PROBLEMS AND DIRECTIONS FOR THE DEVELOPMENT OF INVESTMENT DECISION SUPPORT METHODS

Abstract

The article is devoted to the study of the transformation of methodological approaches to the justification of investment decisions in the context of the digital transformation of economic systems. The relevance of the study is due to fundamental shifts in the nature and content of management processes, caused by the intensive penetration of digital technologies into all aspects of enterprise management. The aim of the work is to conduct a comprehensive analysis of the limitations of classical paradigms of investment analysis and to substantiate the need to develop new-generation methodological systems that meet the requirements of the digital age. As part of the analysis presented in this article, factors that directly and negatively affect the stability and ease of selecting investment projects have been identified and systematized. In particular, the complexity of choosing alternatives grows exponentially due to the increasing intricacy of technological cycles (since an investment idea may be fundamentally incomprehensible to potential investors); the abundance of proposals leads to problems when processing equally viable investment options; and the multi-criteria nature of investment assessment requires, among other things, taking into account various non-financial aspects (in particular, reputational risks). The article comprehensively substantiates the need to expand the methodological framework beyond purely financial analysis, and proposes a comprehensive approach as the optimal alternative — one that combines financial criteria with the assessment of projects from the perspective of strategic alignment. The work is devoted to determining the potential for implementing artificial intelligence tools in investment decision support systems, and in this regard it is asserted that such integration of intelligent agents is viewed not only and not so much as a replacement for traditional expert judgment, but rather as a verification method. In this context, the use of AI capabilities implies an expansion of the cognitive abilities of decision-makers. The need to take into account the time structure of the profitability of digital investments, which is characterized by a lagging and cumulative (accumulative) effect, has been analyzed. In the final part of the article, based on the results of the analysis, conclusions are formulated regarding the need for a fundamental restructuring of the foundations of investment management, and the necessity of transitioning from deterministic and linear models to probabilistic and scenario-based approaches is substantiated.