The impact of digital platforms and artificial intelligence capabilities on product sales by small farms

Mukhanova G. Uashov G. Akhmetzhanova A. Malayeva R. Ploshay A.
26 June 2025 Polissia National University

Scientific Horizons
2025 #28 Issue 6 129 - 149 pp.

The aim of the study was to assess the impact of digital platforms and artificial intelligence technologies on the sales efficiency of agricultural products by small farming households in Kazakhstan, compared with the experience of Central Asian countries and global practices. The study was conducted from March 2023 to February 2025 in 14 regions of the Republic of Kazakhstan using a comprehensive methodology, including a stratified random sample, structured interviews with managers of 324 small farming households (with up to 10 employees and an annual turnover not exceeding 30 million tenge), and 27 expert interviews with representatives of 8 digital platforms (AgroSmart.kz, Egistic, DigiField, QazFarm, AgroMap, Agroplatforma.kz, Agro.kz, Farm.kz). ANOVA, regression, and correlation analysis were performed, as well as machine learning methods (Random Forest, XGBoost) used for developing a predictive model. Statistical data analysis showed that the introduction of digital tools enabled an average sales increase of 27.3% with a reduction in intermediary costs of 18.6%. The highest efficiency was demonstrated by households using a combination of local trading platforms (AgroSmart.kz, Agro.kz) and specialised demand forecasting services. Regional analysis revealed significant differences in the level of digitalisation: in southern regions (Turkestan, Zhetysu), 64.2% of farmers regularly used at least two digital sales channels, whereas in the northern regions (Kostanay, North Kazakhstan), this figure was only 38.7%. The predictive model developed using machine learning algorithms showed a forecasting accuracy for seasonal demand fluctuations of 87.4% when tested on historical data from 2018-2023. The pilot implementation of the developed recommendations in the activities of 23 small farming households resulted in an average revenue increase of 31.5% and a 43.2% reduction in time spent searching for buyers. The study proved the economic feasibility of introducing digital tools into the practice of small farming households in Kazakhstan, even with a limited digitalisation budget.

agro-industrial complex , demanforecasting model , digital platforms , Kazakhstan , machine learning , sales efficiency , small farming households

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Astana IT University, 55/11 Mangilik El Ave., Astana, 010000, Kazakhstan
Narxoz University, 55 Zhandosov Str., Almaty, 050035, Kazakhstan
ALT University named after M. Tynyshpaev, 97 Shevchenko Str., Almaty, 050012, Kazakhstan
Kurmangazy Kazakh National Conservatory 05000, 86 Abylai-Khan Ave, Almaty, Kazakhstan
Economic Sciences International Transport and Humanities University, 32A Zhetisu-1 microdistrict, Almaty, 050063, Kazakhstan

Astana IT University
Narxoz University
ALT University named after M. Tynyshpaev
Kurmangazy Kazakh National Conservatory 05000
Economic Sciences International Transport and Humanities University

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