Artificial Intelligence in the Creative Economy: A Systematic Bibliometric Review and Future Research Agenda - Yudiono, Nur (Dinasti Publisher, 2026)
The rapid development of artificial intelligence (AI) has driven significant transformation in the creative economy, a sector fundamentally rooted in creativity, knowledge, and innovation. Although the number of publications addressing AI in the creative economy has increased substantially in recent years, the intellectual structure, thematic evolution, and research gaps within this field remain insufficiently mapped, particularly within the domains of business and management. This study aims to systematically map the scholarly landscape of AI in the creative economy using a systematic bibliometric review approach. Data were collected from the Scopus database through a structured search strategy and predefined inclusion criteria, resulting in a dataset of 128 articles analyzed using VOSviewer software. The citation analysis reveals a total of 2,107 citations, with an average of 16.46 citations per article and an H-index of 22, indicating that this research area is in a growing phase with an emerging core literature. Co-occurrence analysis identifies four major thematic clusters: digital transformation and innovation in the creative economy, technological impacts on economic growth, AI-driven entrepreneurship, and human–AI collaboration in the future of work. Overlay visualization indicates a shift in research focus from macro-level perspectives toward organization-based perspectives, while density visualization highlights that themes such as AI readiness, organizational capabilities, and human capital development in AI-driven creative environments remain underexplored. This study contributes theoretically by demonstrating a shift from industry-based perspectives toward capability-based perspectives in understanding AI adoption within the creative economy. The findings also provide directions for future research and offer practical implications for creative organizations and policymakers in developing sustainable AI adoption strategies.