Climate-Smart Agriculture in the Age of Artificial Intelligence: Integrating Data-Driven Foresight for Sustainable Food Systems

Samenvatting

Agriculture lies at the center of the climate–food–energy–water nexus, both driving and suffering from global environmental
change. Climate-Smart Agriculture (CSA) has emerged as a strategic framework for enhancing productivity, resilience, and
sustainability. Yet, the increasing complexity of agro-ecosystems demands more adaptive and anticipatory management tools.
This review examines how Artificial Intelligence (AI), particularly machine learning (ML), remote sensing (RS), and Internetof-
Things (IoT) technologies, are revolutionizing CSA through data-driven environmental foresight. We synthesize recent
developments in AI-enabled crop modeling, precision irrigation, soil health monitoring, and greenhouse gas prediction. We
discuss integration frameworks that combine multi-source data, predictive analytics, and decision-support platforms to improve
real-time farm management and climate adaptation strategies. Challenges—such as data scarcity, algorithmic bias, and digital
inequity—are analyzed alongside the need for transparent, human-centric AI governance. The review concludes by identifying
future pathways including digital twin farms, federated learning, and AI-empowered climate services. Through crossdisciplinary
innovation and equitable technology access, AI-driven CSA can transform global food systems into resilient,
sustainable, and foresight-oriented networks prepared to meet the challenges of climate uncertainty.