<![CDATA[The rapid development of artificial intelligence (AI) has brought fundamental changes in modern branding practices, shifting conventional approaches towards data-driven, predictive, and adaptive strategies. The use of technologies such as machine learning, natural language processing (NLP), and predictive analytics allows companies to analyze consumer behavior in depth, personalize brand communications, and optimize strategic decision-making. This study aims to conduct a systematic literature review of branding transformation in the AI era, focusing on the role of machine learning, NLP, and predictive analytics in strengthening brand identity and increasing the competitiveness of the global market. The research method used is a qualitative approach based on library research by analyzing reputable scientific articles indexed in the Scopus, Web of Science, and Google Scholar databases. The analysis was carried out using thematic content analysis to identify thematic patterns, conceptual frameworks, and key research trends in AI-based branding studies. The results of the study show that AI integration significantly increases the effectiveness of branding strategies through advanced personalization, strengthening customer engagement, and optimizing brand reputation management in real-time. Additionally, AI contributes to increased brand value and consumer loyalty in the long run. However, the study also identified various challenges, such as data privacy issues, information security, algorithmic bias, and regulatory gaps, that have the potential to impact consumer confidence. Therefore, AI-based branding transformation needs to be accompanied by ethical, transparent, and consumer-protection-oriented governance. This research is expected to make a theoretical contribution to enriching the strategic marketing literature, as well as to have practical implications for industry players in designing intelligent branding strategies that are adaptive and globally competitive.]]>
