Jensen Huang, NVIDIA's CEO for over three decades, balances a charismatic public image with a reputation as an intensely demanding leader who has built the world's most dominant AI chip company through uncompromising vision and persistence. During his recent visit to Korea in early June 2026, Huang charmed business leaders and the public alike, handing out snacks and greeting people with ease. Yet behind this friendly exterior lies a strategist whose leadership style and ambitions carry major implications for Korea's tech industry and the future of artificial intelligence.

What Makes Jensen Huang Different From Other Tech Leaders?

Huang shares several traits with other high-profile tech entrepreneurs like Elon Musk. Both are immigrant engineers, self-described workaholics, and demanding leaders known for raising their voices in meetings. However, Huang's approach differs in one crucial way: he rarely dismisses employees, even when delivering harsh criticism.

Inside NVIDIA, Huang earned a fearsome reputation. According to "The Thinking Machine: Jensen Huang, NVIDIA, and the World's Most Coveted Microchip" (2024) by Stephen Witt, Huang frequently expressed anger and harshly criticized employees in public settings. These episodes became known internally as "Huang's fury." On one documented occasion, he asked an employee about their years of service and salary before suggesting they return all compensation earned to that point, with dozens of executives witnessing the exchange. Huang justified this approach by arguing that openly discussing mistakes helped the organization learn from failure, though some employees reportedly experienced it as verbal abuse.

What distinguishes Huang's leadership is his combination of long-term vision with extraordinary persistence. A phrase he frequently repeated in meetings was "O.I.A.L.O.," short for "Once in a Lifetime Opportunity." He identified such opportunities in two technologies that many regarded as unlikely to succeed: parallel computing and neural networks.

How Did NVIDIA Become the World's AI Chip Leader?

Huang's strategic decisions transformed NVIDIA from a graphics company into the dominant force in artificial intelligence. His vision and persistence across three decades created the foundation for today's AI boom:

• Parallel Computing Innovation: Huang pursued parallel computing technology, which enabled immense computing power without relying exclusively on traditional supercomputers, fundamentally changing how AI systems could be built and scaled.
• GPU Development: NVIDIA introduced the world's first graphics processing unit (GPU) in 1999, a chip architecture that would later prove essential for training large AI models far more efficiently than traditional processors.
• CUDA Software Platform: In 2007, NVIDIA released CUDA, a software platform that allowed researchers and developers to harness GPU computing power, democratizing access to parallel computing and laying groundwork for the AI era.
• AI Pivot: After 2013, the company increasingly transformed itself into an AI-focused enterprise, positioning itself at the center of the deep learning revolution that followed.

By 2025, NVIDIA briefly became the world's most valuable company by market capitalization, a testament to Huang's three-decade bet on technologies that many initially dismissed.

What Is NVIDIA's Latest Strategic Move in AI Computing?

Huang's strategy has evolved from hiding NVIDIA's strength while waiting for the right moment to openly competing with established rivals. In 2023, Huang described NVIDIA's relationship with Intel using a playful metaphor: "We do not compete with Intel. When Intel gets close, I grab my chips and run away." That posture changed dramatically in early June 2026.

Huang

Earlier in June, Huang unveiled RTX Spark, a next-generation AI laptop chip that combines a CPU and NVIDIA's Blackwell GPU architecture into a single processor. Because agentic AI, a form of autonomous artificial intelligence that can make decisions and take actions independently, can run directly on the chip, analysts described RTX Spark as a significant step toward the AI PC era. The announcement caused shares of established competitors, including Intel, to fall, signaling that NVIDIA's strategy had shifted from evasion to direct competition.

On June 9, 2026, NVIDIA and several Korean companies announced plans to cooperate on projects including the construction of next-generation AI data centers, often called "AI factories," in Korea. This partnership represents recognition of Korea's strengths in manufacturing and what experts call "physical AI," the hardware infrastructure required to run advanced AI systems at scale.

Why Should Korean Companies Be Concerned About NVIDIA Dependency?

While NVIDIA's partnership with Korean firms is encouraging, it also presents a strategic challenge. Huang is a disciplined strategist who will closely examine the competitiveness of Korea's manufacturing industries, including semiconductors. If Korean companies hope to avoid becoming dependent on NVIDIA's AI platform, they must preserve overwhelming technological advantages of their own.

The stakes are high. NVIDIA's dominance in AI chips has created a situation where companies worldwide rely heavily on NVIDIA's technology stack, including CUDA, the software platform that allows developers to build AI applications. To maintain independence, Korean manufacturers will need to sharpen their capabilities continuously, just as Huang spent more than three decades pushing both himself and NVIDIA beyond their perceived limits.

Huang's personal work ethic underscores his commitment to this philosophy. Despite his public visibility and the company's massive success, he reportedly still works 12 to 14 hours per day, seven days a week. This relentless approach has defined NVIDIA's culture and its competitive edge in an industry where innovation cycles move at breakneck speed.

The contrast between Huang's warm public persona and his demanding internal leadership style reveals a fundamental truth about NVIDIA's success: the company's dominance in AI chips stems not from charisma or marketing, but from an uncompromising commitment to technological excellence and a willingness to challenge both employees and competitors to exceed what they thought possible.