دراسات اقتصادية
Volume 19, Numéro 1, Pages 166-194
2025-03-09

Artificial Intelligence And Its Effects On The Traditional Models Of The Media Industry

Authors : Boutora Akrem . Belkhiri Radouane .

Abstract

This study analyses the impact of AI on traditional news business models by investigating the extremist transitions that intelligent tools have brought about through the methods of creation, dispersion, and journalist consumption. The study focuses on how intelligent automation can adapt the arrangement of conventional media, which has time trust in linear and hierarchical models, to a more decentralised and synergies standard structure. The research starts with specifying intelligent automation and its progress over the past decade, progress from machine learning and deep learning to the state of the art generative models. It then analyses the theory related to digital adaptation in journalism, such as digital determinism and the political economy of broadcasting, in systematic order to analyze the systematic effect of AI on conventional news organizations. Moreover, the study considers the feasible objective of intelligent automation in the news industry, including automated development of satisfaction through journalistic practices, the examination of important information for satisfied personalization, and audience consumption processes. It also investigates the academic and honorable challenges associated with this transition, such as the loss of innovative individuality, the proliferation of fake news, and systematic discrimination which restructures the forum's interaction form. As a result, the study concludes that the introduction of broadcasting in the generation of MLPs stresses the need for progressing supervisory procedures that maintain happy autonomy and increase transparency in intelligent structures in order to ensure consistency between digital breakthroughs and virtuous broadcasting procedures.

Keywords

Artificial Intelligence, ; Media Industry, ; Machine Learning ; Technological Determinism ; Algorithmic Bias, ; Fake News ; Automated Journalism ; Content Personalization