Smart agriculture based on artificial intelligence is one of the most important modern trends in agricultural development. It aims to improve productivity and achieve sustainability through the use of advanced digital technologies. This type of agriculture relies on intelligent systems capable of collecting and analyzing agricultural data and making accurate decisions in real time. AI contributes to crop monitoring and analysis of soil and weather conditions using sensors, drones, and satellite imagery. By analyzing this data, optimal planting times, irrigation amounts, and fertilization needs can be predicted, reducing waste and increasing production efficiency. AI is also used for early detection of plant diseases and pests through image analysis and biological pattern recognition. This allows for rapid intervention, reducing the spread of diseases and minimizing the use of chemical pesticides, resulting in healthier and more environmentally friendly crops. In resource management, AI helps optimize water and energy usage, particularly in smart irrigation systems that predict actual plant needs. It also supports farmers in making informed decisions regarding harvesting, storage, and marketing, thereby increasing economic returns. Despite its many advantages, smart agriculture faces challenges related to the cost of modern technologies, digital infrastructure, and training of agricultural personnel. Nevertheless, the future points toward expanded use of AI in agriculture to ensure food security, address climate change, and promote sustainable natural resource management.