Metamaterials (MMs) embody engineered properties that transcend the limitations of natural materials, presenting both a myriad of untapped opportunities and formidable challenges. Despite many metamaterials finding actual applications and a large number of metamaterial designs proving benefits for many applications, they still have not reached their full mainstream adoption. A key focus is on the hurdles in the design and fabrication of MMs, particularly the complex issue of anisotropy and the significant discrepancies often observed between theoretical models and experimental results. The effects of anisotropy on a metamaterial are critical in the context of applications like acoustic cloaking and negative thermal expansion, where the orientation and arrangement of unit cells in the materials play a pivotal role like grain orientation in piece of timber. Additionally, the brittleness under cyclic loading and the specificity to certain frequency bands are discussed as critical limitations that hinder the broader applications of metamaterials. This vision for the future of MMs offers a spotlight on innovative trends and methods poised to tackle these challenges. Among these solutions are the additive manufacturing and machine learning techniques discussed in this work, which offer rapid prototyping and optimization capabilities to locate problems with the material and revise it. By bridging the gap between theoretical and practical feasibility, these advancements herald a new era for MMs across the full spectrum of applications.