Abstract
The increasing complexity of mining and geological conditions in the development of mineral deposits, the operation of careers with a 600 and more meters depth, as well as the formation of unique artificial and alluvial massifs determines the need to obtain complete and reliable information about the state of slope structures for their proper assessment and to determine timely management decisions in order to prevent accidents and ensure industrial and environmental safety. The majority of modern geomechanical models are built on the basis of analytical mathematical methods that are not able to calculate all the factors affecting the conditions of the slope structures. With the advent of digital technologies and artificial intelligence systems, it became possible to develop new methods to collect, transfer and store information about engineering geological and hydrogeological factors, as well as to create software solutions aimed at improving the accuracy of slope structure behavior prediction affected by rapidly changing environmental and technological operating conditions.