The rapid penetration of Artificial Intelligence (AI) into everyday life has transformed people’s interaction with digital technologies. From chatbots to personal assistants, AI systems are increasingly embedded in domestic environments. Consequently, women and children are more likely to be exposed to AI because their daily activities, such as caregiving, learning, and digital consumption, are often targeted by the algorithmic personalized content, leading to frequent interaction with AI systems. AI expansion raises critical concerns regarding gender bias and safety, particularly affecting women and children as primary users. Existing AI systems often fail to incorporate gender-sensitive and child-protection content, resulting in risks such as exposure to inappropriate content and harmful materials. This paper addresses this gap by proposing a conceptual framework for designing trustworthy AI systems that integrate gender responsiveness and child safety as core design principles. Drawing on interdisciplinary literature in AI ethics, gender studies, and digital governance, the study develops the SAFE AI Framework, comprising four key dimensions: Safety, Accountability, Fairness, and Explainability. The framework emphasizes the importance of bias mitigation strategies, age-appropriate content filtering, parental monitoring systems, and transparent AI decision-making processes. This study argues that embedding gender-responsive and child-safe principles into AI systems is essential for building public trust and ensuring responsible AI adoption.