Introduction: This study explores the impact of Artificial Intelligence (AI) technologies on marketing performance through a systematic literature mapping and bibliometric analysis approach. The study identifies dominant AI technologies such as machine learning, natural language processing, predictive analytics, and generative AI and evaluates their impact on key marketing metrics, including customer engagement, conversion rates, and Return on Marketing Investment (ROMI). Methods: The data collection and analysis process was conducted during the period of March to April 2025 on the Scopus database. 69 articles as of April 2025 with the keyword Technology and AI Trends in Marketing. The top 30 articles were downloaded for analysis and debate, then narrowed down to 13 selected scientific articles as secondary data. Results: Bibliometric mapping through keyword co-occurrence analysis revealed six major research clusters, emphasizing the integration of AI in digital marketing, customer interaction, e-commerce, luxury tourism, manufacturing, and big data analytics. The findings suggest that AI-driven personalization, automation, predictive analytics, and omnichannel strategies significantly improve marketing effectiveness and efficiency. Furthermore, customer responses indicated increased satisfaction, engagement, loyalty, and conversion rates after AI implementation. Critical success factors identified included big data integration, real-time strategic adaptation, seamless customer experience, and ethical considerations. This study contributes to the academic field by providing a comprehensive visual map of AI applications in marketing and highlighting future research directions focused on long-term customer loyalty and ethical AI adoption. Keywords: Artificial Intelligence, Bibliometric Analysis, Marketing Performance, Systematic Mapping, Customer Engagement