Intelligent information and analytical system for assessing the digital maturity of enterprises based on artificial intelligence technologies

Abstract

The rapid development of digital technologies, artificial intelligence, cloud computing, business analytics, and data-driven decision-making has significantly increased the need for advanced approaches to assessing enterprise digital maturity. Existing assessment models mainly focus on individual aspects of digital transformation and do not fully exploit the capabilities of integrating information and communication technologies with artificial intelligence methods to support strategic management decisions. The purpose of this study is to develop the concept of an intelligent information-analytical system for assessing enterprise digital maturity that enables comprehensive evaluation of digital development, forecasting of future trends, and generation of recommendations for improving digital transformation efficiency. The research employs system analysis, information system modeling, multi-criteria decision-making, integral assessment methods, data analytics, and machine learning techniques. An original architecture of an intelligent information-analytical system is proposed, integrating data acquisition and processing, digital maturity assessment, predictive analytics, recommendation generation, and visualization modules. A structured system of digital maturity indicators is developed and classified into technological, organizational, analytical, and economic dimensions. In addition, an integral Digital Maturity Index is proposed to provide a comprehensive quantitative assessment of enterprise digital transformation. The practical significance of the proposed approach lies in its applicability as a decision support tool for planning digital transformation initiatives, identifying priority areas for ICT infrastructure development, and improving the effectiveness of digital technology implementation. The developed system can be applied by enterprises operating in different economic sectors as well as by researchers and practitioners in the fields of information systems, digital economy, artificial intelligence, and business analytics.