The aim of the study was to give a general account of the ethical principles that need to be infused in the design, development and deployment (DDD) of AI powered systems. The study was guided by two theories, the deontological theory of ethics and the descriptive theory. The study used qualitative survey design and convenient sampling was done to get a sample of 20 experts in various fields related to moral philosophy, AI software engineers, policy makers, end users and legal practitioners. Participants were conveniently selected to cover a wide spectrum of players involved in the AI development and deployment. The data collection focused of collecting qualitative data through focused group discussion and expert interviews that were guided by interview schedules. The findings showed that various stakeholders in the AI industry had concerns related to bias, privacy issues, accountability, transparency and prejudice. The participants highlighted concerns on privacy issues as important. Participants demonstrated concerns over the safety of personal data in AI development, data security challenges and propensity for misuse for misuse of personal information. Participants stressed on need of developing AI systems and testing them to prevent the reprojection of inequalities through the AI outputs. Other emergent themes were accountability, responsibility for AI generated decisions, lack of clear frameworks for handling errors or harm. Transparency was repeatedly mentioned as needing explainability in developing trust in AI products by all stakeholders in ethical their ethical deployment. The research concludes handling of ethical issues in AI development and use necessitates a multidisciplinary approach that combines technological, regulatory and ethical perspectives. The study recommends establishing comprehensive rules and regulations to govern AI development, stressing on fairness and inclusivity in the designing of algorithms alongside formation of functioning mechanisms for oversighting AI industry in achieving accountability and transparency. This research value is that it advances knowledge of AI ethics further by providing new insights and dimensions from the diverse perceptions of AI stakeholders. It provides the impetus for including ethical issues in the whole lifecycle of AI systems which ranges from design, development to deployment. Further investigations need to be done in order to provide a framework for designing legislation that addresses the intricate ethical issues emergent with AI technologies.