Artificial Intelligence Driven Broadcasting with Virtual News Anchors and Automated Script Generation

Desy Apriani; Galih Putra Cesna; Muhtarom Muhtarom; Lod Sulivyo; Yasir Mustafa Kareem

Authors

Desy Apriani University of Raharja, Indonesia Author https://orcid.org/0000-0001-6967-0369
Galih Putra Cesna CAI Sejahtera Indonesia, Indonesia Author https://orcid.org/0009-0004-0719-8299
Muhtarom Muhtarom Universitas Terbuka, Indonesia Author https://orcid.org/0009-0002-1497-9574
Lod Sulivyo STIE Putra Perdana Indonesia, Indonesia Author https://orcid.org/0000-0003-3736-6295
Yasir Mustafa Kareem EESP Incorporation, British Indian Ocean Territory Author https://orcid.org/0009-0008-5096-2300

Keywords:

Artificial Intelligence, Algorithmic Media Production, Automated Broadcasting, Virtual News Anchors, Digital Journalism

Abstract

The rapid advancement of artificial intelligence technologies has significantly transformed the digital media ecosystem. In contemporary broadcasting environments, artificial intelligence systems are increasingly capable of generating and delivering media content autonomously. The emergence of AI driven radio hosts, virtual news anchors, and automated script generation systems reflects the evolution of algorithmic media production. This study aims to examine the technological architecture and operational impact of artificial intelligence in automated broadcasting environments. The research adopts an empirical qualitative approach supported by comparative analysis of documented AI broadcasting platforms and secondary quantitative indicators from industry reports. The analysis focuses on three components of algorithmic media production: AI radio hosts, virtual news anchors, and automated scriptwriting systems. The findings indicate that AI driven broadcasting significantly improves production efficiency, enables continuous media delivery, and enhances the scalability of digital media services. However, several challenges remain regarding editorial transparency, audience trust, and governance of automated information systems. The study concludes that algorithmic media production can contribute to the development of sustainable digital communication infrastructure when supported by responsible policy frameworks and human editorial oversight.

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