Integrating AI into data-driven agriculture is not a cure-all but a potentially transformative tool. Embracing advanced technologies and driving progress can help ensure a more sustainable and profitable agricultural future, meeting the needs of a growing population. This chapter explores the specific role of AI within smart and precision agriculture. The chapter covers the application of AI in data capture ranging from sensor networks, satellite imagery, drone technology, and weather data integration to monitor crop health, soil conditions, and environmental factors in real-time, enhancing precision agriculture. It examines how various data analysis methods encompassing machine learning algorithms, image recognition & computer vision, and predictive analytics interpret data to provide meaningful insights. The chapter also underpinned various data-driven decision-making scenarios such as targeted irrigation, precision pest & disease control, automated weed control, selective harvesting, livestock monitoring % management, crop rotation planning, and planting date optimization.