The methods and applications of artificial intelligence more and more are linking with technologies of precision agriculture. The classical and modern approaches to artificial intelligence used for problem solving in the technologies of precision agriculture. Searching methods include uninformed and informed search methods which is better way to achieve optimality. Expert systems are typical classical approaches to artificial intelligence and they can be applied for problem solutions. Decision making in precision agriculture include different data collection and data analysis. Hierarchical relationship exists between, data, facts, information and knowledge. Knowledge can be defined as the processing of information to enable intelligent decision making. Both logic and fuzzy logic are discussed. An important aspect of the field of artificial intelligence is the ability of computers to learn from experience and change their behavior in different ways. Some of the modern approaches to artificial intelligence are: artificial neural networks, genetic algorithms, evolutionary computing and agent architectures. One of exciting development in the field of an artificial intelligence appeared through the developments of robotics, which largely related with precision agriculture. The relationships between the methods and applications of artificial intelligence and components of precision agriculture are discussed.