Document Type : Original research papers
Authors
1
Media Advisor at the Ministry of Industry, Mine and Trade.
2
Assistant Professor, Department of Communication Sciences, Faculty of Humanities, East Tehran Branch, Islamic Azad University, Tehran, Iran
10.22098/jast.2026.19344.1459
Abstract
This study examines the primary factors influencing media transformation and artificial intelligence (AI), with a particular emphasis on identifying critical challenges and opportunities within the sports sector. Media transformation in the age of AI is not merely the outcome of technological advancements; rather, it results from a complex interplay of economic, social, cultural, and legal forces that shape its future trajectory in a nonlinear and multi-scenario manner.
Accordingly, this research adopts a foresight methodology by integrating Delphi-based cross-impact analysis with MICMAC structural analysis to identify key drivers across political, economic, social, technological, environmental, and legal (PESTEL) dimensions. In terms of purpose, this study is applied-developmental, and methodologically, it employs a mixed-methods (qualitative–quantitative) approach.
In the first stage, a set of factors influencing AI-driven transformation in the media industry was identified through environmental scanning and a systematic review of the scientific literature. These factors were subsequently refined through three rounds of Delphi with the participation of experts in media, communication, and information technology, resulting in a final consensus on 18 key drivers.
In the next stage, structural analysis using MICMAC software was conducted to examine the interrelationships among these drivers. The results of direct and indirect influence analysis revealed that variables such as the concentration of capital and market power in AI-driven media platforms, the orientation of public policy and regulation, data and algorithmic infrastructures, and the level of technological autonomy constitute the most influential and determining system variables.
In contrast, variables such as legal requirements for algorithmic transparency, public trust in AI-generated content, and the professional skills of the media workforce were identified as dependent variables.
Focusing on the sports industry as one of the most significant sectors within the media landscape, the findings highlight strategic opportunities for the development of sports media and provide actionable insights for managers seeking to leverage AI-driven transformations.
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