Artificial Intelligence for Big Data in Modern Marketing: A Review about Trends, Applications, and Challenges.

Abstract: The rapid digital transformation has triggered an explosion in data generation, with its core impact on the marketing landscape. Big data, with huge volumes, speed, and variety, is thus a significant field of opportunities and challenges for marketers seeking to unravel actionable insights. Traditional approaches to data processing are only inefficient and unable to manage such scale and complexity of data. However, with the advent of AI, quite a few advanced tools can handle big data with greater efficiency, thus enabling better consumer understanding, personalization of marketing strategies, and quick decision-making. It has revolutionized marketing, where systems can now analyze big datasets, recognize patterns, and predict customer behaviors. From descriptive analytics, the shift toward predictive and prescriptive has empowered businesses to optimize campaigns toward enhanced customer experiences. This integration of AI means it can be done instantly, enabling real-time response and fostering more relevant consumer engagement. This review delivers a critical outlook on the current trends in AI, their application to marketing, and the challenges businesses face in implementing these new technologies. Ethical issues around data privacy, transparency, and bias in AI models are discussed. The paper highlights future research directions, including federated learning, quantum computing, and multimodal AI, which hold great promise for even further transformation of the marketing domain.

Artificial Intelligence, Machine Learning, Big Data, Marketing, Predictive Analytics

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