Reinventing Conservation Agriculture with Artificial Intelligent Systems: A Review

Conservation Agriculture (CA) has become a new sustainable management model, which improves the health of soils, increases the efficiency of resource use and guarantees the agricultural productivity in the long run. None the less, the agricultural sector is becoming the victim of the climate change, soil erosion, water shortages and food insecurity. Machine learning and computer system vision are the core features of Artificial Intelligence (AI), which can offer new data-driven solutions to these issues and reinforce sustainable agriculture systems. A systematic literature review was conducted through the process of locating peer-reviewed articles and reports, which were published in 2015–2024. The Artificial Intelligence, Conservation agriculture and precision farming keywords had been used to get the related studies in dataset like Scopus, google scholar and web of science. The literature chosen was examined in terms of theme to evaluate the implementation of AI in soil management, crop production and climate resilience. The results reveal that conservation Agriculture as represented by limited soil disturbance, crop and permanent soil cover rotation practice has good implications on soil sustainability. The PI technologies also introduce precision to the systems of resource management, real-time crop monitoring, detection of diseases and pests, yield prediction, as well as climate-directed decision-making. An AI-CA system will render the process more efficient and less destructive to the environment and will result in data-driven farming.