Achromatopsia is a rare inherited retinal disorder characterized by the absence of cone photoreceptor function, resulting in color blindness, photophobia, nystagmus, and reduced visual acuity. Recent advances in artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), have transformed ophthalmic diagnostics and opened new avenues for early detection and treatment planning. This review paper presents a comprehensive analysis of achromatopsia, focusing on its clinical features, genetic basis, diagnostic approaches and therapeutic developments, with a strong emphasis on AI-driven methodologies. The paper also explores the integration of AI in retinal imaging, genotype–phenotype correlation, and gene therapy optimization. Finally, challenges, limitations and future research directions are discussed.