MINI REVIEW article
Front. Vet. Sci.
Sec. Veterinary Humanities and Social Sciences
This article is part of the Research TopicTransforming Veterinary Medicine: Digital Tools and AI as Path to Sustainable Animal CareView all 11 articles
Ethical Considerations of Artificial Intelligence (AI) in Veterinary Medicine Decision-Making
Provisionally accepted
- TLC Animal Hospital, El Paso, United States
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Abstract The rapid growth and development of Artificial Intelligence (AI) is leading to a paradigm shift across multiple disciplines of decision-making. Veterinary medicine is an area wherein this proliferation offers profound potential for advancement, but is also ripe with potential ethical dilemmas resulting from the assimilation of AI technology into the decision-making process. While AI can increase accessibility of advanced veterinary care and improve efficiency of clinical and administrative workflow, the successful implementation of it into veterinary decision making requires assessment of key areas. These areas are the accuracy and reliability of AI diagnostic interpretations, the ethical implications of bias in AI algorithms, stewardship of privacy and personal data, and the balance of innovation with legal and professional responsibilities of animal welfare. Results of this review found that AI should aid, not replace, veterinary professional decision-making. To that end, continued research into accuracy and vigilance to mitigate bias is necessary, foundational standards for AI use and education must be enacted, and further research into the effect of AI on clinically ambiguous cases is imperative to safeguard the ethical standards of veterinary decision-making.
Keywords: accuracy, Artificail Intelligence, Bias, Decision- making, Ethics, Medicine, Veterinary
Received: 05 Jan 2026; Accepted: 26 Jan 2026.
Copyright: © 2026 Heinlein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Matthew Heinlein
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