This study investigates how voice acoustics and gender stereotypes influence the effectiveness of AI driving coaches in improving driving safety. Using a 2 × 2 × 2 experimental design, we explored the impact of the voice harmonics-to-noise ratio (HNR) and intonation variation on driver behavior moderated by pro-male and pro-female stereotypes. A high HNR and varied intonation enhanced speech clarity and engagement, and promoted safer driving behaviors. However, gender stereotypes shaped the perceptions of AI voices; pro-male biases amplified the authority of high-HNR voices, while pro-female biases aligned better with expressive, high-intonation voices. The study used driving simulators, feedback interventions, eye-tracking, galvanic skin response, and facial expression analysis to measure cognitive load and emotional reactions. This study contributes to the literature on IS and HCI by revealing how cognitive biases affect trust and engagement in AI feedback.