Artificial intelligence is rapidly transforming healthcare, and orthodontics is no exception. The digitization of clinical records, radiographic imaging, intraoral scanning, and treatment monitoring has created unprecedented opportunities for machine learning and deep learning integration into daily practice. This lecture reviews AI’s role across the patient journey, from automated cephalometric analysis and anatomical landmark detection to facial morphology assessment and diagnostic decision support. Predictive algorithms for growth assessment, extraction decisions, and orthognathic surgery planning are examined, alongside AI-driven clear aligner therapy — automated tooth segmentation, virtual simulation, and remote monitoring platforms. The emergence of generative AI and large language models is discussed for clinical documentation, patient communication, and research support. Critical challenges, including data quality, algorithmic bias, explainability, privacy, and regulatory compliance, are addressed. The presentation concludes that the future of orthodontics lies not in replacement but in synergistic human–AI collaboration, making AI literacy an essential contemporary clinical competency.