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Peer-reviewedCC BY-NC-NDNPJ sustainable agriculture

Agentic AI in transforming agriculture: a review.

  • Daoyuan Jin1
  • Daniel Petti2
  • Xuehai Zhou3
  • Peter Ngimbwa4
  • Glen Rains5
  • Shangpeng Sun3
  • Changying Li2
  • Yu Jiang6
6 affiliations
  1. 1Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY USA.
  2. 2Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL USA.
  3. 3Department of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, QC Canada.
  4. 4College of Engineering, University of Georgia, Tifton, GA USA.
  5. 5Department of Entomology, University of Georgia, Tifton, GA USA.
  6. 6School of Integrative Plant Science, Cornell AgriTech, Cornell University, Geneva, NY USA.
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Abstract

Artificial intelligence-based agents are emerging as a transformative paradigm for agriculture, enabling autonomous perception, reasoning, decision-making, and coordinated action across complex data and operational environments. These systems could improve productivity, resilience, resource efficiency, and food security, while raising challenges related to robustness, interoperability, data governance, trust, equity, and regulation. This Review examines the rise of these systems in agriculture and outlines research priorities for their development and deployment.

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Cite

BibTeXRIS
BibTeX
@article{jin2026agentic,
  title = {{Agentic AI in transforming agriculture: a review.}},
  author = {Daoyuan Jin and Daniel Petti and Xuehai Zhou and Peter Ngimbwa and Glen Rains and Shangpeng Sun and Changying Li and Yu Jiang},
  journal = {NPJ sustainable agriculture},
  year = {2026},
  month = nov,
  doi = {10.1038/s44264-026-00199-w},
  url = {https://europepmc.org/article/MED/42996690},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Agentic AI in transforming agriculture: a review.
AU  - Daoyuan Jin
AU  - Daniel Petti
AU  - Xuehai Zhou
AU  - Peter Ngimbwa
AU  - Glen Rains
AU  - Shangpeng Sun
AU  - Changying Li
AU  - Yu Jiang
PY  - 2026
DA  - 2026/11/05
JO  - NPJ sustainable agriculture
DO  - 10.1038/s44264-026-00199-w
UR  - https://europepmc.org/article/MED/42996690
AB  - Artificial intelligence-based agents are emerging as a transformative paradigm for agriculture, enabling autonomous perception, reasoning, decision-making, and coordinated action across complex data and operational environments. These systems could improve productivity, resilience, resource efficiency, and food security, while raising challenges related to robustness, interoperability, data governance, trust, equity, and regulation. This Review examines the rise of these systems in agriculture and outlines research priorities for their development and deployment.
SN  - 2731-9202
ER  -