EVOLUTION OF MODERN MARKETING TOOLS AND THE ROLE OF ARTIFICIAL INTELLIGENCE

Abstract

The article explores the evolution of the use of artificial intelligence (AI) in marketing and assesses its economic feasibility in modern business practices, particularly in the field of performance marketing. The study systematizes the development of AI by stages, starting from the first CRM solutions and customer segmentation algorithms in the 1990s, which laid the foundation for analytics and personalization, to the emergence of recommendation systems, contextual and programmatic advertising in the 2000s–2010s. Special attention is paid to the 2010s, when the spread of cloud services and SaaS solutions led to the “democratization” of access to technology, making AI tools available even to small and medium-sized businesses. This period is characterized by the integration of machine learning and big data into marketing activities, which provided new opportunities for predictive analytics, automation of communications, and personalization of customer interactions. It is shown that the key challenges at each stage of AI development remained the cost of implementation, complexity of integration into existing business processes, the need for staff training, as well as the growing role of regulatory restrictions and ethical requirements. Particular emphasis is placed on legislative initiatives such as the GDPR in the EU, the CCPA in the USA, PIPEDA in Canada, and the Law of Ukraine “On the Protection of Personal Data,” which set new standards of transparency and data security in the digital era. The role of generative models (GPT, Claude, Gemini, Midjourney, Synthesia), which since the 2020s have opened a new stage in the development of marketing, is analyzed separately. These models enabled the automation of text, visual, and video content creation, the scaling of personalized communications, the integration of chatbots with dialogic capabilities, and the reduction of campaign preparation costs. In the 2020s, key issues also included ethics and privacy, new search formats (voice, visual), and AR/VR solutions in consumer interaction. Thus, the results of the study confirm that the economic feasibility of integrating AI into marketing lies not only in cost optimization but also in creating sustainable competitive advantages in the digital economy. The further development of this field will be determined by the balance between automation and human creativity, ethical approaches to data use, and the ability of businesses to adapt to dynamic technological and regulatory changes.