Prospects of the use of artificial intelligence in cadastral and land regulation processes

The article explores the potential and prospects of incorporating artificial intelligence (AI) into cadastral and land management processes, emphasizing its transformative impact on these fields. A comprehensive analysis was conducted to compare the use of scripts with and without AI for various tasks, highlighting the added value of AI elements. Scripts equipped with AI capabilities not only automate routine operations but also enable advanced functionalities such as data analysis, trend forecasting, and recommendation generation. These features significantly enhance the productivity, accuracy, and efficiency of cadastral and land management operations. The article outlines key areas for AI implementation, including the automation of geospatial data processing, the prediction of land-use changes, and the integration of analytical results into decision-making processes. Specific examples demonstrate the application of modern geographic information systems (GIS) that leverage machine learning algorithms to tackle complex challenges, such as identifying optimal land-use strategies and managing environmental impacts. Additionally, the use of AI in precision agriculture is examined, with a focus on calculating vegetation indices and automating land resource monitoring. These applications illustrate the growing importance of AI in creating sustainable and data-driven solutions for land management. Furthermore, the study identifies critical advantages of AI in cadastral processes, such as improved data accuracy, minimization of human errors, and the optimization of time and resource allocation. However, the article also addresses significant challenges associated with AI adoption. These include the need for comprehensive data standardization, the adaptation of existing legislation to accommodate AI-driven approaches, and the development of new methodological frameworks to fully harness the potential of AI in this domain. The findings emphasize the necessity for a balanced approach, combining technological advancements with policy development and methodological innovation, to unlock the full potential of AI in cadastral and land management practices. Keywords: artificial intelligence, cadastre, land management, geoinformation systems, scripts, automation, land management.