Economic aspects of applying artificial intelligence models in the sustainable development of Russian bioeconomy clusters
Year: 2026
Type: article
Abstract: The article examines the economic aspects of applying artificial intelligence models in the sustainable development of Russian bioeconomy clusters. It is shown that in the bioeconomy intelligent models do not generate effects by themselves; their value emerges through changes in resource decision quality, including more accurate forecasting, better coordination of biomass flows and processing capacities, deeper biomass valorization, faster managerial response to deviations, and stronger resilience to external constraints. The paper argues that in the Russian context the key role belongs not to universal digital tools but to models adapted to territorial unevenness of the resource base, variability in biomass quality, infrastructure limitations, biological safety requirements, and technological autonomy goals. Based on Russian and foreign studies, the author proposes a typology of artificial intelligence models in the bioeconomy, including predictive, optimization, coordination, circular, and resilience-oriented models. It is demonstrated that the economic effect of such models is manifested through five channels: value added growth, lower resource intensity, lower logistics and transaction costs, greater reuse of by-products, and higher cluster resilience to shocks. As an original contribution, the article develops a coefficient of economic sustainability of artificial intelligence application and an index of intelligent resource management maturity. The paper concludes that in the Russian bioeconomy the priority should be given not to the broadest possible implementation of artificial intelligence, but to economically targeted adoption, when the type of model is selected according to a specific source of economic effect and does not break the link between production efficiency, resource reproducibility, and safety requirements.
Source: Market economy problems
Language: English
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W7204861359