Trends in artificial intelligence in art, science, and the study of symmetry

Artificial intelligence (AI) greatly impacts the arts and sciences, opening new possibilities for creative expression, visualization, and analytical modeling. Our study explores applications of AI across the disciplines of arts and sciences, with a focus on symmetry-based research. A systematic literature review analyzed 100 peer-reviewed academic articles, categorizing AI methodologies in different disciplines. The results show that machine learning dominates AI applications (46%), while expert systems account for 39%. In the arts, AI is particularly prominent in painting and media arts, where deep learning models contribute to style translation and automation of aesthetic analysis. In the science sector, 48% of AI-driven research is related to engineering, which relies on deep learning for automation and predictive modeling. Symmetry-based AI research primarily focuses on structural optimization, image classification, and energy allocation models, highlighting AI’s role in detecting and exploiting symmetric patterns. The results confirm that AI-based approaches fundamentally reshape artistic and scientific methodologies, with increasing attention to the future integration of symmetry-oriented AI models.