Purpose: Artificial intelligence (AI) has emerged as a powerful tool in plastic and reconstructive surgery, particularly in predicting postoperative outcomes, results, and complications. We present a current and comprehensive overview of AI applications in Plastic and Reconstructive Surgery (PRS), highlighting its potential, whilst addressing the associated drawbacks and ethical limitations. Methodology: A literature search was conducted in December 2023 using MeSH terms "Artificial Intelligence" and "Surgery, Plastic." Databases searched included PubMed, Medline, EMBASE, and the Cochrane Library, resulting in 96 papers for review. After exclusions, 52 papers were identified. Results: This review identified machine learning (ML), deep learning (DL), natural language processing (NLP), computer vision, and data science as crucial domains of AI in PRS. Within these domains, computer vision demonstrated effectiveness in predicting postoperative aesthetic outcomes, while ML was successful in predicting microvascular complications and DL showed promise in complex reconstruction, particularly in the craniofacial niche. Additionally, NLP was found to be useful in gauging patient interest and facilitating patient education. Conclusion: The systematic review highlights the potential of AI in PRS, particularly in the identified domains of ML for predicting complications, computer vision for simulating postoperative outcomes, and DL for complex facial reconstruction. Ongoing research in these areas may help using AI to improve patient outcomes, but it is equally important to address the limitations of technology and the ethical implications to ensure its responsible integration.