Directions, problems and prospects of using artificial intelligence in digital marketing

Introduction. The use of artificial intelligence tools in digital marketing is currently several steps ahead of its theoretical foundations described and formed by scientists. Accordingly, the relevance of the study is due to the rapid introduction of artificial intelligence into digital marketing, which ushered in a new era of technological innovations and the transformation of the marketing paradigm. The object of the study is the issue of applying Industry 4.0 technologies in digital marketing practices. The subject of the study is the directions, problems, and prospects of using artificial intelligence tools in digital marketing practices. The purpose of the study involves analyzing the directions, problems, and prospects of using artificial intelligence in digital marketing. Methods. The study used the method of critical analysis of scientific sources, which allowed identifying the main approaches to conceptualizing the role of artificial intelligence in digital marketing. A systematic approach has been used to form a holistic view of the impact of artificial intelligence on the development of digital marketing practices. A classification of the areas of use of artificial intelligence in digital marketing has been carried out based on the division of information systems into back office and front office. Results. The work established that the use of artificial intelligence tools in digital marketing is the starting point for the formation of a new marketing paradigm. The fragmentation of modern approaches to describing the role of artificial intelligence in digital marketing was revealed. The author’s classification of the areas of use of artificial intelligence has been proposed based on the division of information systems into marketing back office and front office. The introduction of artificial intelligence into digital marketing faces problems of security, confidentiality, ethics, and intellectual property, which are solved through data minimization/anonymization and transparent use of technologies.