The exponential growth of AI education has brought millions of learners to online platforms, yet this massive scale has simultaneously exposed critical pedagogical shortcomings. Traditional video-based instruction, while cost-effective and scalable, demonstrates systematic failures in both sustaining learner engagement and facilitating the deep conceptual mastery essential for AI literacy. We present a pilot study evaluating a novel hybrid learning platform that integrates real-time conversational AI tutors with traditional video lectures. Our controlled experiment $(N = 58,\ \text{mean age } M = 21.4,\ SD = 2.8)$ compared traditional video-based instruction with our AI-augmented video platform. This study employed a sequential within-subjects design where all participants first completed the traditional video condition followed by the AI-augmented condition, providing direct comparisons of learning outcomes. We measured learning effectiveness through immediate post-tests and delayed retention assessments $(2\text{-week delay})$. Results suggest improvements in learning performance: immediate post-test performance showed a large effect size $(d = 1.505)$ with participants scoring $8.3$ points higher after AI-augmented instruction $(91.8\ \text{vs.}\ 83.5\ \text{out of}\ 100,\ p < .001)$. Behavioral analytics revealed increased engagement duration $(71.1%$ improvement with AI tutoring$)$ in the experimental group. This pilot study provides preliminary evidence that conversational AI tutors may enhance traditional educational delivery, suggesting a potential avenue for developing scalable, adaptive learning systems.