.

This study (published at Columbia University in the City of New York) explores the third party risks associated with NVIDIA’s rapid growth as a leading provider of GPUs and AI technology. Despite NVIDIA’s remarkable stock performance, concerns arise around its risk management capabilities, especially given dependencies on third-party technology providers, supply chain vulnerabilities, and the broader implications of AI adoption. Key risks include competitor, vendor, supply chain, and cybersecurity threats, intensified by geopolitical and regulatory challenges. NVIDIA’s partnerships and ecosystem expansion with firms like Lambda, World Wide Technology, and Deloitte highlight the dual nature of opportunities and risks in deploying AI infrastructure. This analysis emphasizes the importance of proactive risk assessment and a comprehensive mitigation framework to address NVIDIA’s multifaceted challenges in the evolving AI landscape, where control over GPUs plays a pivotal role.

“Any sufficiently advanced technology is indistinguishable from magic.”

— Arthur C. Clark

Artificial Intelligence (AI) represents a technological revolution poised to reshape industries and economies worldwide, yet it also introduces significant operational and strategic risks. Our study examines NVIDIA, a leading provider of GPUs and AI technologies, focusing on the operational risks stemming from third-party technology providers, the supply chain and the broader implications of AI adoption. Despite NVIDIA’s meteoric stock performance, which has risen by 3,000% in the past three years, questions persist regarding the company’s ability to manage enterprise risk amidst its rapid growth effectively.

How essential and critical is it to become AI and NVIDIA experts in deploying and coding intelligent applications? What is the true value of being GPU-rich in the current market environment?

Companies are made strong by internal cultural powers and reinforced by an ecosystem of third party providers supporting their growth and market success. Key third-party risks identified include competitor risks, supply chain risks, vendor risks, as well as cybersecurity risks. As NVIDIA expands its ecosystem through partnerships with firms like Lambda, World Wide Technology, Deloitte, and Equinix, the integration of cutting edge AI infrastructure solutions amplifies both opportunities and risks. Notably, geopolitical tensions and regulatory challenges further complicate NVIDIA’s global operations and market positioning. Analyzing these dynamics underscores the importance of implementing proactive risk assessment strategies and developing a comprehensive framework for mitigating the multifaceted risks inherent in NVIDIA’s AI-driven business and predicting emerging challenges that may significantly impact its strategic objectives and operational continuity.

Leaders often focus on the strong business growth of revenue, while the aftermath of risk is often addressed much later in time. GPU rich is a new status, and those who control GPUs seem to control AI. Vectorization of words in neural networks, tokenization, and creation of dimensions in thousands enabled Generative Pre-Trained Transformers in tensor flow is producing outputs similar to human language capability.

We are exploring third party risk possibilities, using the logic of AI deep learning tactics to assess risks that are not always visible from a distance or at a close. Understanding of direction in the AI world is very limited. Is it in software or hardware? Or is it a combination of both? At what proportion? Only time shows where the most value can be created, and how the third party risks emerge.

Authors: Cai, Ziyi; Krehel, Ondrej; Wang, Aolin; Wu, Mengqi; Zhai, Jingsheng and full link Unmasking Vulnerabilities: Assessing Third-Party Risks in NVIDIA.