise of New Roles

Abstract

This thesis investigates how artificial intelligence (AI) is transforming professional roles within media organizations, examining whether it leads to redundancy, role reinvention, or the emergence of new professions. Situated in the context of ongoing AI adoption across different media sectors, the study employs a qualitative, deductive case study approach seen through the lens of theoretical framework of Soft Determinism. Data was collected through semi-structured interviews with representatives from three media organizations of varying sizes and sectors. Thematic analysis, using a combination of AI-assisted and manual coding, identified six key themes relating to AI implementation, role compression, skill transformation, organizational restructuring, ethical resistance, and projections of future media work. Findings reveal that AI is not displacing jobs but is reshaping and reinventing professional roles into hybrid functions where fewer professionals manage broader tasks. Rather than creating entirely new job categories, AI literacy, especially in generative tools has become a valued skillset within existing roles. The study also uncovers structural changes such as flatter hierarchies and redistributed decision-making. This research contributes to a more nuanced understanding of AI’s impact by emphasizing the role of human agency and organisational decision making in shaping technological adoption. The study is limited by its small sample size, restricted access to lower-tier employees, and its focus on only three organizations, but it offers valuable insights into the evolving media workforce. Further research is required for capturing sectoral diversity and broader geographic contexts as AI continues to transform media landscape.