Artificial intelligence (AI) has made significant strides in cardiac imaging, offering advancements in image acquisition, risk prediction, and workflow automation. However, its readiness for widespread clinical adoption remains debated. This review explores both sides of the argument across key domains. It discusses the advantages and challenges of AI for cardiac imaging regarding pre-and post-processing, risk-stratification and prognostication, workflow augmentation, regulatory and ethical frameworks, and cost-effectiveness of AI tools. It will discuss the diagnostic accuracy shown by AI for automated measurements, improved image quality and workflow efficiency with AI-driven worklist prioritization. The potential of personalized care using AI-based prognostic models. It discusses regulatory frameworks for approving AI tools, while ethical frameworks to ensure safe and ethical use of AI are being implemented, simultaneously reimbursement is becoming available, signalling growing trust in their safety and efficacy. It also addresses the challenges AI has yet to overcome, such as the lack of generalizability across diverse populations, limited availability of outcome data and cost-efficacy studies. Despite progress, regulatory and ethical frameworks still struggle to keep pace with AI's rapid evolution, raising concerns about accountability, patient safety, bias, data privacy, and algorithmic transparency.