A General Bibliometric and Conceptual Structure Approach to Global Trends on Artificial Intelligence in Visual Communication and Design Using Scopus Data

Abstract

This study maps the intellectual and conceptual structure of research on artificial intelligence (AI) in visual communication and design using a structured bibliometric approach. A Scopus CSV export dated 21 May 2026 yielded 2,406 English-language journal articles published between 1999 and 2026. The search strategy required the co-presence of AI-related and visual communication/design-related terms within title, abstract, or keyword fields, thereby embedding topical relevance in the retrieval logic. The dataset comprises 830 sources, 7,136 authors, and 478,085 cited references, with an estimated annual growth rate of 19.82% for the complete-growth window ending in 2025. Performance analysis indicates a sharp acceleration after 2019, with publication peaks in 2024 and 2025, while 2026 is treated as a partial year. Science mapping identifies an interdisciplinary field spanning sustainability, human-computer interaction, design studies, education, geoinformation, communication, and applied computing. Conceptual analysis indicates four broad knowledge streams: generative AI and human-AI creativity support; machine learning and computer-vision applications; visual communication/design education; and domain-specific applications in heritage, cities, health, and sustainability. These structures are interpreted as bibliometric associations rather than causal relationships. The study contributes a reproducible map of the field, clarifies its theoretical fragmentation, and proposes a future research agenda centred on human-AI co-creation, visual meaning, cultural context, ethical governance, and theory-driven evaluation.