AI SUPPORT FOR MARKETING ACTIVITIES IN THE B2B MARKET

Abstract

The article presents a comprehensive study of the potential applications of artificial intelligence (AI) technologies in the marketing activities of companies operating in the B2B market. The author’s approach is based on an integrated analysis of the strategic, analytical, communicative, and operational functions of marketing, within which AI performs the role of an instrument for optimization, automation, and hyper-personalization of business processes. The scientific novelty of the article lies in the development of a six-stage AI-supported lead generation framework, which is based on the principles of the PDCA cycle, as well as the approaches of Account-Based Marketing (ABM) and Customer Journey Mapping (CJM). The framework proposes a logically interconnected sequence of stages: (1) internal analysis and planning, (2) external marketing research, (3) lead segmentation, (4) content development and the formation of personalized communications, (5) building relationships with potential clients, and (6) optimization and reporting. For each stage, the article outlines AI tools that ensure automated data processing, insight generation, lead classification, content hyper-personalization, and the automation of interactions across digital channels. The study proposes a conceptual model of AI-supported marketing activities in the B2B market, demonstrating the role of AI as a core system that enables data processing, algorithmic adaptation, and orchestration of marketing functions. It emphasizes that the next-generation marketing ecosystem must be self-regulating, cyclical, and responsive to changes in the external environment, while the use of AI ensures its continuous improvement through flexible integration of feedback and performance data. The article notes that despite the high effectiveness of machine learning algorithms in automating processes of analysis, segmentation, content generation, and communication, they cannot replace the expert knowledge of industry specialists (SMEs). It is shown that the role of SMEs in the era of AI dominance does not diminish but rather transforms – from being a provider of information to serving as a strategic validator, architect of trust, and source of unique expertise. The implementation of the six-stage AI-supported framework allows marketing activities in the B2B segment to be transformed into a manageable, predictable, and algorithmically aligned system capable of self-adaptation. At the same time, the article identifies promising avenues for further research, including verification of the predictive power of AI tools, evaluation of A/B testing effectiveness in the context of algorithmic variables, and analysis of the influence of AI on long-term patterns of customer behavior in the B2B market.