The integration of artificial intelligence (AI) and the Internet of things (IoT) into agriculture, known as smart farming, has shaped the agriculture sector into a new dimension along with technological advancement and efficiency in agricultural practices. AI technologies such as machine learning, deep learning, computer vision, and data analytics are the basic pillars of transforming traditional farming methods into data-driven, precision agriculture systems. These technologies enable farmers to make informed decisions by analysing real-time data from sensors, drones, satellites, and other IoT devices. Precision agriculture techniques optimize resource management, including water, fertilizers, and pesticides thereby enhancing crop yields while minimizing environmental impact. On the other hand, in crop monitoring and management, AI algorithms play a vital role in detecting diseases, pests, etc. through image recognition and predictive modelling. Early detection allows for timely interventions, reducing crop losses and improving overall plant health. Moreover, AI-driven robotic systems automate labour-intensive tasks like seeding, spraying, and harvesting, alleviating labour shortages and improving operational efficiency. This review paper comprehensively examines the applications, benefits, challenges, and future directions of AI and IoT in revolutionizing the agriculture sector for the last few years.