Taking 30 provinces(due to the lack of data, the statistical data mentioned here do not include the Tibet Autonomous Region, the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province) in China as samples, the TOE framework and dynamic QCA method was used to study the synergetic effect of artificial intelligence elements on the improvement of new quality productivity. The results show that all six antecedent conditions are non-essential conditions, and the lack of intelligent organizational capabilities is the core obstacle to high new quality productivity. Five configuration paths are identified including ability-driven-financial synergy type, technology-driven-ability synergy type, ability-driven type, ability-driven-government synergy type and organization-led type. According to the consistency analysis results within and between groups, the consistency in some years fluctuates, and there is no obvious time effect or case effect. The explanatory power of the results is relatively strong. Based on this, it is proposed to adopt multi-dimensional comprehensive measures, customize specific strategies for different configuration types, maintain policy continuity and stability, and focus on the core of organizational capabilities, aiming to enhance the development of new quality productivity in China.