Abstract
Public investment in research is to support the development of human knowledge, but the diverse results, scientific discoveries, and innovations should, above all, be valuable to society. The growing importance of the public value of research and assessment of non-academic benefits implies interest in ways of achieving such effects. One of them is the selection of methodological approaches to enhance the quality of research and the related benefits observed within the scientific organization environment. Recently, there have been increasing opportunities to develop AI-based methodological innovations that enhance the public value of research. The use of AI technology facilitates the achievement of breakthrough scientific results and the implementation of solutions that monitor and support the improvement of the value of research assessed in terms of its impact on the socio-economic environment. The aim of this paper is to identify the current main methodological trends and to determine the factors that influence the adoption of responsible methodological innovations based on AI, in order to streamline advanced scientific research to enhance the public value of research, increase the efficiency of scientific research, and improve the working environment in research organizations. The study employs observations of management processes, the evaluation of research projects, quantitative literature research methods, and qualitative and in-depth analysis of selected publications. The determinants of AI-based methodological innovations that drive the creation of social compatibility and public value in scientific research are identified. Mechanisms that support the growth of responsible research innovation, obtaining results that go beyond the state of knowledge, and improving the public value of research are outlined. Conclusions are also formulated regarding the effective planning and implementation of research characterized by significant public value and compatibility between science and society.