Kazan, Kazan, Russian Federation
Kazan', Kazan, Russian Federation
VAK Russia 5.2.3
VAK Russia 5.2.4
VAK Russia 5.2.5
VAK Russia 5.2.6
VAK Russia 5.2.7
UDC 336.2
UDC 004.8
UDC 631
The article explores the practical possibilities of using artificial intelligence technologies in the processes of settlements with the budget for taxes and fees at enterprises of the agro-industrial complex of the Russian Federation. It is shown that in this subject area the greatest effect is achieved not by replacing the specified tax calculation, but by improving the quality of initial data, intelligent processing of primary documents, automation of control procedures, identifying anomalies and predicting the total tax burden in a single tax account. Based on the analysis of the Tax Code of the Russian Federation, materials of the Federal Tax Service of Russia, acts in the field of personal data and information security, as well as modern Russian studies on the digitalization of tax administration and taxation of the agro-industrial complex, the principles of using AI in the tax contour of agricultural organizations are formulated. It is justified that seasonality, documentary capacity of expenses, the use of unified agricultural standards and the need for constant linking of production facts with accounting and tax accounting are of particular importance for agricultural enterprises. An applied approach to the implementation of AI tools in the tax function is proposed, including intelligent processing of primary documentation, automated classification of operations, risk analytics and forecasting of liabilities for liquidity management purposes. It was concluded that AI in the tax sphere of the agro-industrial complex should develop as a tool for compliance and risk manageability, and not as an autonomous mechanism for making legally significant decisions.
tax accounting, digitalization of tax administration, artificial intelligence, budget settlements, unified tax account, agro-industrial complex, unified agricultural tax system, tax risks, OCR, machine learning, forecasting
1. Vliyanie cifrovizacii ekonomiki na nalogooblozhenie predpriyatiy APK / G.S. Klychova, A.S. Klychova, S.V. Kozmenkova, G.F. Sattarova // Professiya buhgaltera - vazhneyshiy instrument effektivnogo upravleniya sel'skohozyaystvennym proizvodstvom: sbornik nauchnyh trudov po materialam VIII Mezhdunarodnoy nauchno-prakticheskoy konferencii, posvyaschennoy pamyati professora V.P. Petrova, Kazan', 19 maya 2020 goda. – Kazan': Kazanskiy gosudarstvennyy agrarnyy universitet, 2020. – S. 145-153.
2. Fahretdinova, E. N. Cifrovizaciya - klyuchevoy faktor strategicheskogo razvitiya agropromyshlennogo kompleksa / E. N. Fahretdinova // Agrarnaya nauka XXI veka. Aktual'nye issledovaniya i perspektivy: Trudy III mezhdunarodnoy nauchno-prakticheskoy konferencii, Kazan', 22 13 maya 2019 goda. – Kazan': Kazanskiy gosudarstvennyy agrarnyy universitet, 2019. – S. 437-441.
3. Edinyy nalogovyy schet (ENS) // Federal'naya nalogovaya sluzhba Rossii: ofic. sayt.
4. Ryabinina, N. I. Osobennosti nalogooblozheniya predpriyatiy APK i nalogovye riski sel'hozproizvoditeley v Rossii / N. I. Ryabinina, N. A. Turanceva // Ekonomika, predprinimatel'stvo i pravo. – 2018. – T. 8, № 4. – S. 203-212.
5. Beresneva A. V. OSOBENNOSTI NALOGOOBLOZhENIYa PREDPRIYaTIY AGROPROMYShLENNOGO KOMPLEKSA // Ekonomika i socium. 2021. – C. 435-438.
6. Andrianova N.G. Iskusstvennyy intellekt v nalogovom kontrole: problemy i perspektivy pravovogo regulirovaniya // Problemy ekonomiki i yuridicheskoy praktiki. – 2025. – S. 22-31.
7. Davletov, A. R. Sovremennye metody mashinnogo obucheniya i tehnologiya OCR dlya avtomatizacii obrabotki dokumentov / A. R. Davletov // Vestnik nauki. – 2023. – S. 676 – 698.
