ARTIFICIAL INTELLIGENCE AND INTELLIGENT PLATFORMS IN ANIMAL PRODUCTION: CURRENT ADVANCES AND FUTURE PERSPECTIVES

Abstract

This review aimed to synthesize current advances in artificial intelligence (AI) and intelligent digital platforms applied to animal production, highlighting their main techniques, applications, challenges, and future perspectives. Recent developments in digital agriculture have accelerated the adoption of AI-based tools capable of supporting data-driven decision-making in livestock systems. Among the available technologies, Machine Learning, Deep Learning, and Computer Vision have become the most established approaches for predicting productive performance, monitoring animal health and welfare, optimizing nutrition and reproduction, and improving management efficiency. More recently, intelligent platforms integrating AI, the Internet of Things, cloud computing, and sensor networks have enabled continuous monitoring and real-time decision support across multiple production systems. Emerging technologies, including large language models and explainable AI, are expected to further enhance knowledge management and decision support, although challenges related to interoperability, data quality, model validation, and producer adoption remain. Overall, AI is no longer an emerging technology but an essential component of Precision Livestock Farming, with increasing potential to promote more efficient, sustainable, and evidence-based animal production.