Mobile-First AI: Reaching the World’s Most Underserved Populations Through Everyday Devices
1
Public Health, Southern New Hampshire University, Manchester, United States
Popul. Med. 2026;8(Supplement Supplement 1):A778
ABSTRACT
INTRODUCTION:
Mobile-first artificial intelligence (AI) is rapidly expanding how public health teams reach people with basic phones and limited connectivity, literacy, or trust in formal health systems. In many low-resource and rural settings, mobile phones are now the most consistent point of contact for health education and behavior change communication, yet implementation remains fragmented and inequitable.¹
METHODS:
This practice based inquiry draws on implementation science frameworks, case studies, and program evaluations from AI enabled mobile interventions in academic, government, and community settings.²⁻⁵ Examples include SMS and WhatsApp-based agents, voice and chatbot tools, and multilingual micro learning delivered through low-bandwidth or offline-compatible platforms. Data from prior scoping reviews, training initiatives, and field pilots were analyzed to identify common design patterns, equity considerations, and enabling conditions for scale.¹⁻⁴
RESULTS:
Mobile-first AI tools showed promise for extending digital health literacy, providing tailored health promotion content, and supporting myth-busting during infectious disease and chronic disease campaigns among underserved groups.¹⁻³ Programs that combined simple user journeys, local languages, and trusted community or organizational partners reported higher engagement and repeat use. Integrating mobile AI into public health and health professions education improved learner confidence, practical skills, and ethical awareness related to AI informed practice.¹,²,⁴ Persistent challenges included data privacy and security, responsible use of sensitive conversational data, variable device and network access, limited workforce capacity to maintain tools, and uncertainty about governance, evaluation, and sustainability models.³⁻⁵
CONCLUSIONS:
Mobile phones, paired with well-designed AI tools, offer a powerful pathway to reach the “last mile” of health promotion with more inclusive, context-aware, and scalable solutions. To avoid deepening digital and AI inequities, public health leaders must guide ethical design, champion mobile-accessible AI literacy for both communities and professionals, invest in locally grounded partnerships, and rigorously evaluate real-world impact across diverse, low-resource settings.¹,³⁻⁵
Mobile-first artificial intelligence (AI) is rapidly expanding how public health teams reach people with basic phones and limited connectivity, literacy, or trust in formal health systems. In many low-resource and rural settings, mobile phones are now the most consistent point of contact for health education and behavior change communication, yet implementation remains fragmented and inequitable.¹
METHODS:
This practice based inquiry draws on implementation science frameworks, case studies, and program evaluations from AI enabled mobile interventions in academic, government, and community settings.²⁻⁵ Examples include SMS and WhatsApp-based agents, voice and chatbot tools, and multilingual micro learning delivered through low-bandwidth or offline-compatible platforms. Data from prior scoping reviews, training initiatives, and field pilots were analyzed to identify common design patterns, equity considerations, and enabling conditions for scale.¹⁻⁴
RESULTS:
Mobile-first AI tools showed promise for extending digital health literacy, providing tailored health promotion content, and supporting myth-busting during infectious disease and chronic disease campaigns among underserved groups.¹⁻³ Programs that combined simple user journeys, local languages, and trusted community or organizational partners reported higher engagement and repeat use. Integrating mobile AI into public health and health professions education improved learner confidence, practical skills, and ethical awareness related to AI informed practice.¹,²,⁴ Persistent challenges included data privacy and security, responsible use of sensitive conversational data, variable device and network access, limited workforce capacity to maintain tools, and uncertainty about governance, evaluation, and sustainability models.³⁻⁵
CONCLUSIONS:
Mobile phones, paired with well-designed AI tools, offer a powerful pathway to reach the “last mile” of health promotion with more inclusive, context-aware, and scalable solutions. To avoid deepening digital and AI inequities, public health leaders must guide ethical design, champion mobile-accessible AI literacy for both communities and professionals, invest in locally grounded partnerships, and rigorously evaluate real-world impact across diverse, low-resource settings.¹,³⁻⁵
| eISSN: | 2654-1459 |
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