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In the contemporary digital landscape, artificial intelligence (AI) has become an integral force shaping media consumption patterns. This study critically examines the intersection of AI, capitalism, and media consumption in India through the lens of Marxist Media Theory, particularly the Critical Political Economy of AI. By employing a qualitative research methodology and discourse analysis method, this research explores how algorithmic content distribution perpetuates capitalist ideologies, reinforces class hierarchies, and commodifies user attention. The study systematically reviews existing literature, identifies research gaps, and investigates how AI-driven platforms operate within a capitalist framework to maximize profit while subtly influencing public discourse. The discourse analysis method is applied to assess the narratives embedded within algorithmic recommendations, advertising models, and digital labour exploitation. The findings indicate that AI-driven media landscapes create an illusion of choice while ultimately reinforcing corporate control over information dissemination. This research contributes to the broader discourse on AI ethics, digital capitalism, and media consumption in postcolonial India by highlighting the socio-economic implications of algorithmic governance. The study concludes with a discussion on the ethical concerns of AI-driven media ecosystems and offers recommendations for policy reforms that prioritize digital equity and user autonomy.
Keywords:
AI, Capitalism, Media Consumption, Algorithmic Content, Marxist Media Theory
Cite Article:
"AI, Capitalism, and Media Consumption: A Marxist Critique of Algorithmic Content Distribution in India", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.b411-b418, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512150.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator