Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Pandey, Ananya; Joseph, Jipson Title A name given to the resource Leveraging artificial intelligence for sustainable development in agriculture: An exploratory study Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Artificial Intelligence and Data Science for Sustainability: Applications and Methods;pp.187-211 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-6829-9.ch007" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-6829-9.ch007</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85218077718?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85218077718?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Pandey A., Christ University, Bangalore, India; Joseph J., Christ University, Bangalore, India Description An account of the resource In a world where sustainability has been given utmost priority, agriculture plays a pivotal role. Artificial Intelligence in the agricultural sector has changed the landscape of agriculture across the globe. 'Agvolution' (evolution in agriculture) including AI supported precision farming methods, data analytics, and robotics is a novel strategy which increases crop yields using less fertilizers, and energy. AI in agriculture supports ethical farming, boost revenue, and lessen negative environmental effects. AI systems aggregate data from weather stations, sensors, and satellites to produce improved weather forecasts. This mechanism enhances environmental sustainability. Despite numerous advantages with AI, the farming community face challenges like data security and privacy, high cost of machines and tools. In light of the above, the authors explore the usage of AI in agriculture to attain sustainability, and analyze the need to establish governance structures for increasing food security and systems to overcome the challenges faced by the farmers. 2025, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836936831-2; 979-836936830-5; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online