Can AI Help Us Better Understand Animal Behaviour?

Understanding an animal has usually meant watching it closely and trying to work out what its sounds, movements and behaviour might mean. Is that bark playful or defensive? Is that cow not eating her food because she’s ill or simply not hungry? Is that whale click part of a social interaction or something else?

AI hasn’t suddenly given us all the answers, but it has changed how much information we can analyse. Researchers can now use machine learning to work through recordings, footage and other data at a scale that would be difficult for humans to manage alone.

It isn’t translating what animals are saying in any literal sense, but it can definitely help researchers, vets and farmers identify patterns in animal behaviour that might be difficult to spot, giving them more information about communication, health and welfare.

How Is AI Learning To Understand Animals?

The data varies depending on the animal being studied. Researchers can analyse vocalisations and calls, movement, images and video, eating patterns or location data from tracking devices.

AI can then search large datasets for recurring patterns; that might mean finding similarities between animal calls, identifying unusual behaviour or helping researchers work out whether a specific sound is linked to specific behaviour.

An algorithm might find that a certain sound regularly appears before a certain behaviour without knowing why – this can point researchers towards a pattern, but humans will still have to work out what that pattern tells us about the animal.

From Animal Sounds To Behaviour

Research published on Nature in 2024 found new patterns in the way sperm whales use their codas, including patterns involving rhythm, tempo and changes that depend on the vocal exchanges. The researchers proposed a “sperm whale phonetic alphabet” to describe this structure , but the study didn’t determine what the codas mean. Instead, it showed that sperm whale vocalisations have a more complex and structured system than previously understood.

Elephants are another example – researchers used machine learning to analyse vocalisations from wild African savannah elephants in Kenya and investigate whether their calls contained information about the individual being addressed.

The model identified the elephant the call was directed at in 27.5% of calls, compared with around 8% when the acoustic information was randomly shuffled. Playback experiments also showed that elephants responded differently to calls that had originally been directed at them than to calls directed at different one. The researchers concluded that elephants use individually specific, name-like calls, although this doesn’t mean they have names in exactly the same way humans do.

How Could AI Help Us Care For Animals?

The same technology can also help researchers and animal carers identify changes in behaviour that could point to a health or welfare issue.

Research from the University of Surrey, published on Frontiers in Veterinary Science in 2026, researched how AI and bioacoustics could be used to monitor animal health and behaviour. The researchers explain that AI can combine sound with other types of recorded data to help classify animal health and identify potential points for intervention, although they also note that evidence-based interventions using quantitative sound data have not yet been fully developed.

Wildlife researchers can also use cameras, microphones and other sensors to collect information without constantly being near the animals themselves. AI can then help process the large amounts of data these systems produce, making it easier to identify species and analyse behaviour. The University of Surrey review says that bioacoustic monitoring can be used for species detection, location and population monitoring, while video can provide additional behavioural context.

For pet owners, similar technology is also appearing in smart collars and cameras that monitor things such as activity and routines. These systems can provide additional information about changes in behaviour, however, they shouldn’t be treated as a replacement for veterinary advice.

Can AI Really Understand Animals?

There are still obvious limits to what the technology can tell us – a sound or movement needs to be considered in the context in which it occurs, and the same behaviour can have different explanations depending on the situation.

AI systems also depend on the data used to train them. Animal vocalisations can be different with factors such as age, sex, location and date, while environmental conditions can also affect recordings. The University of Surrey review highlights these challenges when discussing automated bioacoustic analysis.

AI might spot an unusual movement pattern or vocalisation, but that doesn’t exactly tell us whether an animal is stressed, frightened, unwell or simply just behaving differently.

A New Kind Of Animal Whisperer

AI isn’t about to give humans a universal animal translator, but it is giving researchers new ways to analyse animal behaviour using far more data than could realistically be examined by hand. From whale vocalisations and elephant calls to livestock monitoring, the technology can help people find patterns that would be difficult to spot through observation alone.

Instead of teaching animals to “talk” to us, AI is giving humans more information about what they are doing, how their behaviour changes and when something might need closer attention. That could make AI a useful tool for animal health, welfare and conservation while we’re still a long way from cracking the animal language code.