Commercial vehicle operation faces challenges from driver distraction associated with traditional Human-Machine Interfaces (HMIs) and inconsistent network connectivity, particularly in long-haul scenarios. This paper addresses these issues through the development and presentation of an embedded, offline AI-powered voice assistant. The system is designed to reduce driver distraction and enhance operational efficiency by enabling hands-free control of vehicle functions and access to critical information, irrespective of internet availability. The technical approach involves a three-tier architecture comprising an Android-based In-Vehicle Infotainment (IVI) unit for primary user interaction and voice processing, an Android mobile device acting as a communication bridge and processing hub, and a proprietary OBD-II dongle for CAN bus interfacing. Offline speech recognition is achieved using embedded wake word detection and speech-to-intent engines. A user-centered design methodology, informed by a field study with 25 professional truck drivers in Brazil, guided the prioritization of system functionalities. Key findings from this study highlighted strong driver interest in voice interaction for vehicle status monitoring (e.g., fluid levels, fault alerts) and control of essential systems (e.g., lighting, cabin environment). The implemented prototype successfully integrates these prioritized features, demonstrating the viability of offline voice control. Preliminary observations indicate robust wake word and intent recognition accuracy (≥97% based on vendor benchmarks) and acceptable system responsiveness (400-700 ms latency) under typical cabin noise conditions. This work establishes a foundation for safer, more intuitive HMIs in software-defined commercial vehicles, emphasizing the importance of offline capabilities for reliable operation.