Feed management is central to profitability and sustainability in aquaculture, as feed accounts for the largest share of production costs. Inefficient feeding practices such as fixed schedules and overfeeding often lead to poor feed conversion ratios (FCR), water quality deterioration, and increased disease risk. Artificial Intelligence (AI) is emerging as a practical solution to improve feeding precision. By integrating data from cameras, water quality sensors, and automated feeders, AI systems monitor fish behaviour, appetite, and environmental conditions to adjust feed quantity and timing in real time. This approach reduces feed wastage, improves FCR, stabilizes pond conditions, and enhances overall productivity. Accessible low-cost technologies are making AI-assisted feeding feasible even for small and marginal farmers. Rather than replacing farmer expertise, AI functions as a decision-support tool, combining field experience with data-driven insights to promote efficient, profitable, and environmentally responsible aquaculture practices.