Intent-Based Networking (IBN) is a model that enables proactive network control and automation to satisfy high-level demands. It follows a closed-loop mechanism that abstracts the network complexity and dynamically allows updates to the network monitoring and intelligence. Hence, it eliminates the traditionally practiced error-prone manual network control. In contrast with the traditional reactive approach, IBN-based approach promotes the proactive and dynamic solution. To this end, IBN uses machine learning (ML) to predict the future and keeps a balance between the intended and actual state. Hence, this work considers an IBN-driven routing mechanism to ensure service provisioning with the desired quality of service (QoS). In contrast to the traditional static routing scheme, this work considers AI-driven dynamic and proactively updatable routing schemes to ensure QoS. This work demonstrates AI-driven service route control mechanism for ensuring quality of service (QoS) on top of Korea Advanced Research Network-Software Defined Infrastructure (KOREN-SDI). More precisely, an ML-based approach is used to find the best path between source and destination nodes. In addition, it incorporates IBN closed-loop process to monitor and update service routes proactively based on predicted future link utilization. This novel approach introduces proactive updates on runtime to avoid future failures and ensures seamless service provisioning with the fulfillment of QoS demands by changing traffic routes dynamically.