Accelerating the construction of digital rural areas is a strategic choice that conforms to the trend of technological change and reshapes the development pattern of rural areas. Currently, China has built a digital infrastructure covering both urban and rural areas, with over 300 million internet users in rural areas. Digital technology is gradually integrating into rural production, life, and governance, and the construction of digital villages has achieved phased results. In recent years, breakthroughs have been made in big model technology, giving rise to a new paradigm of artificial intelligence applications based on intelligent agents and terminals. Its advantage lies in the ability to predict demand, proactively respond, and accompany the process, allowing technology to truly revolve around people, adapt to people, and serve people. Therefore, artificial intelligence is not only expected to overcome practical bottlenecks such as weak rural industrial foundations and resource reserves, limited digital capabilities of business entities, but also has the potential to provide real-time, personalized, and low threshold digital services for villages and residents, helping rural areas accelerate their entry into a new stage of digital intelligence integration development. On the one hand, in response to the scarcity of agricultural data and difficulties in data annotation, artificial intelligence technology can independently generate high-quality crop phenotype images, pest and disease samples, and environmental data to construct and expand agricultural datasets. Intelligent agents transform dispersed field experience into quantifiable and transferable intelligent decision-making models through task decomposition, active learning, and rapid iteration, achieving effective transfer and reuse of agricultural knowledge between different regions and crop types. Compared to traditional paths, this new model can significantly improve resource utilization efficiency, shorten iteration cycles, and reduce data acquisition and processing costs. On the other hand, as the interaction paradigm gradually evolves from "finger clicking" to intelligent interaction based on "human-computer dialogue", rural residents can easily obtain technical guidance, medical consultation, educational resources and other services through oral questioning, greatly reducing the threshold for digital skills. For example, the application of artificial intelligence assisted diagnosis in rural areas such as Zhejiang and Jiangsu has to some extent alleviated the local medical pressure; The exploration of generative artificial intelligence education platforms in Guizhou and Yunnan has expanded the coverage of high-quality educational resources. However, compared with the service industry, industry, and urban areas, there is still an objective gap in the digitalization level of agriculture and rural areas, and the urban-rural digital divide is still prominent. If we continue to follow the traditional path of large-scale data accumulation and high cost investment in construction, rural areas will not only find it difficult to effectively catch up in the process of digital development, but may even face the risk of further widening the gap. To seize the opportunity of artificial intelligence reshaping the development pattern of rural areas, it is necessary to build a multi-dimensional collaborative promotion system. Coordinate policy guidance. Closely align with the national "Artificial Intelligence+" action plan, coordinate and promote the precise implementation of major tasks and projects in the field of digital rural areas. Strengthen cross departmental collaboration mechanisms and continuously improve the systematic and regional adaptability of policies. Scientifically and reasonably coordinate local realities, industrial advantages, development goals and paths, and use artificial intelligence technology to promote the upgrading of digital rural areas according to local conditions. Persist in scene guidance. By benchmarking against advanced experiences in certain industries and regions, and based on actual development needs, we aim to create "model rooms" in fields such as crop breeding, food security, education and healthcare, disaster prevention and control, and rural governance. Systematically extract and promote the successful experience of leading scenarios to be replicated throughout the entire region, industry, and chain, realizing the transformation of artificial intelligence applications from "model rooms" to "commercial housing", and effectively promoting the increase of agricultural benefits, rural vitality, and farmers' income. Build a solid foundation base. Support agricultural leading enterprises to collaborate with technology-based enterprises and research institutes to strengthen the construction of basic corpora and high-quality datasets, and promote innovative applications of data annotation, synthetic data, and other technologies in the field of agriculture; Accelerate the classification and open sharing of government and public data, ensuring that data is accessible, flowing, and used effectively. Promote the construction of 5G networks and gigabit optical networks in rural areas, and accelerate the digital transformation of rural infrastructure. Strengthen ecological construction. Based on the existing industry alliance platform, establish a specialized promotion group for agriculture and rural areas, actively carry out standard research and development, scenario demonstration, competition activities, international cooperation and other work, and build an open, collaborative and sustainable digital rural artificial intelligence application ecosystem. Encourage universities to establish interdisciplinary fields related to agricultural artificial intelligence and focus on cultivating high skilled talents in rural areas. Build a number of artificial intelligence industry incubators rooted in rural areas, guide technology, talents, and resources to gather in rural areas, and continuously inject momentum into the construction of digital villages. (New Society)