The use of artificial intelligence technologies for scientific and technological forecasting

Currently, artificial intelligence is widely used in the formation of social, economic and environmental forecasts. When creating artificial intelligence, machine learning technologies, deep learning technology and searching for patterns in information arrays (Big Data), artificial language processing and generation technologies, etc. are widely used. At the same time, the issue of using artificial intelligence in scientific and technological forecasting has not been worked out enough. The purpose of the study was to find effective approaches to the use of artificial intelligence technologies in the formation of scientific and technological forecasts. The objective of the study was to identify artificial intelligence technologies that can be used at various stages of the life cycle of scientific and technological forecasting and to specify individual ways of using them to solve problems of predicting the level of development of science, engineering and technology compared to the world. This confirms the relevance of the study. The main research method is the analysis of domestic and foreign publications and best practices for using artificial intelligence technologies in scientific and technological forecasting, as well as the results of research work performed by the authors in the field of scientific and technological forecasting and adapting them to improve the formation of forecasts in the context of digital transformation of the economy and enterprises The authors considered the structure of artificial functions performed by technologies and identified priority areas for the use of artificial intelligence at various stages of scientific and technological forecasting. The expediency and features of the use of semantic analysis and cognitive technologies in predicting the level of readiness of equipment and technologies in comparison with the world under various scenario conditions are shown, which provides the greatest efficiency of the adopted solution. The issues of information and analytical support for the use of artificial intelligence in scientific and technological forecasting based on information technologies for decision support are considered. The novelty of the presented results lies in the fact that, for the first time, the authors describe the possibilities of using the most effective artificial intelligence technologies at various stages of the life cycle for the formation of scientific and technological forecasts from the standpoint of a systematic and integrated approach.