Interpretive Summary: Rethinking livestock farming for artificial intelligence integration

By: Andrea Rosati

Implications

• Holistic infrastructure redesign—AI adoption in livestock farming requires not just adding sensors and devices to existing facilities, but rethinking barn layouts, workflows, and movement patterns to create “AI-ready” environments that optimize data capture and animal welfare.
• Transformation of workforce roles and skills—The shift to AI-driven management demands new professional profiles (e.g., digital field operators, AI system managers, data analysts) and continuous training to ensure both technological competence and critical interpretation of AI-generated insights.
• Data integration and interoperability—Effective use of AI relies on standardized, compatible data systems across feeding, health, reproduction, and monitoring processes, enabling seamless communication, real-time analytics, and improved decision-making.
• Cybersecurity as a core operational priority—Increased digitalization brings significant vulnerability to cyber threats, making cybersecurity policies, access control, IoT device protection, and staff awareness essential to safeguarding data, continuity, and trust.
• Shift from reactive to predictive management—AI allows real-time detection of health, behaviour, and environmental changes, enabling proactive interventions and replacing fixed schedules with dynamic, data-triggered workflows.
• Expanded collaboration networks—Digital platforms facilitate continuous, secure, and data-driven collaboration with veterinarians, nutritionists, researchers, and technology providers, fostering innovation, benchmarking, and co-development of AI solutions at local and global levels.

Introduction

Animal husbandry is currently undergoing an unprecedented structural transformation, driven by the growing adoption of advanced digital technologies and, in particular, artificial intelligence (AI). The urgency of tackling global challenges—such as environmental sustainability, animal welfare, economic competitiveness, and food security—requires a profound revision of traditional management models, making it necessary to take a major leap in the collection, analysis, and use of data.

In this new scenario, artificial intelligence is not simply an additional tool but a true catalyst for change (Fuentes et al., 2022; Ohashi et al., 2024). Its integration requires a comprehensive redefinition of the business infrastructure, workflows, staff skills, relationships with consultants and suppliers, as well as cybersecurity measures. The livestock farming of the future is not built solely with sensors and algorithms, but with a systemic vision that can harness the potential of digitalization and make it operational in the real-life context of farming.

Read more in Animal Frontiers: From Isolated Data to Integrated Ecosystems.