Assessing the economic efficiency of digital investments in the regional agro-industrial complex

Background. In the context of geopolitical instability, sanctions pressure and the desire for technological sovereignty, digitalization of the agro‑industrial complex (AIC) is coming to the fore as a strategic priority of state policy. The national project “Technological provision of food security”, launched in 2025, provides for the investment of 1 trillion rubles by 2030 in order to increase the efficiency, import independence and technological independence of the industry. However, despite the growth in investment volumes — more than 30 % of agricultural enterprises are already implementing digital solutions — there is no unified methodology for assessing their economic efficiency, taking into account regional specifics, high capital intensity and uncertainty of the external environment. Existing approaches, focused mainly on static calculations (payback period, efficiency coefficient), do not allow for an adequate assessment of multi‑variant development scenarios and the long‑term effect of the introduction of digital technologies. This problem is particularly acute in the Siberian regions, where difficult climatic conditions, staff shortages and insufficient digital infrastructure require a special approach to investment management. Under these conditions, the formation of scientifically based tools for evaluating the effectiveness of digital investments becomes a prerequisite for the rational use of budgetary and private resources and ensuring the sustainable development of the agricultural sector at the regional level. Purpose. The aim is to develop and test a methodological approach to assessing the economic efficiency of investments in the digitalization of the regional agro‑industrial complex, taking into account the uncertainty of the external environment. Materials and methods. The work uses system, structural, dynamic and coefficient analysis, correlation and regression modeling and scenario approach. The empirical basis was data from Rosstat, the Ministry of Agriculture of the Russian Federation and the authorities of the Novosibirsk region for 2018–2023. The author’s methodological approach is proposed based on the formation of three scenarios (expected, optimistic, pessimistic), the normalization of standard financial indicators (NPV, IRR, ROI, payback period) and the calculation of a complex integral performance indicator. Results. Empirical analysis revealed a steady positive trend in investment activity in the agro‑industrial complex of the Novosibirsk region. More than 10 major investment projects are implemented annually in the region, with the total investment volume reaching 70 billion rubles in 2023. Special attention is paid to equipping enterprises with modern digital equipment: during the analyzed period, the region’s farmers purchased machinery and equipment worth 6.5 billion rubles, of which 1.4 billion rubles were compensated from the regional budget. An entropy analysis conducted taking into account the digitalization coefficient showed that in 2021–2023 there was an abrupt increase in investment activity (3.1 times in agriculture and 12.2 times in processing), which led to a decrease in the entropy coefficient and, as a result, to an increase in the manageability of investment policy. Based on the analysis, the author’s methodological approach to assessing economic efficiency was developed and tested. Its core is scenario modeling, which allows not only to choose the most likely outcome, but also to obtain a balanced assessment that takes into account all possible scenarios. The simulation results demonstrated the high economic feasibility of investing in the digitalization of the agro‑industrial complex of the region. Under the main (expected) scenario, with a total investment of 81.7 billion rubles, the effectiveness of the investment policy amounted to 112.94 %. This means that each invested ruble generates 1.1294 rubles of economic effect. At the same time, the total amount of resource savings (including labor, energy, materials) is estimated at 2.51 billion rubles, and the total economic effect from the implementation of the scenario is 9.36 billion rubles. The structure of optimal investments in this scenario is distributed as follows: 26.3 % — in cultivation, 72.3 % — in processing, and only 1.4 % — directly in the purchase of digital technology and equipment. This paradoxical result is explained by the fact that digital technologies are a catalyst for efficiency, but their maximum effect is achieved precisely in capital‑intensive and labor‑intensive processing processes, where significant synergistic effects are possible. The optimistic scenario, assuming a favorable macroeconomic environment and a high willingness of personnel to innovate, demonstrates even greater potential. With an investment volume of 92.0 billion rubles, efficiency increases to 114.03 %, and the total economic effect reaches 11.32 billion rubles. This scenario confirms that if favorable conditions are created, the agro‑industrial complex of the region is capable of accelerated growth. On the contrary, the pessimistic scenario, which models conditions of economic instability and reduced government support, shows that even in adverse conditions, investments in digitalization remain profitable. With a decrease in investments to 62.0 billion rubles, the efficiency is still 110.7 %, and the economic effect is 5.99 billion rubles. This key finding confirms the sustainability and strategic importance of digital investments for ensuring food security in the region. A special value of the developed methodology is its ability to solve not only direct, but also inverse forecasting problems. Direct forecasting allows you to assess the consequences of a given amount of investment. Reverse forecasting, on the contrary, allows us to determine the necessary amount of investment to achieve specific targets. For example, to fulfill one of the key objectives of the national project — to increase food production by 30 % by 2026 (to 247.9 billion rubles) — it is necessary to increase investments from 54.12 to 58.925 billion rubles. A comparative analysis of the scenarios shows that the optimistic scenario exceeds the baseline (expected) potential by 9.63 %, while the pessimistic one reaches only 64 % of the baseline level. This gives a complete picture of the range of possible outcomes and allows you to form flexible, adaptive strategies. For an investor, such an analysis reduces risks by providing a clear understanding of break‑even points and growth potential. For the state regulator, it serves as the basis for developing targeted support measures aimed at minimizing the negative consequences of a pessimistic scenario and creating conditions for the implementation of an optimistic one. Thus, the results obtained not only confirm the hypothesis of high efficiency of digital investments in the regional agro‑industrial complex, but also provide scientifically sound, practically applicable tools for their quantitative assessment and management in conditions of uncertainty.