CT imaging has evolved significantly, moving from single-slice scanners to multi-slice, dual-energy, and now photon-counting CT (PCCT). Artificial Intelligence (AI) has been integrated into the imaging workflow to improve image reconstruction, diagnostic accuracy, and patient outcomes. This study focuses on the evolution of CT scanners with an emphasis on the advancements brought by PCCT and AI, particularly in a tertiary care setting. Conclusion: Photon-counting CT and AI offer revolutionary advancements in radiology by improving image quality, reducing radiation dose, and enhancing diagnostic precision. Their integration into clinical practice is crucial for personalized patient care and efficient workflow management in tertiary care centers. Introduction CT imaging has undergone remarkable transformation since its inception in the 1970s. The introduction of photon-counting technology and the integration of artificial intelligence are two major milestones that have redefined the diagnostic potential of CT scanners. This evolution is essential for tertiary care centers where high patient volumes and diagnostic accuracy are critical. Aim To study the evolution of CT scanners, focusing on photon-counting technology and AI integration, and their impact on clinical outcomes in a tertiary care setting. Objectives To evaluate the technological advancements from conventional CT to photon-counting CT. To assess the role of AI in improving CT imaging quality and diagnostic accuracy. To analyze the impact of PCCT and AI on radiation dose reduction and patient outcomes. Materials and Methods The study involves a retrospective analysis of the progression of CT technology within a tertiary care center, focusing on the transition from traditional to photon-counting CT and the incorporation of AI-based solutions for imaging and diagnostics. Results Image Quality: PCCT showed a significant improvement in image resolution compared to conventional CT, with sharper images and better material differentiation. Radiation Dose: A reduction in radiation dose was observed with PCCT, with a 20-40% decrease compared to traditional CT techniques. AI Integration: AI-assisted image reconstructions reduced noise and enhanced the diagnostic accuracy, particularly in complex cases. Clinical Outcomes: The combined use of PCCT and AI led to earlier detection of pathologies and more accurate diagnoses, reducing the need for repeat scans. Conclusion: the ongoing advancements in CT technology, marked by the introduction of PCCT and AI, are set to transform medical imaging, offering improved diagnostic accuracy, faster scanning, and reduced radiation exposure, paving the way for more efficient and personalized healthcare solutions.