With the rapid development of Generative Artificial Intelligence (Generative AI), global demand for high-performance computing and AI computing power has continued to surge. Graphics Processing Units (GPUs) have become critical infrastructure driving the digital economy and industrial innovation. Leveraging technological innovations in GPUs and the construction of the CUDA software ecosystem, NVIDIA has secured a leading position in the global AI computing market. Adopting the case study method, literature analysis and strategic management tools, this paper conducts a systematic investigation into NVIDIA. By integrating competitiveness evaluation, the BCG Product Portfolio Matrix and the TOWS Matrix, it analyzes the company’s competitive advantages, product portfolio allocation and future development strategies. The research reveals that NVIDIA’s core competitive edges stem from the CUDA ecosystem, highly focused R&D capabilities, robust financial standing and in-depth partnerships for advanced process supply chains, which collectively form an inimitable competitive moat. Nevertheless, the company also faces multiple risks, including over-concentrated supply chains, restricted access to regional markets, excessive reliance on major customers and challenges from emerging competing technologies. The BCG Matrix analysis indicates that the data center business falls into the Star category, while the gaming business acts as a Cash Cow. The autonomous driving and edge computing businesses demonstrate strong growth potential as emerging segments. Furthermore, four strategic directions—growth, diversification, turnaround and defense—are proposed via the TOWS Matrix to address the rapidly evolving industrial landscape. The findings can serve as a reference for Fabless semiconductor enterprises in formulating competitive strategies, building ecosystems and managing risks, and also expand the application scope of strategic management theories in the AI chip industry.