A SYSTEMIC APPROACH TO THE DIGITAL TRANSFORMATION OF AGRICULTURAL PRODUCTION: DEFINITION AND STRUCTURAL-FUNCTIONAL CLASSIFICATION
Abstract
The article explores the systemic aspects of the digital transformation of the agricultural sector, with a specific focus on innovative information and communication technologies. The study analyses the main directions of digitalisation, from sensor networks and data collection platforms to systems of automation, analytics, and decision-making in agricultural production. Particular attention is given to the integration and interaction of these technologies within a unified digital ecosystem that encompasses the entire production and management cycle. A new author’s definition of the concept of “innovative digital technologies in the agricultural sector” is proposed. This definition emphasises the integrative, adaptive, and systemic nature of such technologies, highlighting their ability to transform traditional agribusiness models into intelligent, data-driven, and resource-efficient systems. Based on this definition, a comprehensive classification of digital solutions is developed, which considers their functional roles, technological foundations, and sectoral specificity. The article also outlines the key benefits of digitalisation for agriculture, including increased operational efficiency, improved productivity, enhanced environmental sustainability, and better-informed decision-making. In addition, the study identifies the main challenges of digital transformation in the agrarian context, such as limited access to infrastructure, low digital literacy among rural populations, high implementation costs, and the lack of a unified strategic approach at the state level. The study’s findings are relevant to both academic research and practical applications. They can serve as a methodological foundation for assessing the digital maturity of agricultural enterprises, designing digital transformation roadmaps, and shaping policies that support the development and diffusion of innovative technologies in the agri-food sector. By providing a structured framework for the understanding and classification of digital innovations, the article contributes to the formation of a theoretical and analytical base for further exploration of digital agriculture in conditions of economic, technological, and climate uncertainty.
References
Космідайло І. В., Маковійчук О. В. Можливості використання цифрових платформ в управлінні сільським господарством в Україні на основі передового зарубіжного досвіду. Вісник академії праці, соціальних відносин і туризму. Серія: економіка, психологія та управління. 2025. № 3. DOI: https://doi.org/10.54929/3041-2390-2025-03-01-03
Саулко Д. П. Трансформаційний потенціал смарт-промисловості в аграрному секторі економіки України. Ефективна економіка. 2024. № 11. DOI: https://doi.org/10.32702/2307-2105.2024.11.102
Шевченко А. А., Петренко О. П., Косик Д. В. Штучний інтелект в рослинництві: успішні кейси аграрних підприємств. Modern Economics. 2024. № 47(2024). С. 130-137. DOI: https://doi.org/10.31521/modecon.V47(2024)-19
Ahamed N. N., Vignesh R. (01.01.2022) Smart Agriculture and Food Industry with Blockchain and Artificial Intelligence. Journal of Computer Science, vol. 18, pp. 1–17. DOI: https://doi.org/10.3844/jcssp.2022.1.17
Bahn R. A., Yehya A. A. K., Zurayk R. (2021) Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region. Sustainability, vol. 13, № 6, pp. 1-24. DOI: https://doi.org/10.3390/su13063223
Bezpartochnyi M., Britchenko I. (2022) Digitalization for agriculture and rural development in Ukraine. 23rd International Scientific Conference. “Economic Science for Rural Development 2022” (Latvia, Jelgava, May 11th-13th, 2022) №56. Latvia, Jelgava: LLU Esaf, pp. 398-406. DOI: https://doi.org/10.22616/ESRD.2022.56.039
