This paper introduces an AI-driven, data-driven methodology for estimating spectrum demand by leveraging both site license and crowdsourced data. The approach uses an enhanced combined proxy, validated against real-world mobile network traffic, to achieve high predictive accuracy, demonstrating its robustness across multiple major Canadian cities for improved spectrum planning.