Over the years, AI-driven mobile health (mHealth) applications have emerged to support maternal healthcare. However, most applications have failed to incorporate persuasive strategies and address existing myths/culturally rooted concerns about postnatal care in Nigeria. In this study, we leverage the Persuasive Systems Design model to develop PostMom, a medium-fidelity AI-driven mHealth prototype aimed at improving Nigerian mothers’ knowledge of postnatal care. We piloted PostMom with 36 Nigerian mothers who interacted with the prototype and subsequently completed a post-study survey, which comprised of the Perceived Persuasiveness Scale, the System Usability Scale (SUS), and open-ended questions. Quantitative results from this study showed a good SUS rating (M = 77.67), and a significant persuasiveness rating of the PostMom prototype (p < .001). In addition, qualitative feedback from our participants presented three design opportunities: (1) support for navigation, readability, and inclusivity; (2) emotionally supportive and culturally sensitive engagement; and (3) clear information presentation with credibility cues and disclaimers. Our findings contribute to designing the next iteration of our culturally tailored AI-driven persuasive maternal application (PostMom), which can be scaled to other cultural and low-resource settings in the future.