Explaining the results of an AI model is essential in many cases to make it acceptable to business users and regulators.  The complexity of defining the model increased exponentially with the advent of massive deep neural models with billions of connections in the new age of Gen AI models.  This session provides an efficient approach to building Explainability in AI models.  The attendees will be introduced to state of the art in Explainability with live examples.