Adoption of intelligent technologies in the BRICS+ agricultural sector: determinants and forecasts

O. T. Ergunova, E. G. Kiseleva, A. G. Somov

Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia

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Volume 26 No. 9

Date of paper submission: 07.08.2025, date of review: 22.04.2026 date of acceptance: 05.06.2026.

Published: 09/30/2026

Abstract. Paper examines the digital transformation of the agricultural sector in BRICS+ countries, focusing on the adoption of automation, intelligent systems, and artificial intelligence technologies. The purpose of the study is to identify the key determinants of agricultural digitalization in BRICS+ economies and to assess future development trends. Methods. The research methodology integrates comparative analysis of cross-country statistical data, the CRITIC multi-criteria weighting method, and trend-based linear extrapolation. This approach enables the identification of dominant drivers of digital transformation and the evaluation of their prospective dynamics. Results. The findings demonstrate that the level of agricultural digital development in BRICS+ countries is primarily influenced by ICT penetration, investment in research and development, and the digital literacy of the agricultural workforce. Significant heterogeneity in technological readiness is observed: China and Brazil lead in the adoption of precision agriculture, covering 15.3 % and 13.5 % of agricultural land, respectively, while Ethiopia remains substantially behind, with adoption rates below 1 %. Forecast results indicate a sustained increase in investments in digital infrastructure, a growing dependence of agricultural productivity on technological advancement, and the emergence of structural conditions that may intensify digital inequality across BRICS+ countries. The scientific novelty of the study lies in the empirical identification of differentiated structural, investment, and human capital drivers of agricultural digitalization, as well as in revealing heterogeneous transformation mechanisms under varying levels of technological readiness and institutional development within the BRICS+ framework. The results may inform public policy design in agrotechnology and support international scientific and technological cooperation initiatives.

Keywords: digital technologies, intelligent technologies, agriculture, forecasting, agricultural sector, BRICS countries, innovations

For citation: Ergunova O. T., Kiseleva E. G., Somov A. G. Adoption of intelligent technologies in the BRICS+ agricultural sector: determinants and forecasts. Agrarian Bulletin of the Urals. 2026; 26 (09): 1783‒1803. https://doi.org/10.32417/1997-4868-2026-26-09-1783-1803 (In Russ.)  

 

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