Security provisioning has become the most important design consideration for large-scale Internet of Things (IoT) systems due to their critical roles to support diverse vertical applications by connecting heterogenous devices, machines and industry processes. Conventional authentication and authorization schemes are insufficient in dealing the emerging IoT security challenges due to their reliance on both static digital mechanisms and computational complexity for improving security level. Furthermore, the isolated security designs for different layers and link segments while ignoring the overall protection lead to cascaded security risks as well as growing communication latency and overhead. In this article, we envision new artificial intelligence (AI) enabled security provisioning approaches to overcome these issues while achieving fast authentication and progressive authorization. To be more specific, a lightweight intelligent authentication approach is developed by exploring machine learning at the gateway to identify the access time slots or frequencies of resource-constraint devices. Then we propose a holistic authentication and authorization approach, where online machine learning and trust management are adopted for analyzing the complex dynamic environment and achieving adaptive access control. These new AI enabled approaches establish the connections between transceivers quickly and enhance security progressively, so that communication latency can be reduced and security risks are well-controlled in large-scale IoT. Finally, we outline several areas for AI-enabled security provisioning for future researches.