The potential roles for artificial intelligence in supporting veterinarians during an emergency response

This article considers how artificial intelligence (AI) could support, within a New Zealand context, the contribution of private veterinarians to protecting animal health and welfare during emergency responses. These may include veterinary involvement in natural disasters, such as fire and flood, or formal emergency animal disease responses, which are the responsibility of different government departments.An emergency response in New Zealand that impacts the health and welfare of animals, relies heavily on privately operated veterinary practices, which typically lack the coordination and support required for effective engagement. Drawing on historical events such as the response to the recent incursion of <i>Mycoplasma bovis</i>, this article reviews systemic limitations of the current emergency response process, such as fragmented data flows, unclear roles, and insufficient planning, and explores how AI could address these challenges.Key concepts of AI are introduced, including predictive modelling and decision support, and their relevance is considered within the veterinary context. Recent developments, such as multimodal models, generative reasoning models, and mobile-friendly architectures, offer opportunities to enhance preparedness, support faster decision-making, and improve coordination. However, technical advances alone are insufficient to resolve previous limitations. AI tools are only advantageous if embedded in day-to-day workflows, supported by well-governed data-sharing arrangements, and accompanied by clear guidance on their interpretation and limitations. Challenges relating to ethics, commercial incentives, and operational integration remain considerable.Progress in this area depends on collaboration between veterinarians, technologists, and policymakers as part of existing activities to prepare for an emergency response. By aligning commercial and public-good objectives and clarifying how everyday veterinary activity contributes to system-wide resilience, AI could become a practical tool in the profession's growing role in emergency response.This review identifies strategic opportunities for veterinarians to shape and deploy AI technologies that support animal welfare, improve coordination, and strengthen national resilience during an emergency response to an event involving animals. Realising this potential will require early cross-sector collaboration, durable ethical oversight, and a clear articulation of shared value across both routine and emergency veterinary practice.<b>Abbreviations:</b> AI: Artificial intelligence; ANI: Artificial narrow intelligence; DL: Deep learning; EDMC: Emergency and disaster management cycle; FMD: Foot-and-mouth disease; GPT: Generative pretrained transformers; LLM: Large language model; ML: Machine learning; RL: Reinforcement learning; RLHI: Reinforcement learning with human intervention.