MODELING OF MULTI-CRITERIA ASSESSMENT OF THE STATE AND DEVELOPMENT OF INTELLECTUAL AND INNOVATIVE TECHNOLOGIES

Abstract

The article investigates the problem of developing a scientifically grounded approach to the comprehensive assessment of the state and development of intellectual and innovative technologies under the conditions of digital transformation of the economy. The increasing role of intellectual capital, digitalization, artificial intelligence, automation of management decision-making, and innovation activity requires the improvement of methodological approaches to assessing the development level of intellectual and innovative technologies. The purpose of the study is to develop a multi-criteria assessment model for the state and development of intellectual and innovative technologies based on an integrated system of indicators, ranking procedures, and classification analysis. The proposed approach combines normalization techniques, weighting procedures, integral assessment methods, and classification algorithms to provide a comprehensive evaluation framework. The scientific novelty of the study lies in integrating ranking and classification models into a unified comprehensive assessment system. Unlike existing approaches, the proposed methodology enables not only determining the integral development level but also classifying the evaluated objects according to qualitative development groups, thereby improving analytical capabilities. The practical significance of the obtained results consists in the possibility of applying the proposed methodology by public authorities, research institutions, universities, and enterprises for assessing innovation development, supporting strategic planning, and improving decision-making processes in the field of intellectual and innovative technologies. The article highlights the main challenges associated with the implementation of IIT, including data security risks, ethical concerns, the necessity of continuous workforce upskilling, regulatory barriers, and the socio-economic consequences of automation. The growing influence of AI and machine learning in decision-making processes raises questions about transparency, accountability, and potential biases in automated systems. The study also discusses the legal and economic aspects of IIT adoption, focusing on intellectual property rights, privacy regulations, and the need for global governance frameworks to ensure responsible technology use. Furthermore, the article analyzes the prospects for IIT development in the context of global competitiveness, increased efficiency in business operations, modernization of industrial production, and the digital transformation of education and scientific research. It is argued that successful integration of IIT requires a collaborative approach involving governments, businesses, and educational institutions to foster an innovation-driven economy. The findings suggest that while IIT holds immense potential for enhancing productivity and economic growth, proactive measures must be taken to address associated risks and challenges.