Artificial Intelligence and Media Convergence in Sub-Saharan Africa

Abstract

The integration of artificial intelligence (AI) in digital media, print media, and broadcast media is transforming modern communication environments in terms of efficiency, customization, and creativity in storytelling. The research aims at exploring the convergent effects of AI in resource-constrained media environments in sub-Saharan Africa, with a special emphasis on Ethiopia. The study used a systematic literature review of 25 peer-reviewed research studies and a mixed-methods approach in gathering primary research data using a survey of 138 media professionals and 20 in-depth interviews. The results show an uneven adoption rate in the different sectors, with digital media showing the highest level of efficiency gains (M = 4.1/5), while print and broadcast actors are progressing slowly due to infrastructural constraints and a lack of skills. Despite these advancements, all sectors confront significant ethical concerns, including algorithmic bias, misinformation amplification, and the erosion of human editorial oversight. Converging with the convergence theory and the Technology Acceptance Model, the paper explores the factors that influence the acceptance of AI, including perceived usefulness, organizational readiness, and trust in automated systems. The analysis underscores the necessity of hybrid human–AI workflows, context-sensitive ethical guidelines, and targeted policy interventions to address persistent inequalities and safeguard media integrity. Through the lens of specific sociotechnical realities in Ethiopia, the study identifies the dual role of AI trends globally, namely, their role as disruptors and their role as catalysts for innovation. The research offers valuable insights to promote sustainable, inclusive, and ethical media transformation in the Global South.