In today’s data-driven business environment, organizations encounter challenges in effectively utilizing predictive analytics to drive decision-making while ensuring ethical data practices. This paper proposes an AI-powered predictive analytics framework to improve operational efficiency, enhance decision accuracy, and maintain data privacy and security. The system integrates machine learning techniques with ethical governance policies, enabling real-time insights from large datasets. AI helps businesses analyse past data and predict future trends by utilizing predictive and prescriptive analytics. This allows for more proactive and well-informed initiatives. Machine learning is essential for automating data-driven decisions and providing businesses with real-time insights that enable them to react rapidly to changing market circumstances. A comparative evaluation demonstrates that the system achieves 92.5% prediction accuracy, significantly improving data processing speed and operational cost savings. This research contributes a practical, scalable, and ethically responsible approach to integrating AI-driven predictive analytics into business processes, offering both technological innovation and a model for responsible data use. This framework is applicable across diverse industries, including retail, finance, and healthcare, where data-driven insights are essential for strategic operations.