Machine learning is becoming increasingly important in digital marketing in the modern business environment, and there is a need to explore the possibilities offered by machine learning in the optimization of this activity. The subject of the work is to investigate machine learning techniques in the automation of the process of creating digital content in marketing and how they can improve the quality and effectiveness of marketing campaigns. The aim of the paper is to analyze the knowledge so far about the mentioned topic in the professional and scientific literature and to analyze the experiences of marketing experts in the application of machine learning and, in doing so, to determine the strategies for the application of machine learning, the benefits and challenges that appear, ethical issues and understanding which elements are considered key for successful implementation. strategies for applying machine learning in content marketing. In the introduction, the subject and goals of the paper are highlighted, with an emphasis on the need to research the impact of automation on the processes of content creation and distribution. Data collection and used methodologies are described in detail to ensure quality analysis and interpretation of results. In the second part of the paper, the term machine learning is defined with reference to historical development, supervised and unsupervised learning techniques and relevant terminology. Further, specific AI tools applied in marketing are explored and concrete case studies are given on the application of machine learning in marketing strategies. Special attention is paid to the ethical and practical challenges arising from this technology. The third part of the paper explores concrete applications of machine learning to the creation, optimization of distribution and personalization of content, with a focus on programmatic advertising, search engine optimization (SEO) and trends in the personalization of marketing strategies. The fourth chapter presents an exploration of marketers' experiences of the role of machine learning in digital marketing, including objectives, methodology, results and discussion, with recommendations for future research and identification of limitations. The conclusion summarizes the key findings and implies future directions for research and application in the field of digital marketing, highlighting the importance of continuous adaptation and innovation in a dynamic digital environment. This paper will provide concrete knowledge and guidance to marketers on how to use the potential of machine learning in their marketing strategies. Through reasoned analysis and interpretation of collected data, this paper will provide a deeper understanding of the impact of machine learning on marketing practice, which will be useful both to the academic community and to practice.