Integration of artificial intelligence technologies in news production and distribution: a multiple case study of two mainstream media houses in Kenya

Abstract

Artificial Intelligence (AI) refers to algorithm-based computational systems capable of mimicking human cognitive functions, such as problem-solving, decision-making, language understanding, and pattern recognition. Its growing use in global media industries has enhanced newsroom efficiency by automating routine tasks, enabling real-time data processing, and supporting personalized content delivery. Despite these opportunities, AI also raises concerns related to editorial control, credibility, and ethical use. This study examined how AI technologies are being integrated into news production and distribution in two mainstream media houses in Kenya: Royal Media Services (RMS) and the Kenya Broadcasting Corporation (KBC). Guided by the Diffusion of Innovation Theory, Unified Theory of Acceptance and Use of Technology, and Technological Determinism Theory, the study explored three research questions: How has AI been integrated into news production processes in RMS and KBC? How has AI been integrated into news distribution processes in RMS and KBC? What challenges hinder the integration of AI technologies in RMS and KBC? Methodologically, the study employed the qualitative research approach and the case study research design, utilizing semi-structured interviews with 5 journalists and 1 data specialist from each of the two selected media houses, drawn from a population of 30 journalists and 4 data specialists in the selected media houses. Purposive and snowball sampling methods were used to identify respondents with experience on AI technologies. Data were thematically analyzed through systematic transcription, coding, theme development, and interpretive synthesis. Ethical principles, including informed consent, confidentiality, and voluntary participation, were observed throughout the study. Findings show that AI has been partly integrated into various processes of news production, particularly content creation, quality enhancement, content curation, and editorial efficiency. In distribution, AI supports audience segmentation, personalized content recommendations, cross-platform optimization, and automated content sharing. However, a full and seamless integration remains constrained by several challenges. These include credibility concerns arising from misinformation and “AI hallucinations,” financial limitations that hinder access to advanced tools, limited AI literacy and training, regulatory uncertainty, data privacy concerns, ethical dilemmas around AI generated content, and resistance from journalists worried about job displacement or loss of editorial autonomy. The study concludes that while AI use in Kenyan newsrooms is growing, it remains uneven and shaped by contextual, technical, and organizational limitations. Media houses should therefore expand AI training, strengthen editorial oversight, invest in cost effective AI solutions, and develop clear editorial guidelines. National regulatory bodies should also provide policy direction to guide responsible and transparent AI adoption and integration in the media sector