A significant advancement in additive manufacturing has been achieved with the development of 'MechStyle,' a generative AI tool by researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), in collaboration with Google, Stability AI, and Northeastern University. This innovative system addresses a critical challenge in 3D printing: enabling the creation of personalized objects that are not only visually appealing but also structurally sound and durable for everyday use. Previously, AI-driven 3D model customization often resulted in impractical designs, with studies indicating that only about 26% of such modified models retained their structural viability. This was primarily because AI systems lacked an understanding of the physical forces and material properties essential for real-world functionality. 'MechStyle' overcomes this limitation by integrating finite element analysis (FEA) simulation. This allows the system to predict how aesthetic changes made by the generative AI will impact the object's strength and stability. When users provide a 3D model and a text or image prompt for personalization, MechStyle modifies the geometry while continuously simulating the effects on vulnerable areas, thereby preventing structural failure. The tool offers two modes: a freestyle mode for creative exploration and a 'MechStyle' mode that rigorously evaluates structural impact, ensuring designs are physically viable after fabrication. Testing with 30 diverse models, stylized to resemble various textures like bricks or cacti, demonstrated that MechStyle could achieve up to 100% structural viability. This breakthrough has broad implications, making personalized 3D printing more accessible for hobbyists and professionals alike, and extending its potential applications to consumer goods, artistic objects, and crucial assistive technologies like custom splints or utensil grips, where both aesthetics and functionality are vital. The research signifies a move towards more intelligent and practical AI applications in the physical world, bridging the gap between digital design flair and real-world mechanical integrity. While the current system cannot repair initially unsound models, future developments aim to enhance this capability and allow for generating 3D models from scratch based on user prompts.