• M. Aswini Kumar
• N. Ashfaq

The rapid evolution of Artificial Intelligence (AI) has redefined the landscape of media and journalism, fundamentally transforming the processes of content creation, dissemination, and audience engagement. This research explores the multifaceted impact of AI-driven tools such as natural language generation, automated news writing, content recommendation systems, and deep learning algorithms on modern journalism. Using a mixed-method approach that combines secondary data analysis and expert insights from media professionals, the study examines how AI enhances efficiency, accuracy, and creativity in content production while simultaneously raising ethical and professional challenges. The findings reveal that AI contributes significantly to real-time news delivery, personalized audience experiences, and cost-effective media operations. However, concerns regarding authenticity, bias, misinformation, and the potential displacement of human journalists persist. The study emphasizes the need for a balanced integration of AI, advocating for human oversight, ethical transparency, and responsible innovation in journalistic practices. Ultimately, the research concludes that AI should be viewed as a collaborative tool that augments human creativity and editorial judgment rather than replaces them, ensuring that the core values of truth, accountability, and integrity remain central to journalism in the digital age.

Artificial Intelligence, content creation, media innovation, digital journalism, ethical reporting, news automation.

"AI for Content Creation: Impact on Media and Journalism", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.e380-e392, November-2025, Available :http://www.jetir.org/papers/JETIR2511448.pdf

"AI for Content Creation: Impact on Media and Journalism", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppe380-e392, November-2025, Available at : http://www.jetir.org/papers/JETIR2511448.pdf