Artificial Intelligence (AI) has emerged as a transformative technology in healthcare and dentistry, offering unprecedented opportunities for improving diagnostic accuracy, treatment planning, and clinical efficiency. In endodontics, imaging plays a critical role in the diagnosis of pulpal and periapical diseases, root canal morphology assessment, treatment monitoring, and outcome evaluation. The integration of AI with digital imaging technologies, including periapical radiography, panoramic imaging, and Cone Beam Computed Tomography (CBCT), has significantly enhanced image interpretation and decision-making. AI-based systems utilizing machine learning, deep learning, and convolutional neural networks can automatically detect periapical lesions, identify root canal anatomy, evaluate treatment outcomes, and assist clinicians in complex diagnostic scenarios. This review explores current applications, technological foundations, clinical benefits, limitations, and future directions of AI in endodontic imaging. Findings indicate that AI-assisted imaging improves diagnostic consistency, reduces human error, and enhances clinical efficiency. However, challenges related to data quality, algorithm transparency, regulatory approval, and ethical considerations remain significant. The study concludes that AI will become an indispensable component of modern endodontic imaging and precision dental care.