Today’s AI tools can produce highly accurate results, yet advanced machine learning models often remain a black box. Transparency is essential when businesses are relying on AI more than ever. Explainability needs to be part of the equation when building AI systems we can trust. Organizations should start by including explainability as one of the key principles within their responsible AI guidelines by applying FEAT (Fairness, Ethics, Accountability and Transparency) for building responsible AI products. Through this talk, I will discuss how we can benefit from AI and minimize risk by making ML models explainable for businesses.