This study applies Generative Design with Artificial Intelligence (GDAI) to the front suspension lower control arm (LCA) to achieve weight reduction while preserving structural integrity and performance. Traditionally, LCAs are manufactured from stamped steel for economy and standard passenger cars or from cast aluminum for premium vehicles. In this work, GDAI is applied to aluminum AlSi10Mg to address excess weight while ensuring equivalent mechanical performance. The generative design framework integrates finite element analysis (FEA) with AI-driven geometry optimization to produce lightweight and structurally efficient solutions. Optimization results indicate a potential weight reduction of 17.5% compared with the baseline model, alongside stress distribution improvements of up to 10% under identical load cases. Additional benefits include optimized geometry, reduced material consumption, and enhanced load path continuity. Furthermore, the approach reduces design iteration time by 50% compared to conventional CAD-based methods. The findings highlight the capability of AI-driven generative design to deliver high-performance suspension LCAs with reduced mass, improved durability, shorter development cycles, and accelerated additive manufacturing outcomes. These results contribute to improved vehicle efficiency, lower production costs, and enhanced sustainability.