Barriers to Clinical Integration of Artificial Intelligence in Computer-Assisted Dental Implant Surgery: A Critical Review.

Abstract

Translating artificial intelligence (AI) from virtual implant planning to dental implant surgical execution is obstructed by technical, clinical, and socioethical barriers. This critical review appraises these impediments, focusing on tomographic data heterogeneity, closed hardware ecosystems that block kinematic data extraction, and algorithmic opacity that erodes clinician trust. Current literature over-relies on static retrospective validations with high bias risk. This gap should be bridged by a roadmap prioritizing federated learning, open-source interoperability, explainable AI, and prospective multicenter trials to establish algorithms as dynamically adaptive surgical systems.