This study investigates the transformative impact of artificial intelligence on art research by analysing data from 749 art research projects and 555,982 non art research projects, as well as 23,999 journal articles. We utilized the SciBERT model for text analysis on research funding proposals and the econometric model to evaluate AI impact on the academic productivity and impact. Our findings reveal that AI has significantly reshaped the role of art across various disciplines. The integration of AI has led to a notable expansion in keyword networks, highlighting advancements in visual art creation, data driven methodologies, and interactive educational tools. AI has also facilitated the integration of art knowledge into nearly all research disciplines, contrasting with the traditionally confined distribution of art knowledge. Despite the substantial increase in publication impact and citation counts facilitated by AI, it has not markedly improved the likelihood of publishing in high-prestige journals. These insights illustrate the complex nature of AI's impact enhancing research impact while presenting challenges in publication efficiency and multidisciplinary integration. The study offers a nuanced understanding of AI's role in art research and suggests directions for addressing the ongoing challenges of integrating art and AI across disciplines.

翻译：本研究通过分析749个艺术研究项目、555,982个非艺术研究项目以及23,999篇期刊文章，探讨了人工智能对艺术研究的变革性影响。我们采用SciBERT模型对研究资助提案进行文本分析，并运用计量经济学模型评估人工智能对学术生产力与影响力的作用。研究发现，人工智能显著重塑了艺术在多个学科中的角色。人工智能的融合带来了关键词网络的显著扩展，凸显了视觉艺术创作、数据驱动方法以及交互式教育工具等领域的进展。人工智能还促进了艺术知识向几乎所有研究学科的渗透，这与艺术知识传统上局限于特定领域分布的情况形成鲜明对比。尽管人工智能大幅提升了出版影响力和引用次数，但并未显著提高在高声望期刊发表论文的可能性。这些发现揭示了人工智能影响的复杂性：它在增强研究影响力的同时，也在发表效率和跨学科整合方面提出了挑战。本研究深化了对人工智能在艺术研究中作用的理解，并为应对艺术与人工智能跨学科整合中的持续挑战提供了方向。