Artificial intelligence tools are increasingly being applied to animal welfare monitoring — from automated lameness detection to emotional state recognition in livestock and companion animals.
AI applications in animal welfare monitoring represent a genuine advance in welfare science — continuous automated monitoring can detect welfare problems earlier and at greater sensitivity than periodic manual inspection. Lameness detection before clinical presentation allows earlier intervention. Vocalization analysis can identify pain states invisible to visual inspection. As these tools become more affordable and validated, they offer the prospect of continuous welfare surveillance across commercial livestock operations at low marginal cost.