Artificial intelligence and animal farming
A scenario of drivers, barriers, and impacts in 2032
Bibliographic Data
| ID | 12150849 |
|---|---|
| Authors | Mark Ryan (0000-0003-4850-0111, Ministry of Economic Affairs and Climate Policy, corresponding author), Vincent Blok (0000-0002-9086-4544, Wageningen University & Research) |
| Year | 2026 |
| Volume | 43 |
| Issue | 1 |
| Publication date | 2026-01-26 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Agriculture and Human Values (JOURNAL) |
| Journal identifiers | ISSN: 0889-048X • E-ISSN: 1572-8366 |
| Publisher | Springer Nature (Netherlands) (PUBLISHER • NL) |
| DOI | 10.1007/s10460-025-10806-0 |
| OpenAlex | W7125679384 |
| Language | EN |
| References cited | 187 |
In animal farming, there is the hope that artificial intelligence (AI) will improve efficiency and increase profits while providing solutions to reduce pollution and pesticide use and improve environmental sustainability, animal health and welfare. However, many are also concerned about AI’s ethical, legal, social, and economic impacts. These include the instrumentalisation of animals, bias caused by AI in how animals are portrayed, allowing the continuation of a harmful farming industry, and concerns around power asymmetries, data ownership, and copyright infringements. Therefore, there is a tension between the potential benefits and drawbacks of AI use in animal farming. This paper takes a forward-looking view of the benefits and challenges that AI may create in animal farming by the year 2032. Through several iterative rounds with stakeholders, this paper maps out a future scenario of AI in animal farming, identifying technological developments alongside potential drivers, barriers, and impacts. The scenario concludes with five recommendations for policymakers: 1. Initiate education programmes on AI in the sector; 2. Create ethical guidelines for AI in animal farming; 3. Science policy should be realistic and not only rely on technical solutions like AI; 4. Ensure public safety from harm caused by AI; 5. Implement better guidance on data-sharing in the sector.
Agriculture · Animal agriculture · Animal ethics · Animal welfare · Harm · Precision agriculture · Public policy · Animal Behavior and Welfare Studies · Effects of Environmental Stressors on Livestock · Food Supply Chain Traceability
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| Citation velocity | historical |
|---|---|
| Highly cited | No |