8. Nikitina O.A. Sravnitel'nyy analiz metodov NLP dlya klassifikacii i klasterizacii korporativnyh dokumentov / O. A. Nikitina // Vestnik nauki. – 2025. – T. 3, № 12(93). – S. 1355-1361.
9. Andrianova N.G. Cifrovizaciya kontrolya za uplatoy naloga na dobavlennuyu stoimost' s ispol'zovaniem iskusstvennogo intellekta: problemy i perspektivy // Nalogi i nalogooblozhenie. 2025. – S. 46-55.
10. Mel'nikov, A. B. Vliyanie cifrovizacii na APK: analiz tekuschego sostoyaniya i perspektivy razvitiya / A. B. Mel'nikov, E. G. Scherbina // Obespechenie prodovol'stvennoy bezopasnosti Rossii v usloviyah formirovaniya novogo tehnologicheskogo uklada : Sbornik materialov i dokladov I Mezhdunarodnoy nauchno-prakticheskoy konferencii, posvyaschennoy 65-letiyu ekonomicheskogo fakul'teta, Krasnodar, 14–16 aprelya 2025 goda. – Krasnodar: IP Alzidan M., 2025. – S. 340-347.
11. Babalykova, I. A. Iskusstvennyy intellekt i mashinnoe obuchenie v buhgalterskom uchete / I. A. Babalykova, I. V. Dyadyurin, M. A. Volkov // Vestnik Akademii znaniy. – 2025. – № 2(67). – S. 104-107.
12. Cifrovizaciya nalogovogo administrirovaniya kak instrument povysheniya effektivnosti nalogovoy politiki / S. A. Aleksahina, A. A. Gorshkova, N. A. Ozerova, E. N. Nohtueva // Ekonomika, predprinimatel'stvo i pravo. – 2024. – T. 14, № 12. – S. 7079-7094.
13. Edinyy nalogovyy schet (ENS) // Federal'naya nalogovaya sluzhba Rossii: ofic. sayt.
14. Edinyy sel'skohozyaystvennyy nalog (ESHN) // Federal'naya nalogovaya sluzhba Rossii: ofic. sayt.
15. Nalogovaya ispol'zuet tehnologii iskusstvennogo intellekta dlya vyyavleniya neplatel'schikov NDS // Federal'naya nalogovaya sluzhba Rossii. – 26.07.2022.
16. Oleynik, M. A. Audit raschetov s byudzhetom po nalogam sel'skohozyaystvennyh organizaciy / M. A. Oleynik, Yu. N. Shol', E. S. Zaharova // Estestvenno-gumanitarnye issledovaniya. – 2020. – № 27(1). – S. 291-298.
17. O personal'nyh dannyh: feder. zakon ot 27.07.2006 № 152-FZ // Oficial'nyy internet-portal pravovoy informacii.
18. O Federal'noy gosudarstvennoy informacionnoy sisteme proslezhivaemosti zerna i produktov pererabotki zerna: postanovlenie Pravitel'stva RF ot 09.10.2021 № 1722.
19. Krasilyuk, A. Yu. Ispol'zovanie iskusstvennogo intellekta v nalogovoy sfere / A. Yu. Krasilyuk, A. A. Plaksin // Al'manah molodogo issledovatelya. – 2023. – № 15. – S. 221-225.
20. Suglobov A.E. Aktual'nye tendencii i problemy primeneniya rezhima avtomatizirovannoy uproschennoy sistemy nalogooblozheniya (AUSN) v RF / Suglobov A.E., Minakov A.V. // Russian Journal of Management. 2026. T. 14. № 2. S. 179-195.
21. Orlova E.A. Analiz nalogovoy nagruzki predpriyatiy malogo i srednego biznesa v razreze sub'ektov RF / Orlova E.A., Suglobova S.A. // Russian Journal of Management. 2025. T. 13. № 10. S. 119-130.
22. Demina I.D. Social'no-ekologicheskie faktory v korporativnoy otchetnosti organizaciy apk: ocenka i obespechenie dostovernosti / Demina I.D., Dombrovskaya E.N., Gordova M., Suglobova S.A. // Ekonomika, trud, upravlenie v sel'skom hozyaystve. 2026. № 2 (133). S. 17-27.
