<![CDATA[The rapid development of digital technology has transformed contemporary markets into data-driven ecosystems where consumer behavior can be continuously monitored and analyzed. The integration of Big Data and Artificial Intelligence has enabled companies to implement highly personalized marketing strategies that influence consumer decision-making processes. This study aims to analyze the role of Big Data and Artificial Intelligence in shaping consumer preferences within digital markets, particularly through mechanisms of behavioral prediction, algorithmic personalization, and repeated exposure across multiple digital touchpoints. This research employs a qualitative descriptive approach based on a systematic literature review of recent scholarly publications related to digital marketing, Big Data analytics, and Artificial Intelligence. Data were collected from reputable academic journals indexed in international databases and analyzed using thematic analysis and conceptual synthesis to identify key patterns and mechanisms through which data-driven technologies influence consumer preferences. The results indicate that Big Data enables firms to collect and analyze large volumes of behavioral data, while Artificial Intelligence transforms these data into predictive insights that generate personalized recommendations, targeted advertisements, and automated interactions. These mechanisms significantly increase consumer engagement, conversion rates, and transaction values, while simultaneously guiding consumer attention toward specific products. Consequently, consumer preferences in digital markets are not only revealed but actively constructed through algorithmic systems embedded within digital platforms. In conclusion, Big Data and Artificial Intelligence function as strategic technologies that reshape consumer preference formation by enabling firms to predict, personalize, and influence purchasing behavior in contemporary data-driven marketing environments.]]>
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