AI models are significantly integrated into every part of modern systems; their decisions are major driving factors for business outcomes, operational efficiency, customer experiences, and organizational reputation. Systems with transparent processes, accountability, fair decisions, and compliance with law and regulation are essential for building a reliable and trustworthy ecosystem. Integrating Responsible AI (RAI) principles into infrastructure across various sectors is paramount for its necessity and ethical benefits. The paper presents the integration of Responsible AI (RAI) principles with demand forecasting systems in the supply chain sector. At each stage of data pre-processing, model training, evaluation, and prediction, the techniques are integrated to mitigate the bias, evaluate fairness, enhance transparency, protect privacy, and make compliant decisions with overall accountability. The study paves the way for more reliable AI models without compromising performance and core objectives.