Use of Artificial Intelligence in Agriculture

Published by admin on

Scientia Review
Scientia Review
Volume 2, 2026 – Issue 6
Listen
OPEN ACCESS Popular Science Article
Pranabesh BarmanKrishi Vigyan Kendra, Udaguri, Assam, 784514Pranabesh BarmanKrishi Vigyan Kendra, Udaguri, Assam, 784514pranabeshbarman@gmail.com1Pranabesh BarmanKrishi Vigyan Kendra, Udaguri, Assam, 7845140009-0003-5834-6653, Sarmistha BorgohainKrishi Vigyan Kendra, Sonitpur, Assam- 7840282, Chayanika NathKrishi Vigyan Kendra, Darrang, Assam- 7841463 & Pranjit BaruahKrishi Vigyan Kendra, Barpeta, Assam- 7813164 1 Krishi Vigyan Kendra, Udaguri, Assam, 784514 2 Krishi Vigyan Kendra, Sonitpur, Assam- 784028 3 Krishi Vigyan Kendra, Darrang, Assam- 784146 4 Krishi Vigyan Kendra, Barpeta, Assam- 781316
Scientia Review · 2(6), 2026 · Article ID: SR01128 · ISSN: 3107-7919
Received: 3 June 2026 Revised: 4 June 2026 Accepted: 7 June 2026 Published online: 9 June 2026
Cite this article
Barman, P., Borgohain, S., Nath, C., & Baruah, P. (2026). Use of artificial intelligence in agriculture. Scientia Review, 2(6), 11–13.
Abstract

Artificial Intelligence (AI) is revolutionizing the agricultural sector by enabling data driven decision making, improving resource use efficiency and enhancing crop productivity. The integration of AI with technologies such as machine learning, computer vision, robotics, drones, sensors and the Internet of Things (IoT) has accelerated the development of precision agriculture. AI applications in agriculture include crop monitoring, disease and pest detection, irrigation management, yield prediction, agricultural automation and supply chain optimization. As the global population is projected to reach approximately 9.7 billion by 2050, food production must increase significantly while ensuring environmental sustainability (Food and Agriculture Organization. AI driven technologies have demonstrated substantial potential in addressing these challenges through intelligent resource management and predictive analytics. This article discusses the major applications, benefits, challenges and future prospects of AI in agriculture, supported by scientific evidence and real world examples.

Keywords: Artificial Intelligence, Precision Agriculture, Machine Learning, Smart Farming, Agricultural Automation, Sustainable Agriculture