Additive Manufacturing (AM), commonly referred to as 3D printing, has emerged as an innovative and efficient method for the fabrication of prototypes and customized artifacts. AM offers notable advantages in material utilization, effectively mitigating waste generation while enabling the optimization of designs to meet specific process requirements, particularly concerning weight and geometric intricacies. Furthermore, AM holds considerable promise in augmenting supply chain efficiency, curtailing energy consumption, and streamlining resource allocation, thereby conferring multifaceted benefits to manufacturing processes. Other AM applications occur in biomedical, aerospace, buildings and protective structures. It is imperative to recognize that the scope of AM transcends traditional three-dimensional methodologies, encompassing a diverse spectrum of manufacturing techniques characterized by varying degrees of complexity and applicability. Artificial Intelligence (AI) stands as a pivotal focal point in contemporary discourse, encompassing a plethora of approaches including Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, and Generative Models. While the potential of AI is vast, both academia and industry confront substantial challenges in effectively harnessing its capabilities. The convergence of AM and AI engenders unprecedented opportunities across a myriad of industries, spanning domains such as food additives, pharmaceuticals, mechanical engineering, chemistry, energy, aerospace, and defense. Tailored applications necessitate bespoke solutions, with AI emerging as a potent instrument for addressing critical imperatives such as design optimization, material selection, reduce energy consumption, cost-effectiveness, process stability, safety monitoring, copyright protection, and counterfeit prevention. This paper endeavors to assess the contemporary landscape of AM and AI integration, delineating emerging trends, delineating challenges, and elucidating prospects for the future. Through an exploration of the synergies between these transformative technologies, this study aims to furnish insights into potential avenues for sustainable innovation and advancement across diverse sectors.