The AI-viticulture nexus: Robotics and precision technologies for sustainable vineyards

Abstract

Automation technologies, such as Artificial Intelligence (AI), robotics, IoT and remote sensing, are transforming viticulture by addressing labour shortages, climate resilience challenges and resource optimization. AI-driven machine learning models process data from multispectral drones and IoT sensors to monitor soil health, water stress and canopy dynamics, enabling precision agriculture practices like targeted irrigation and nutrient delivery. Autonomous robotic systems perform tasks such as selective harvesting, pruning and pest management, enhancing operational efficiency while reducing manual labour. IoT networks provide real-time insights into microclimatic conditions, empowering growers to adopt climate-smart strategies that minimize chemical inputs and improve yield stability. Despite progress, key barriers persist: AI models require terroir-specific adaptation, fragmented datasets hinder interoperability and field validation of autonomous systems under diverse conditions remains limited. Future research must prioritize accessible solutions: low-cost sensor networks for smallholders, adaptive AI frameworks for climate volatility (e.g., drought or flood prediction) and edge computing for real-time analytics. Ethical concerns data privacy, algorithmic bias and technology access disparities demand inclusive governance. Additionally, user-friendly interfaces are essential for broad adoption. Addressing these gaps will unlock automation’s full potential in advancing sustainable viticulture: optimizing water/energy use, reducing agrochemical reliance, enhancing biodiversity and ensuring economic resilience for growers. Ultimately, integrated automation promises a balance between ecological stewardship, resource efficiency and sector-wide viability in a climate-constrained future.