Objective: This systematic literature review aims to comprehensively synthesize existing evidence on Visual Effects (VFX) and Artificial Intelligence (AI) using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The primary objective is to map the landscape of VFX and AI, examining the historical development of VFX techniques and practices in the context of AI advancements. Methods: Following PRISMA guidelines, a thorough search of five electronic databases—IEEE Xplore, Scopus, Taylor & Francis Online, ACM Digital Library, and ScienceDirect—was conducted to identify articles published up to April 18, 2024. Inclusion criteria encompassed English-language journal articles. Independent reviewers screened articles for eligibility, resolving discrepancies through consensus. Data extraction and synthesis were performed systematically. Results: A total of 41 studies met the inclusion criteria and were included in the review. These studies covered a wide range of topics related to VFX and AI, with various study designs. The findings are presented in a narrative synthesis. Discussion: The review indicates that AI development in VFX is comprehensive, covering topics such as image processing, inpainting, video processing, 3D modelling, rendering, deepfake technology, style transfer, tracking, animation, simulation, rigging, texture compression, and depth map enhancement. These advancements highlight the transformative role of AI in enhancing creative expression, production efficiency, and the quality of visual effects. Conclusion: This systematic literature review provides a comprehensive overview of the current state of knowledge on AI and VFX. The integration of AI into VFX is profoundly transforming the industry, enhancing creative expression, production efficiency, and the quality of visual effects. Continued advancements in AI technologies promise to further revolutionize VFX practices, offering new possibilities and efficiencies for future productions.