Aquaculture has emerged as the fastest-growing food-producing sector globally, playing a crucial role in meeting the rising demand for affordable protein sources. By 2030, it is projected that aquaculture will contribute more than half of the world's total fish production, driven largely by the rapid increase in global population and the corresponding surge in demand for fish. However, the aquaculture industry continues to face challenges that hinder its full potential, including dependency on human intervention and limitations in effective management practices. These constraints can compromise productivity, sustainability, and the overall health of aquatic species. In response to these issues, the integration of Artificial Intelligence (AI) technologies into aquaculture systems presents a transformative opportunity to enhance operational efficiency and sustainability. AI tools such as drones, advanced camera systems, deep learning algorithms and the Internet of Things (IoT) offer practical solutions that can mitigate these longstanding challenges.

The implementation of AI in aquaculture enables real-time monitoring and precise control over critical environmental parameters, such as water quality, temperature and oxygen levels, thus reducing waste and minimizing environmental impact. With the help of AI-powered automated feeding machines, aquaculture operations can be conducted more efficiently, eliminating the need for constant human supervision while ensuring optimal feeding schedules. Moreover, AI systems can be customized to adapt feeding activity according to the specific behavior of different aquaculture species, enhancing growth rates and feed conversion ratios. Drones, equipped with smart sensors and imaging technology, allow for close monitoring of fish health and development, enabling prompt interventions in cases of disease outbreaks or abnormal behavior. These technologies not only improve animal welfare but also support early detection and response mechanisms that are crucial for maintaining stock health and preventing large-scale losses. Furthermore, AI acts as an intelligent data collector and analyzer, empowering fish farmers with actionable insights through predictive analytics and informed decision-making. By leveraging historical and real-time data, AI enhances the capacity to forecast production trends, evaluate performance metrics and implement strategies that optimize yield and resource use.

This article was written by Associate Professor Dr. Lee Seong Wei from the Department of Agricultural Sciences, Faculty of Agro-Based Industry, Universiti Malaysia Kelantan. Dr. Lee specializes in aquaculture and holds a Doctor of Philosophy in Fish Disease Biotechnology and Natural Products from Universiti Malaysia Terengganu, a Master’s degree in Health Biotechnology of Aquatic Organisms and a Bachelor's degree in Agrotechnology Aquaculture from Kolej Universiti Sains dan Teknologi Malaysia.