ARTIFICIAL INTELLIGENCE IN SOCIAL MEDIA MARKETING: AN ANALYSIS OF KEY OPPORTUNITIES AND CHALLENGES

ARTIFICIAL INTELLIGENCE IN SOCIAL MEDIA MARKETING: AN ANALYSIS OF KEY OPPORTUNITIES AND CHALLENGES

Authors

  • Benedictus Lysander Tristan Setiawan BINUS University, Indonesia

DOI:

https://doi.org/10.1234/aira.v4i2.48

Keywords:

AI applications, social media marketing, personalized marketing, customer engagement, ethical challenges

Abstract

Artificial intelligence (AI) has significantly reshaped social media marketing by enabling personalized marketing strategies, improving customer engagement, and enhancing real-time campaign optimization. This study aims to explore both the opportunities and challenges posed by AI applications in social media marketing. A systematic literature review was conducted, utilizing databases such as Scopus and following the PRISMA guidelines to ensure transparency and rigor. The review involved title and abstract screening, full-text evaluation, and quality assessment by independent reviewers. Findings indicate that AI-driven personalization increases engagement and customer loyalty through tailored content and automated support systems. Moreover, AI empowers marketers to derive real-time insights and refine campaign strategies dynamically. However, ethical challenges related to data privacy, algorithmic bias, and the erosion of genuine human interaction were also identified as critical concerns. The study highlights the need for marketers to balance technological advancement with ethical responsibility, ensuring transparent, fair, and consumer-centered AI implementations. Overall, AI offers transformative potential for social media marketing, but its deployment must be aligned with ethical frameworks to sustain consumer trust and brand reputation.

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Published

2025-07-31

How to Cite

Setiawan, B. L. T. (2025). ARTIFICIAL INTELLIGENCE IN SOCIAL MEDIA MARKETING: AN ANALYSIS OF KEY OPPORTUNITIES AND CHALLENGES. AIRA (Artificial Intelligence Research and Applied Learning), 4(2), 1–13. https://doi.org/10.1234/aira.v4i2.48

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