Artificial intelligence (AI) represents the latest trend in dentistry, offering precise tools that can reshape the outcomes of our treatments. Considering the need to support and enhance the clinical decision-making process, this systematic review provides insights into the effectiveness and accuracy of various AI models. The aim is to evaluate the evidence on the effectiveness of various AI models for implant dentistry in diagnosis, treatment planning, prognosis, and implant system classification. In accordance with the PRISMA-DTA guidelines, a comprehensive search was conducted across multiple databases, including PubMed/Medline, Google Scholar, and Cochrane from the year 2016 to 2024. During the article screening and selection process, the PICO guidelines were followed. The methodological quality and bias of the study were assessed using the Critical Appraisal Skills Programme (CASP) 2023 checklist for systematic review and the CASP checklist for clinical prediction rule. It has been found that AI models are highly effective in detecting anatomical landmarks, improving surgical planning for implant positioning, predicting the outcome based on alveolar bone patterns around the implant, and providing accurate classification in detecting implant systems. For clinicians to achieve the greatest benefits for their patients, a broader knowledge of AI applications in implant dentistry and a deeper understanding of its insights are essential.