Terms, such as artificial intelligence (AI), machine learning (ML), neural networks (NN), and deep learning (DL), have slowly crept into orthodontics over the last couple of decades and have spurred the rapid development of diverse clinical applications impacting various aspects of orthodontics. In this chapter, the authors have endeavored to simplify the AI jargon, elucidate the major domains of applications of AI and ML in the field of clinical orthodontics, provide an overview of the contemporary level of evidence on the use of these applications, highlight the challenges and limitations that preclude their envisioned incorporation into day-to-day orthodontic practice, and outline possible means of overcoming these challenges. The authors believe that AI-based orthodontic systems could potentially serve as auxiliary tools to assist routine clinical procedures in the near future. However, the outcomes derived from contemporary ML models should be interpreted with caution and used as a reference, rather than absolute norms at least during the nascent stages of AI-influenced clinical practice. The advancement of AI/ML algorithms and their subsequent incorporation into clinical orthodontics should ideally help encourage high-quality diagnosis, treatment planning, and, consequentially, continually enhance orthodontic treatment standards in the near future. Clinicians could well benefit by viewing AI as a support system, rather than a threat.