Application of generative artificial intelligence in the aquacultural sector

Artificial Intelligence (AI) applications in aquaculture have recently attracted growing attention, as these technologies are becoming vital for data analysis, improving production processes, and optimizing the use of natural resources. Among the different AI approaches, Generative Artificial Intelligence (GAI) emerges as one of the most innovative and promising.This paper explores the use of Generative Artificial Intelligence (GAI) in aquaculture, evaluating its advantages and challenges within the industry's unique context. It begins with an overview of generative model architectures, then delves into their potential contributions to aquatic resource management, the improvement of farming practices, and the promotion of environmental sustainability.To obtain the most up-to-date insights, research was carried out using database such as SCOPUS, Google Scholar, and Web of Science databases. GAI holds significant promise for aquaculture, with applications that include enhanced water quality management, fish stock health prediction, and automated feeding supervision. When applied responsibly, GAI can streamline routine operations while contributing to a more resilient and sustainable future for the aquaculture industry. With its ability to extract valuable insights from big data, GAI proves to be a powerful tool for tackling future challenges, ensuring food production that meets the demands of a growing global population while addressing increasingly urgent environmental concerns.