Employing Artificial Intelligence Technologies in the Monitoring and Analysis Processes of Jordanian Television Channels – A Study on the Communicator
DOI:
https://doi.org/10.35516/hum.v52i4.7212Keywords:
Artificial intelligence, Monitoring and analysis, Television channels, Technologies.Abstract
Objective: To explore the extent to which Jordanian television channels employ artificial intelligence technologies in the process of media monitoring and analysis, and to reveal the AI technologies adopted by Jordanian channels, as well as the main challenges faced.
Methods: The research employed a descriptive approach, relying on a media survey method. A random sample of 50 individuals working in Jordanian channels was surveyed, utilizing a questionnaire as the data collection tool.
Results: The research findings revealed a disparity among employees of Jordanian television channels regarding their knowledge of AI technologies used in the media domain. It was observed that 34% of the sample had some level of familiarity with these technologies, while 24% had no knowledge of AI technologies employed in media operations. Additionally, the research demonstrated a significant positive correlation between the adoption of modern technology by Jordanian television channels and the utilization of AI technologies in monitoring and analysis.
Conclusions: The research concluded that Jordanian channels are still in the early stages of adopting AI technologies and employing them in the process of media monitoring and analysis. The research highlighted the need for Jordanian channels to focus on employing AI technologies in monitoring and analysis due to their effectiveness. It also recommended training television channel employees on using AI technologies in media monitoring and analysis, through practical training sessions and providing them with the necessary facilitative tools.
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Copyright (c) 2025 Dirasat: Human and Social Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accepted 2024-05-06
Published 2025-03-10


