In the domain of virtual assistants or conversational systems, it is important to empathise with the user. Being empathetic involves understanding the emotion of the ongoing dialogue and responding to the situation with empathy. We propose a novel approach for empathetic response generation, which leverages predicted intents for future response and prompts the encoder-decoder model to improve empathy in generated responses. Our model exploits the combination of dialogues and their respective emotions to generate empathetic response. As responding intent plays an important part in our generation, we also employ one or more intents to generate responses with relevant empathy. We achieve improved human and automated metrics, compared to the baselines.