Efficient stock counting in warehouses is challenging, typically relying on manual audits or barcodes. This paper introduces Humanized TASC (Tagless And Automated Stock Counting), an AI-driven, drone-based solution for autonomous inventory checks without tags or barcodes. The drone navigates and captures shelf images, which are processed by computer vision to detect and classify unboxed products. A real-time GUI monitors the process, and stock data is stored in a database. The system integrates NLP, enabling users to query stock data in natural language (e.g., “How many batteries were counted in the last run?”). This provides an intuitive interface, reducing operational overhead and errors. Humanized TASC demonstrates the feasibility of combining drones, AI vision, and NLP for intelligent inventory management in a simulated environment, suggesting potential for future autonomous warehouse operations.