With these philosophical foundations laid, we turn to the practical task of establishing ethical frameworks—guidelines that ensure AI developments are aligned with humanity’s highest values and aspirations. Ethical frameworks for AI are crucial in navigating the complex landscape of Angelic Intelligence, especially as these technologies become more integrated into various aspects of life globally. Academic research highlights the importance of developing ethical frameworks that are inclusive of diverse cultural perspectives. Studies have shown that ethical considerations and values can vary significantly across cultures, influencing how AI is perceived and utilized. For instance, research published in the Journal of Global Ethics emphasizes that Western frameworks often prioritize individual rights and autonomy, while Eastern philosophies may focus more on collective well-being and harmony. By incorporating a wide range of cultural values into AI ethics, we can create more robust and universally applicable guidelines. This multicultural approach not only enhances the relevance and acceptance of ethical frameworks but also ensures that AI technologies contribute positively to all societies. Research by Floridi et al. (2018) in “AI4People - An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations” provides a comprehensive analysis of ethical principles for AI, emphasizing the importance of transparency, accountability, and fairness. This framework is designed to guide policymakers and developers in creating AI systems that respect human dignity and rights. Binns (2018) in “Fairness in Machine Learning: Lessons from Political Philosophy” explores how principles of distributive justice can inform the design of fair AI systems, suggesting that AI should be designed to avoid reinforcing social inequalities. Additionally, Jobin, Ienca, and Vayena (2019) in “The Global Landscape of AI Ethics Guidelines” survey numerous ethical guidelines worldwide, highlighting common principles such as privacy, accountability, and the prevention of harm. These studies collectively underscore the need for interdisciplinary approaches to AI ethics, integrating insights from philosophy, law, and computer science to develop robust frameworks that can adapt to the evolving landscape of AI technology.