There has been a tidal wave of recent interest in artificial intelligence (AI), machine learning and deep learning approaches in cardiovascular (CV) medicine. In the era of modern medicine, AI and electronic health records hold the promise to improve the understanding of disease conditions and bring a personalized approach to CV care. The field of CV imaging (CVI), incorporating echocardiography, cardiac computed tomography, cardiac magnetic resonance imaging and nuclear imaging, with sophisticated imaging techniques and high volumes of imaging data, is primed to be at the forefront of the revolution in precision cardiology. This review provides a contemporary overview of the CVI imaging applications of AI, including a critique of the strengths and potential limitations of deep learning approaches.