This chapter proposes a framework for explainable artificial intelligence (XAI) in enterprises. XAI has long been touted as a way to mitigate several issues in enterprise AI systems: (dis)trust, over- and under-reliance, opaqueness, lack of understanding, lack of compliance, bias and discrimination, and poor human decision-making. We argue that, despite having made progress in some of these areas, such as improving understanding and compliance, progress in others has been stunted due to incorrect assumptions about how AI tools are used and understood. We map out a framework for explainable AI that considers some recent positions on the use of explainable AI, with a focus on decision-making in enterprises.