Naida Andrii, PhD (Economics), Associate Professor of the Department of Accounting and Taxation, Odesa State Agrarian University, Odesa, Ukraine

ORCID ID: 0000-0002-6371-1382
e-mail: andrew.od2017@gmail.com

Kryukova Irina, Doctor of Economics, Professor, Head of the Department of Accounting and Taxes, Odessa State Agrarian University, Odessa, Ukraine

ORCID ID: 0000-0002-0577-6364
e-mail: kryukovaia1@gmail.com

Selivanova Natalia, PhD (Economics),  Associate Professor of the Department of Accounting, Analysis and Audit, Odesa Polytechnic National University, Odesa, Ukraine

ORCID ID: 0000-0002-4157-4946
e-mail: n.selivanova.odessa@gmail.com

Hnatieva Tetiana, PhD (Economics),  Associate Professor of the Department of Accounting and Taxation, Odesa State Agrarian University, Odesa, Ukraine

ORCID ID: 0000-0001-6071-0889
e-mail: hnatieva_tn@ukr.net

Implementation of Artificial Intelligence Technologies in the Accounting and Analytical Support of Agricultural Enterprises

Abstract. Introduction. Effective management, planning, and decision-making require accounting and analytical support for agricultural enterprises. In the context of the ongoing digital transformation of the economy, integrating advanced technologies — particularly artificial intelligence (AI) — into accounting and economic analysis has become crucial. The growing volume of data, the need for prompt processing, the desire to minimize human error, and the demand for accurate financial and economic indicator forecasting necessitate the implementation of AI technologies in accounting and analytical support for agricultural enterprises.

The methodological and theoretical basis of the article comprises the works of leading foreign and domestic scholars in the fields of e-commerce, the digital economy, and marketplace business modeling. To achieve the research objectives, the following scientific methods were applied: analysis and synthesis (to generalize international experience), structural-functional analysis (to assess marketplace operational mechanisms), comparative analysis (to identify differences between Ukrainian and international platforms), and a systemic approach (to determine transformation pathways for marketplaces in Ukraine). The justification of theoretical conclusions and explanations was carried out using structural and system-functional approaches to analyzing and evaluating marketplace transformation models. The information base of the research includes scientific publications, research reports, monographs, and materials from open-access databases.

Purpose. The purpose of the article is to identify the prospects and directions for implementing artificial intelligence technologies in the accounting and analytical support of agricultural enterprises.

Results. The scientific study involved an in-depth analysis of the theoretical foundations, current state, and prospects for implementing artificial intelligence (AI) in accounting and analytical systems within enterprise operations. The study revealed that the digital transformation of business processes is not a temporary trend, but rather an objective necessity driving fundamental changes in accounting, financial analysis, and managerial decision-making approaches.

AI serves as a tool capable of elevating the enterprise’s accounting function to a new level. AI’s capabilities, such as processing large volumes of data, detecting anomalies, forecasting trends, and generating recommendations, enable the transition from reactive to proactive enterprise management.

Conclusions. Artificial intelligence has the potential to transform the accounting and analytical functions of enterprises, making them more efficient, innovative, and valuable for strategic business development. Successful integration of these technologies will provide agricultural enterprises with economic advantages and strengthen their position in the competitive global digital economy.

The implementation of AI technologies in agricultural enterprises can enhance the accuracy of forecasting production and financial indicators, reduce risks through timely threat detection, accelerate managerial decision-making, improve the transparency and controllability of business processes, and lay the foundation for the digital transformation of agribusiness.

Keywords: artificial intelligence; accounting and analytical provision; agricultural enterprises; implementation.

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