Abstract
The conservation of archaeological heritage is important for understanding and preserving human history, but conventional approaches often cannot deal effectively with the magnitude and complexity of modern issues. The integration of AI (artificial intelligence) into archaeological methodologies is enhancing research, analysis, and preservation practices. This paper focuses on the changing dynamics of AI applications in archaeological research, pointing out the phases of trend detection, technological progress, and collaborative networks: using bibliometric analysis, co-authorship networks, and keyword density visualizations, we select the dominant topics affecting the discipline, such as ML (machine learning), remote sensing, and predictive modelling. The data indicates that new technologies, such as automated detection systems and neural networks, have greatly improved strategies for site discovery and preservation. However, there exist significant issues like data access, ethical concerns, and technology inequalities across research fields. This study aims to provide a thorough and up-to-date synthesis of AI’s role in archaeology, highlighting its potential to define new best practices for heritage conservation and defining a framework for future research and collaboration. Finally, this research underlines the importance of using interdisciplinary approaches to ensure that AI serves not only as an efficient tool, but also as an ethical and sustainable means of maintaining humanity’s shared cultural heritage.