Gold nanoparticles (AuNPs) have emerged as a versatile platform in biomedical applications, particularly in drug delivery, cancer therapy, and diagnostics, due to their unique physicochemical properties. This review focuses on the integration of computational methods and artificial intelligence (AI) with nanotechnology to optimize AuNP-based therapies. Computational modeling is essential for understanding the interactions between AuNPs and biological molecules, guiding nanoparticle design for improved targeting, stability, and therapeutic efficacy. Recent advancements, including AI-driven models in precision cancer therapy and the combination of AuNPs with antimicrobial peptides (AMPs) to combat drug-resistant pathogens, are highlighted. The review also discusses challenges such as toxicity, targeting efficiency, and the need for scalable synthesis, alongside the limitations of computational modeling in capturing complex biological environments. Emphasizing the importance of ongoing research and interdisciplinary collaboration, this review underscores the potential of integrating computational insights with AuNP technology to enhance the precision, safety, and effectiveness of therapeutic and diagnostic approaches.