This study aims to explore how the Internet of Things (IoT) and artificial intelligence (AI) technologies can drive the intelligent transformation of modern agriculture, with the intention of providing a theoretical basis for the development of smart agriculture. This study employs the literature review method to systematically sort out the current application status of key technologies, including IoT, big data, and AI, in modern smart agriculture against the backdrop of the big data era. The findings indicate that IoT technology enables real-time monitoring of agricultural environments, big data technology provides data support for agricultural production decision-making, and AI demonstrates immense potential in areas such as intelligent breeding, yield prediction, and pest and disease identification. The deep integration of IoT, big data, and AI is the key for improving the level of intelligent production. At the same time, this paper analyzes the current challenges in data, cost, standards and talents, and looks forward to the future directions of cross-modal data fusion, lightweight AI, transfer learning, blockchain security and human-machine collaboration, in order to provide reference for related research and promote theoretical innovation and practice in this field.