In pig production system accurate estimation of growth performance is essential as it contributes directly to the animal welfare and farm productivity. However, manual weighing of pigs is labor intensive and often cause stress to the animals, thereby increasing the risk of disease transmission. In modern pig production, group housing systems has made the accurate measurement of individual-level growth performance a challenging task. To address this challenge, the article will explore the used of artificial intelligence (AI) to estimate individual pig growth in group-level housing systems. There are two complementary approaches to estimate individual pig growth. The first approach is to analyse temporal weight data to understand the hidden growth variations among pigs and predict the performance of the animals in a non-invasive manner providing high performance. The second approach is to extract morphological features from images or videos data to analyse the growth patterns. These approaches can be used for early detection of abnormal pigs, reduce labor costs, improve efficiency and long-term sustainability in pig production.