Emerging technologies are transforming metal additive manufacturing (MAM), leading to improved precision, efficiency, and scalability. The impact of emerging technologies in MAM can be explored by studying how innovations such as artificial intelligence (AI), internet of things (IoT), digital twins, and material science enhance precision, efficiency, and MAM scalability. This study investigates the integration of artificial intelligence (AI), the internet of things (IoT), digital twin (DT), and advanced material science in MAM processes. AI enables real-time process optimization, defect detection, and predictive maintenance, whereas IoT facilitates seamless connectivity and data exchange across manufacturing techniques. Digital twins provide virtual replicas of MAM processes, enabling simulation, monitoring, and optimization of production workflows. Innovations in material science are expanding the range of metals and alloys available for MAM, improving the mechanical properties, and reducing material waste. Inaddition, sustainable manufacturing practices are being incorporated to minimize energy consumption and environmental impacts. Challenges such as high initial costs, material limitations, and the need for skilled labour are also discussed. The study concludes by highlighting the transformative potential of these technologies for improving MAM.