Clear Aligner Orthodontic Therapy: A Comprehensive Narrative Review of Materials, Clinical Evidence, Biomechanical Limitations, and the Emerging Role of Artificial Intelligence

Background: Clear aligner therapy (CAT) has become one of the most widely adopted orthodontic modalities overthe past two decades, driven by aesthetic demand, digital workflow integration, and perceived comfort advantagesover fixed appliances. However, its biomechanical envelope remains narrower than that of conventional brackets andwires, and clinicians continue to debate which cases fall inside and outside its predictable range.Materials and Methods: This narrative review compiles evidence from PubMed, Scopus, Web of Science, andConsensus covering publications from 2013 to 2026, without a formal PRISMA protocol, on the materials science,clinical effectiveness, periodontal and microbiological effects, biomechanical limitations, and artificial intelligence(AI) applications of CAT.Global Scientific Journal | www.globalscientificjournal.comVolume 14, Issue 8, August 2026 Edition | ISSN 2320-9186Page 2 of 10Results: CAT achieves outcomes comparable to fixed appliances in mild-to-moderate malocclusions and offersperiodontal and hygiene advantages, but remains less predictable for root torque, rotation of rounded teeth, verticalmovements (intrusion/extrusion), and complex extraction cases, where fixed appliances retain superiority. Skeletaldiscrepancies, severe crowding, and open-bite correction in hyperdivergent patients frequently require adjuncts(temporary anchorage devices, attachments) or hybrid fixed/aligner protocols. AI is increasingly embedded across thealigner workflow — in diagnosis and cephalometric analysis, root and bone movement prediction, attachment design,and remote monitoring platforms — narrowing, but not eliminating, the gap between predicted and achieved toothmovement.Conclusion: Clear aligners are an effective, evidence-based option for a well-defined subset of malocclusions.Recognizing their biomechanical limitations and reserving them for appropriately selected cases — with adjunctivemechanics or AI-assisted planning where indicated — is essential for predictable outcomes. Further prospective,standardized research is needed to validate AI-driven prediction tools against actual clinical results.