The Role of Artificial Intelligence in Selected Marketing Areas
Purpose: Artificial intelligence (AI), particularly Generative AI (GenAI), is a central transformative force in modern marketing. This rapid evolution has created a fundamental tension between the recognized benefits (e.g., hyper-personalisation, operational efficiency, ROI) and significant challenges regarding ethics, algorithmic bias, and consumer trust in generated content. Due to the rapid growth of publications, knowledge in the field has become fragmented. The purpose of this paper is to synthesize the current state of research on the applications and impact of AI across selected marketing areas. Design/Methodology/Approach: The article employs a narrative literature review. A multi-stage search was conducted in leading scientific databases (Science Direct, Ebsco, Proquest) using keywords such as "artificial intelligence" "ai" and "marketing". The resulting literature was categorized and narratively synthesized into seven thematic areas which form the basis of the analysis. Findings: The findings show broad possibilities for the application of AI in the proposed areas. GenAI is revolutionizing content creation, offering massive efficiency gains but raising critical questions about authenticity. AI analytics form the foundation of modern ad targeting (boosting ROI) and predictive analysis, enabling anticipatory marketing. In customer-facing roles, AI (via chatbots and sentiment analysis) is redefining the customer experience (CX) and B2B relationships (AI-CRM). Finally, AI presents specialized applications and paradoxes, such as in green marketing, where its optimisation benefits are weighed against its own energy consumption. Practical Implications: This synthesis provides managers with a structured overview of AI's current capabilities. It highlights the necessity of balancing efficiency gains from automation (e.g., programmatic advertising, chatbots) with the strategic management of new risks, particularly in consumer trust, content authenticity, and the ethical use of predictive data. Originality/Value: By synthesizing seven distinct areas - from content creation to B2B marketing - it provides a conceptual framework for academics. It identifies key research gaps, including the need to study consumer psychological reactions to GenAI, the 'green paradox' of AI, and organizational barriers to adoption in B2B contexts.