The paper presents a comprehensive conceptual framework for ethical AI development in IT systems, addressing the societal, ethical, and legal concerns arising from the rapid advancement of AI technologies. The framework integrates multidisciplinary perspectives from ethics, computer science, law, and philosophy, emphasizing the importance of ethical considerations at every stage of the AI development lifecycle. Key components include transparency, accountability, fairness, privacy, and security. Transparency ensures that AI algorithms and decision-making processes are comprehensible and explainable, fostering trust and enabling scrutiny. Accountability mechanisms attribute responsibility for AI-driven outcomes and facilitate recourse in cases of harm or injustice. Fairness advocates for mitigating biases and discrimination across diverse demographic groups. Privacy protection measures safeguard personal data from unauthorized access or misuse, while robust security protocols defend against malicious exploitation and adversarial attacks. The framework aims to empower developers, policymakers, and organizations to navigate the complex ethical landscape of AI development, ensuring responsible and beneficial deployment of AI technologies. The adoption of such a framework is crucial for harnessing the transformative potential of AI while upholding fundamental ethical principles and societal values.The paper presents a comprehensive conceptual framework for ethical AI development in IT systems, addressing the societal, ethical, and legal concerns arising from the rapid advancement of AI technologies. The framework integrates multidisciplinary perspectives from ethics, computer science, law, and philosophy, emphasizing the importance of ethical considerations at every stage of the AI development lifecycle. Key components include transparency, accountability, fairness, privacy, and security. Transparency ensures that AI algorithms and decision-making processes are comprehensible and explainable, fostering trust and enabling scrutiny. Accountability mechanisms attribute responsibility for AI-driven outcomes and facilitate recourse in cases of harm or injustice. Fairness advocates for mitigating biases and discrimination across diverse demographic groups. Privacy protection measures safeguard personal data from unauthorized access or misuse, while robust security protocols defend against malicious exploitation and adversarial attacks. The framework aims to empower developers, policymakers, and organizations to navigate the complex ethical landscape of AI development, ensuring responsible and beneficial deployment of AI technologies. The adoption of such a framework is crucial for harnessing the transformative potential of AI while upholding fundamental ethical principles and societal values.