Agricultural Artificial Intelligence: Obstacles and Opportunities

Artificial Intelligence (AI) has the potential to completely transform the agriculture sector by giving farmers new tools to maximize crop yields, reduce environmental impact, and optimize resource efficiency. The widespread application of AI in agriculture is hampered by a number of issues, despite its potential. These include the lack of accurate and high-quality data, the high implementation costs, the challenge of modifying AI models to adapt to complex and dynamic agricultural environments, and the ethical issues associated with applying AI to crop management, resource allocation, and pesticide application decision-making processes. Certain challenges and limitations that restricts the farmers and various organization bodies to adapt the AI techniques implementation in agricultural field are briefly discussed in this chapter along with some generic solutions that may give hands to the individuals reading the context. In order to effectively use AI into agriculture, several constraints need to be resolved. Enhancing data quality and collecting, cutting down on the cost of AI technologies, making AI models more flexible, and creating unambiguous ethical standards for their use should be the top priorities for researchers and developers. AI has the ability to significantly change agriculture and create a future that is more resilient, productive, and sustainable if these challenges are successfully addressed.