Cavazza A., Mas F. D., Paoloni P., Manzo M. (2023) Artificial intelligence and new business models in agriculture: a structured literature review and future research agenda. British Food Journal, vol. 125, № 13, pp. 436–461. DOI: https://doi.org/10.1108/BFJ-02-2023-0132
Elbasi E., Mostafa N., AlArnaout Z. et al (2022) Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review. IEEE Access, vol. 11, pp. 171–202. DOI: https://doi.org/10.1109/ACCESS.2022.3232485
Global Digital Agriculture Market Size and Forecast – 2025-2032. Coherent Market Insights. URL: https://www.coherentmarketinsights.com/industry-reports/digital-agriculture-market (дата звернення: 03.08.2025)
Kovalova M., Valentinov V., Gagalyuk T. (2025) Societal value creation through digital technologies: Insights from stakeholder collaborations of Ukrainian agroholdings. International Food and Agribusiness Management Review, vol. 28(8), № 3, pp. 580–598. DOI: https://doi.org/10.22434/ifamr.1277
Kussul N., Shelestov A., Yailymov B. et al. (2025) Assessment of war-induced agricultural land use changes in Ukraine using machine learning applied to Sentinel satellite data. International Journal of Applied Earth Observation and Geoinformation, vol. 140, pp. 1-24. DOI: https://doi.org/10.1016/j.jag.2025.104551
Lochan K., Khan A., Elsayed I. et al. (2016) Advancements in Precision Spraying of Agricultural Robots: A Comprehensive Review. IEEE Access, vol. 4, pp. 1-34. DOI: https://doi.org/10.1109/ACCESS.2024.3450904
Mana A., Allouhi A., Hamrani A. et al. (2024) Sustainable AI-Based Production Agriculture: Exploring AI Applications and Implications in Agricultural Practices. Smart Agricultural Technology, vol. 7(7664), pp. 1-15. DOI: https://doi.org/10.1016/j.atech.2024.100416
Oliveira R. C. d., Silva R. D. d. S. e. (2023) Artificial Intelligence in Agriculture: Benefits, Challenges, and Trends. Applied Sciences, vol. 13, № 13, pp. 1-17. DOI: https://doi.org/10.3390/app13137405
Peladarinos N., Piromalis D., Cheimaras V. et al. Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review. Sensors. Vol. 23, 11.08.2023. P. 7128. DOI: https://doi.org/10.3390/s23167128
Rani R., Sahoo J., Bellamkonda S. et al. (2023) Role of Artificial Intelligence in Agriculture: An Analysis and Advancements With Focus on Plant Diseases. IEEE Access, vol. 11, pp. 137999–138019. DOI: https://doi.org/10.1109/ACCESS.2023.3339375
Roy M., Medhekar A. (2025) Transforming smart farming for sustainability through agri-tech Innovations: Insights from the Australian agricultural landscape. Farming System, vol. 3, pp. 1-16. DOI: https://doi.org/10.1016/j.farsys.2025.100165
Kosmidailo I. V., Makoviichuk O. V. (2025) Mozhlyvosti vykorystannia tsyfrovykh platform v upravlinni silskym hospodarstvom v Ukraini na osnovi peredovoho zarubizhnoho dosvidu [Opportunities for using digital platforms in agricultural management in Ukraine based on advanced foreign experience.] Visnyk akademii pratsi, sotsialnykh vidnosyn i turyzmu. Seriia: ekonomika, psykholohiia ta upravlinnia – Bulletin of the Academy of Labor, Social Relations, and Tourism. Series: Economics, Psychology, and Management, vol. 3. DOI: https://doi.org/10.54929/3041-2390-2025-03-01-03
Saulko D. P. (2024) Transformatsiinyi potentsial smart-promyslovosti v ahrarnomu sektori ekonomiky Ukrainy [The transformational potential of smart industry in Ukraine's agricultural sector]. Efektyvna ekonomika – Efficient economy, vol. 11. DOI: http://doi.org/10.32702/2307-2105.2024.11.102
