Forest Science is the science of afforestation, management, utilization, conservation and restoration, as well as the related theories and technologies of forest ecology and sustainable utilization of forest resources. Forests, the main subjects of Forest Science, are characterized by long life periods, high spatial heterogeneity, and extremely complex structure and composition. In the context of climate change, forests play a key role as significant carbon sinks in mitigating climate change, while also being affected by climate change. Traditional studies of Forest Science involve a labor-intensive fieldwork, high trial-and-error costs, and a low decision-making efficiency, which makes it challenging to address the multi-faceted situations of the present and affects the sustainable management of forest ecosystems. Climate-smart Forestry (CSF) integrates the next-generation information and artificial intelligence (AI) technology to shift the traditional researches and management paradigms of Forest Science from three aspects: data acquisition, simulation analysis, and management decision-making, providing a new methodological framework for Forest Science research. The integration of AI and Forest Science knowledge can drive innovation in the field, shift traditional research paradigms, and promote the innovative development of CSF. Based on the prospect in the published paper titled “On the Research of Climate-smart Forestry”, here we outline the concepts and research framework of CSF, introduce key technologies for data acquisition, simulation analysis, and management decision-making, and explore pathways for shifting in research paradigms. The study includes research cases such as intelligent data collection/IoT transmission from the Ker Towers of the Qingyuan Forest CERN, digital twin analysis in the Saihanba Forestry Center, and AI expert decision-making. Based on these cases, there is a new vision in three fields of paradigm shift: forest IoT devices and sensors, multi-process coupling models for ecosystem simulation, and decision systems for ecosystem services that integrate human-AI interaction.