Future Scenario of Agricultural Jobs Using Large Language Models
Kushagra Sharma, Sanjeev Kumar, Patil N D Chethan, Sapna Jarial · Apple Academic Press eBooks · 3 Nov 2026
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Abstract
The agricultural industry stands at the brink of transformation due to emerging technologies, particularly large language models (LLMs). This chapter looks at how these models are poised to reshape agriculture jobs in the coming years, drawing insights from research and reviews. Beginning with an overview of current agricultural practices and the growing influence of technology, these models are showcased for their diverse applications in agriculture, ranging from crop monitoring and pest prediction to soil nutrient management and market optimization. By improving decision-making, LLMs could revolutionize farming by making it more precise and efficient. Support systems powered by LLMs offer real-time advice and training to farmers, facilitating problem-solving and continuous 344 improvement in agricultural practices. LLMs also promote sustainable farming and climate change adaptation. Sensors, drones, and artificial intelligence improve productivity, efficiency, and sustainability in digital agriculture, enabling data-driven resource management. LLMs may assist agriculture, but data privacy, employment displacement, and ethical issues arise. Significant research gaps persist, including understanding the longterm effects on employment and ensuring effectiveness across diverse agricultural contexts. Responsible integration requires strong data privacy and ethical standards. LLMs offer great agricultural opportunities, but they require careful planning and continual study to overcome difficulties and maximize benefits for all stakeholders. This chapter aims to provide a comprehensive exploration of how LLMs are shaping the future landscape of agriculture jobs, emphasizing the need for proactive adaptation and ethical oversight in harnessing these transformative technologies.
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Book, report or commentary. A book, a consultancy or government report, an essay or an interview. Edited, but not journal peer review.
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- 2026 (recently)
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