Shevchenko A. A., Petrenko O. P., Kosyk D. V. (2024) Shtuchnyi intelekt v roslynnytstvi: uspishni keisy ahrarnykh pidpryiemstv [Artificial intelligence in crop production: successful cases of agricultural enterprises]. Modern Economics, vol. 47(2024), pp. 130-137. DOI: https://doi.org/10.31521/modecon.V47(2024)-19
Ahamed N. N., Vignesh R. (2022) Smart Agriculture and Food Industry with Blockchain and Artificial Intelligence. Journal of Computer Science, vol. 18, pp. 1–17. DOI: https://doi.org/10.3844/jcssp.2022.1.17
Bahn R. A., Yehya A. A. K., Zurayk R. (2021) Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region. Sustainability, vol. 13, № 6, pp. 1-24. DOI: https://doi.org/10.3390/su13063223
Bezpartochnyi M., Britchenko I. (2022) Digitalization for agriculture and rural development in Ukraine. 23rd International Scientific Conference. “Economic Science for Rural Development 2022” (Latvia, Jelgava, May 11th-13th, 2022) №56. Latvia, Jelgava: LLU Esaf, pp. 398-406. DOI: https://doi.org/10.22616/ESRD.2022.56.039
Cavazza A., Mas F. D., Paoloni P., Manzo M. (2023) Artificial intelligence and new business models in agriculture: a structured literature review and future research agenda. British Food Journal, vol. 125, № 13, pp. 436–461. DOI: https://doi.org/10.1108/BFJ-02-2023-0132
Elbasi E., Mostafa N., AlArnaout Z. et al (2022) Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review. IEEE Access, vol. 11, pp. 171–202. DOI: https://doi.org/10.1109/ACCESS.2022.3232485
Global Digital Agriculture Market Size and Forecast – 2025-2032. Coherent Market Insights. URL: https://www.coherentmarketinsights.com/industry-reports/digital-agriculture-market (accessed August 03, 2025)
Kovalova M., Valentinov V., Gagalyuk T. (2025) Societal value creation through digital technologies: Insights from stakeholder collaborations of Ukrainian agroholdings. International Food and Agribusiness Management Review, vol. 28(8), № 3, pp. 580–598. DOI: https://doi.org/10.22434/ifamr.1277
Kussul N., Shelestov A., Yailymov B. et al. (2025) Assessment of war-induced agricultural land use changes in Ukraine using machine learning applied to Sentinel satellite data. International Journal of Applied Earth Observation and Geoinformation, vol. 140, pp. 1-24. DOI: https://doi.org/10.1016/j.jag.2025.104551
Lochan K., Khan A., Elsayed I. et al. (2016) Advancements in Precision Spraying of Agricultural Robots: A Comprehensive Review. IEEE Access, vol. 4, pp. 1-34. DOI: https://doi.org/10.1109/ACCESS.2024.3450904
Mana A., Allouhi A., Hamrani A. et al. (2024) Sustainable AI-Based Production Agriculture: Exploring AI Applications and Implications in Agricultural Practices. Smart Agricultural Technology, vol. 7(7664), pp. 1-15. DOI: https://doi.org/10.1016/j.atech.2024.100416
Oliveira R. C. d., Silva R. D. d. S. e. (2023) Artificial Intelligence in Agriculture: Benefits, Challenges, and Trends. Applied Sciences, vol. 13, № 13, pp. 1-17. DOI: https://doi.org/10.3390/app13137405
Peladarinos N., Piromalis D., Cheimaras V. et al. Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review. Sensors. Vol. 23, 11.08.2023. P. 7128. DOI: https://doi.org/10.3390/s23167128
Rani R., Sahoo J., Bellamkonda S. et al. (2023) Role of Artificial Intelligence in Agriculture: An Analysis and Advancements With Focus on Plant Diseases. IEEE Access, vol. 11, pp. 137999–138019. DOI: https://doi.org/10.1109/ACCESS.2023.3339375
Roy M., Medhekar A. (2025) Transforming smart farming for sustainability through agri-tech Innovations: Insights from the Australian agricultural landscape. Farming System, vol. 3, pp. 1-16. DOI: https://doi.org/10.1016/j.farsys.2025.100165
Copyright (c) 2025 Вадим Колісніченко
This work is licensed under a Creative Commons Attribution 4.0 International License.
