Convergence of human and artificial intelligence as a driver of modernisation of fiscal stimulation in the agricultural sector

Анотація

Introduction. In the context of ongoing digital transformation of the economy, increasing complexity of socio-economic processes, and the intensification of wartime and post-war challenges, the issue of enhancing the effectiveness of fiscal policy – particularly in stimulating the agricultural sector – has become critically important. Traditional instruments of state support are losing their effectiveness under conditions of high uncertainty, which necessitates their intellectualisation through the application of advanced digital technologies. In this context, the convergence of human and artificial intelligence emerges as a new paradigm for the development of adaptive and effective managerial decisions within the system of fiscal stimulation of the agricultural sector. Aim. The aim of the article is to examine the theoretical foundations and substantiate practical approaches to the modernisation of fiscal stimulation of the agricultural sector based on the convergence of human and artificial intelligence, with the identification of key influencing factors in the context of sustainable development of Ukraine’s agricultural sector, and the development of a conceptual model for evaluating the effectiveness of their interaction. Methods (Methodology). The study employs the dialectical method, methods of theoretical generalisation, systematisation, and comparative analysis, as well as structural-logical and graphical modelling methods. The methodological foundation is based on the principles of fiscal policy theory, institutional economics, the concept of sustainable development, and approaches to the digital transformation of the agricultural sector. Results. The article substantiates the essence and role of the convergence of human and artificial intelligence as a driver of modernisation of fiscal stimulation in the agricultural sector. A conceptual graphical model is developed, reflecting the nonlinear relationship between the level of convergence of human and artificial intelligence and the effectiveness of fiscal stimulation over time, taking into account the influence of endogenous and exogenous factors. It is demonstrated that the effectiveness of fiscal policy is determined not only by the level of digitalisation but primarily by the quality of interaction between human and artificial intelligence and the ability to ensure their optimal configuration. Directions for enhancing the effectiveness of fiscal stimulation in the agricultural sector are proposed, based on the implementation of intelligent decision-making approaches.

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