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Improving Food Market Infrastructure Through the Application of Artificial General Intelligence Technologies

Year: 2026

Type: article

Abstract: The article examines the improvement of food market infrastructure through the strategic application of Artificial General Intelligence (AGI) technologies. The study deeply analyses the operational limitations of conventional retrospective market analytics and proposes a novel, data-driven methodology for integrating advanced AGI systems into food production cycles. The scientific novelty of this research consists in developing a closed-loop AGI platform architecture specifically designed to forecast dynamic consumer preferences over a five-year horizon and to generate evidence-based production recommendations for food enterprises in the Kyrgyz Republic. Furthermore, the paper investigates how this intelligent platform optimizes supply chain logistics, reduces food waste, and mitigates market supply fluctuations under volatile economic conditions. By leveraging predictive modeling and machine learning algorithms, the proposed system enhances decision-making transparency and boosts competitiveness within the regional agro-industrial sector. Ultimately, the comprehensive findings and structured implementation frameworks provide valuable strategic guidelines for policymakers and industry stakeholders to ensure national food security and sustainable economic growth.

Source: Journal of "Practical problems of economics and finance"

DOI: 10.65164/d0tm5f46

Authors: Abdilbaet Mamasydykov, Perizat Alisheva, Maksatbek Sulaimankulov

Institution: Kyrgyz-Uzbek International University named after Batyraly Sydykov

Language: English

Topic: Impact of AI and Big Data on Business and Society

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Zero hunger

Open Access status: hybrid

OpenAlex ID: W7166804628

FWCI:

Cites: 1

Cited by:

Related to: 10