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From prototype to principle: A design science approach to artificial intelligence innovation in maternal health
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DOI：10.1016/j.technovation.2026.103568.png)
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Abstract
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This study presents a Design Science investigation into developing and evaluating a conversational AI platform for maternal health. Through iterative co-design, beta testing, and reflective analysis, the research demonstrates how emotionally complex care contexts generate actionable design principles, theoretical insights, and entrepreneurial implications. The findings highlight how empathy, transparency, contextual awareness, and modular depth shape user trust and engagement, offering a foundation for designing responsible, human-centered AI in sensitive domains. Below is a summary of highlights. (see Table 1, Fig. 1) • A conversational AI platform for maternal health was designed and evaluated using Design Science. • Iterative co-design revealed the need for empathy, traceability, modular depth, and contextual personalization in maternal AI tools. • The artifact generated six transferable design principles for emotionally intelligent, human-centered AI. • Findings show trust in AI emerges relationally through tone, transparency, and user-led meaning-making. • The study advances Design Science by showing how emotionally complex health domains enable world-to-theory knowledge creation.
Keywords:
Design science
Conversational AI
Maternal health
Human-centered AI
Femtech innovation
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