This chapter explores how artificial intelligence (AI) is transforming ophthalmology practice management by enhancing clinical decision-making, education, workflow, and patient engagement. AI systems—including machine learning (ML), computer vision, and large language models (LLMs) such as ChatGPT, are increasingly used to analyze complex ophthalmic data from imaging, electronic health records (EHRs), and wearable devices. In practice, AI supports ophthalmic physicians in predictive diagnostics, triage, administrative automation, and documentation, ultimately boosting efficiency and clinical precision. Despite these advances, barriers to implementation remain due to ethical, methodological, and operational challenges. The chapter reviews current uses in ophthalmic education, including AI-assisted simulations and case-based learning, as well as decision support systems and workload management. It also discusses issues of data privacy, algorithmic bias, professional training, and human–AI collaboration. Responsible adoption will require strong ethical oversight, transparent governance, and ongoing efforts to incorporate AI literacy into ophthalmic education. When properly implemented, AI can improve both clinical and operational aspects of ophthalmology, promoting a more efficient, equitable, and patient-centered care model.