<![CDATA[The rapid development of artificial intelligence (AI) has transformed innovation management by enabling organizations to enhance decision-making, knowledge management, business processes, and the development of innovative products, services, and business models. As the number of publications continues to increase and the research becomes increasingly multidisciplinary, studies on AI-driven innovation management have expanded across various disciplines, creating a need for a more systematic mapping of the field's development, thematic structure, and emerging topics. This study aims to map the evolution of AI-driven innovation management and identify its intellectual and thematic structure through bibliometric and science mapping analysis. The study employed a bibliometric approach using scientific publications indexed in the Scopus database. Data were collected on 5 July 2026 using the TITLE-ABS-KEY search field and predefined keywords related to AI-driven innovation, artificial intelligence, innovation management, and digital innovation. From an initial 180 documents, 80 English-language journal articles published between 2019 and 2026 were selected through a screening process and analyzed using descriptive bibliometric analysis and VOSviewer-based science mapping. The results indicate a substantial increase in publications since 2024, with 2025 recording the highest number of publications, totaling 43 articles. The data for 2026 represent a partial year because data collection was conducted in July and should therefore be interpreted with caution. China and India were the leading contributing countries, with 11 publications each. Business, Management and Accounting was the dominant subject area, accounting for 43% of the total publications. Keyword analysis indicates that artificial intelligence occupies a central position and is strongly connected with innovation, digital transformation, machine learning, knowledge management, and project management. The overlay visualization identifies several relatively recent themes, including generative AI, Industry 5.0, AI-driven business model innovation, leadership, and knowledge acquisition and transfer. The study concludes that AI-driven innovation management is evolving from a primarily technology-oriented focus toward a more strategic, knowledge-oriented, and interdisciplinary research domain. These emerging themes represent promising research areas based on the current bibliometric patterns and warrant further investigation.]]>
