ABSTRACT The thorough, objective, and regular assessment of animal welfare in zoos and aquariums is rapidly becoming an essential task for these institutions. Traditional welfare assessment methods are, however, difficult to scale to the number of species and individuals housed in zoos and aquariums. Automation, using artificial intelligence (AI) can provide solutions to these challenges. This literature review provides an overview of recent advances in this field, with a focus on studies relevant to zoo and aquarium animal welfare. AI in animal behavior and welfare monitoring, particularly in farm animals, has become increasingly commonplace in recent years. Recent studies have investigated AI's capability to identify and assess animal behavior in poultry, pigs, sheep, and cattle, including estrus prediction in cows; classification of animal vocalizations; and detection of potential welfare concerns, including early signs of lameness in cattle and sheep. In companion animals, AI has been used for facial recognition, vocalization‐based emotion recognition, and behavioral monitoring. Laboratory animal behavior monitoring through AI tools has also rapidly increased since 2000. AI is increasingly used in zoos, including the identification of individual animals; monitoring of their movement within their enclosure; and quantifying behavior, including time spent using enrichment. The rapid increase in AI use in animal welfare shows promise in improving animal management and welfare in zoos and aquariums, through improved and more efficient monitoring and prediction.
Liptovszky et al. (2025) studied this question.