Artificial Intelligence (AI) is on the verge of becoming the next major transformative technology in healthcare, much like mobile technology has been in everyday life. AI's application in healthcare includes automation, from simple pattern recognition to advanced tools like AI-driven insulin pumps and predictive data analytics. The technology is gaining momentum due to advancements in computing power, cloud computing, and the availability of big data, supported by the Internet of Things (IoT) for real-time data collection. AI adds a new dimension to digitization in healthcare, influencing both clinical practice and patient experience. It supports clinical decision-making through predictive models that help determine treatment responses. Examples include Microsoft's MINE project, which uses machine learning to track myopia progression and predict refractive surgery outcomes. AI is also expanding telehealth and telehomecare, offering tools like AI bots for triage, smart assistants for homecare, and continuous monitoring of the elderly. Digital therapeutics, where software acts as a treatment modality, are also growing, with apps for monitoring visual acuity and managing macular diseases. While AI has significant potential, it is still in its early stages. Current AI is "narrow," excelling at specific tasks, while general AI with human-like intelligence remains distant. AI is seen as a labor-saving tool in healthcare, enhancing the efficiency and effectiveness of patient-facing professionals rather than replacing them. The future of AI in healthcare is promising, but its full potential is yet to be realized.Artificial Intelligence (AI) is on the verge of becoming the next major transformative technology in healthcare, much like mobile technology has been in everyday life. AI's application in healthcare includes automation, from simple pattern recognition to advanced tools like AI-driven insulin pumps and predictive data analytics. The technology is gaining momentum due to advancements in computing power, cloud computing, and the availability of big data, supported by the Internet of Things (IoT) for real-time data collection. AI adds a new dimension to digitization in healthcare, influencing both clinical practice and patient experience. It supports clinical decision-making through predictive models that help determine treatment responses. Examples include Microsoft's MINE project, which uses machine learning to track myopia progression and predict refractive surgery outcomes. AI is also expanding telehealth and telehomecare, offering tools like AI bots for triage, smart assistants for homecare, and continuous monitoring of the elderly. Digital therapeutics, where software acts as a treatment modality, are also growing, with apps for monitoring visual acuity and managing macular diseases. While AI has significant potential, it is still in its early stages. Current AI is "narrow," excelling at specific tasks, while general AI with human-like intelligence remains distant. AI is seen as a labor-saving tool in healthcare, enhancing the efficiency and effectiveness of patient-facing professionals rather than replacing them. The future of AI in healthcare is promising, but its full potential is yet to be realized.