The Sustainable Development Goal (SDG) Target 3.8 has emphasized the persistence of health risks as a major challenge for emerging and developing countries. This challenge necessitates the achievement of Universal Health Coverage (UHC) by enhancing the infrastructure of the public sector. However, relying solely on public sector healthcare may not be sufficient to meet the needs of large populations, particularly in underdeveloped regions. Consequently, private sector healthcare solutions have emerged to fill service gaps, but they remain unaffordable for many low-income individuals. To the end, Health insurance can play a crucial role in making these services more accessible and affordable, but it faces several challenges including poor accessibility, low awareness, lack of skilled workforce, and corruption. The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies can offer solutions to these challenges. However, the adoption of technology in the insurance domain poses behavioral challenges that must be identified and addressed. This is particularly important in developing and emerging countries where markets are still underdeveloped, and information asymmetries are high. This study examines some of these challenges by studying people’s attitude towards humanoid agents. For this study a case study approach has ben used. Overall, addressing the challenges of health insurance and incorporating advanced technologies can provide a vital safety net against health risks to people.