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The Influence of AI-Driven Technologies on Social Media Marketing Strategies

Author

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  • Nang Thiri San.

    (Faculty of Information Science, University of Information Technology Yangon, Myanmar)

  • Hlaing Htake Khaung Tin

    (Faculty of Information Science, University of Information Technology Yangon, Myanmar)

Abstract

The advent of artificial intelligence (AI) has transformed the way companies adopt social media marketing and enabled them to be more efficient, personalized in their actions, and interesting to the customers. The study also examines ethical and operational concerns associated with AI technologies, including algorithmic bias, content authenticity, data privacy, and implementation challenges. The paper below focuses on the impact of emerging technologies like machine learning, natural language processing, and predictive analytics on creating and executing marketing campaigns on social media. The objective of the present study is to examine the role of these technologies in marketing strategies and how it enhances social media marketing with respect to content creation, customer targeting, sentiment analysis, and enhancement of the performance of various campaigns. To conduct research, a mixed-method approach will be employed, combining both quantitative and qualitative elements, and the impact of technologies on key performance indicators like engagement rate, conversion rate, and customer acquisition cost will be evaluated through statistical analysis of empirical data. In addition to this, potential problems related to the use of AI technologies will be highlighted and considered. Overall, this research should show that technologies can be extremely helpful for social media marketing when used properly but at the same time present some challenges that need to be overcome.

Suggested Citation

  • Nang Thiri San. & Hlaing Htake Khaung Tin, 2026. "The Influence of AI-Driven Technologies on Social Media Marketing Strategies," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 11(6), pages 1189-1197, June.
  • Handle: RePEc:bjf:journl:v:11:y:2026:i:6:p:1189-1197
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