While data protection is improved by including AI-powered cybersecurity solutions in cloud computing for healthcare systems, there are major ethical questions raised. With an eye on privacy, data security, bias, transparency, account-ability, autonomy, and regulatory compliance, this paper investigates these difficulties Because AI models need large datasets for training, patient privacy and data security are being called into question. Furthermore, prejudices ingrained in training data could lead to discriminatory policies, therefore influencing the equity of security policies. Accountability in artificial intelligence depends on openness in decision-making; nevertheless, complicated algorithms are often not explainable. Patients’ autonomy is also under danger since informed permission for the usage of data is still unclear. Furthermore negotiating the ethical terrain calls for following strict healthcare policies including HIPAA and GDPR. The study underlines the importance of ethical governance systems in order to strike a balance between moral obligations and technical developments. Examining these ethical issues will help the paper offer practical insights for healthcare organizations, legislators, and artificial intelligence developers to support ethical, open, and efficient cybersecurity policies in healthcare cloud computing.