Analysis of Multimodal Data in Project Management: Prospects for Using Machine Learning

Abstract

The modern project environment is characterized by high complexity, uncertainty, speed and depth of changes that affect the project during its life cycle. However, the project’s change management processes do not take into account the need to implement analytical procedures for dynamic processing of multimodal data arrays. The purpose of the study is to determine the content of analytical procedures for project management and substantiate the use of machine learning technologies for their effective implementation. The methodological basis was project management methods, theory of change, concepts of artificial intelligence and machine learning, as well as analytical approaches. Methods of descriptive modeling of the project management process and expert assessments of the prospects for using machine learning technologies were also used in the work. The information base was made up of scientific materials on the topic under consideration, as well as expert assessments. The results of the study allowed us to conclude that for the analysis of multimodal data, natural language processing and intellectual decision support technologies are most in demand, which can serve as the basis for new technological solutions in the field of project management.