REGULATORY AND LEGAL SUPPORT AND INSTITUTES OF DEVELOPMENT OF CORPORATE INFORMATION SYSTEMS OF PRODUCT QUALITY MANAGEMENT IN THE AI ECONOMY - Lyudmila Y. Yugai; Dmitriy A. Xenofontov; Ekaterina N. Ilyina; Yury A. Tikhomirov; Andrey E. Safronov (Proceedings on Engineering Sciences)
This work elaborates on theoretical, methodological, and legal aspects, which characterise the development of the regulatory support of corporate information systems of quality management in the conditions of disseminating AI technology. The essence and specifics of information systems of quality management are studied, advantages and limitations of AI in optimisation of information and management processes in the systems of quality management are considered, trends and dynamics of the AI economy development are analysed, the state of regulatory and legal support of development of corporate information systems of quality management is studied, the directions of its adaptation to the innovative processes, digitalisation, and the wide usage of AI technologies AI in the systems of quality management are given, and the role of international institutes in these processes is identified. Methodological provisions cover the complex interdisciplinary and system approaches. The multidisciplinary approach connects studies of different sectors, and the system approach allows studying corporate information systems of quality management as a single whole with common characteristics, some of which are formed due to the development of regulatory and legal support and institutional support. The methodology is based on the empirical and analytical approach, which uses the methods of analysis and synthesis, in particular, comparative and system analysis, methods of observation and generalisation, and context analysis and expert methods. The theoretical basis of the research is connected with the relevant discussion about the determination of direction and limits of regulation of the usage of AI in management processes, which include product quality management. The value of the research results consists in the disclosure of the potential of AI in dealing with limitations of traditional systems of quality management, especially in the sphere of big data processing, collection and analysis of information online, and a higher level of intellectual support of managerial decisions. The practical and scientific value of this paper lies in substantiation of the advantages of AI in information systems of product quality management and identification of the directions of adapting regulatory & legal and institutional environments of the corresponding systems to safe and effective application of AI.