Nvidia co-founder and CEO Jensen Huang said Thursday at the Goldman Sachs Technology Conference in San Francisco that cybersecurity is highly likely to become the next major application market for artificial intelligence. He argued that AI-driven automation of computer programming is fundamentally changing the tempo of cyber offense and defense, and that enterprise demand for security tools will surge as a result—giving AI computing power a new high-value application outlet.
Huang explained that as AI models dramatically lower the barrier to writing code, the volume of exploitable code and the number of vulnerabilities requiring rapid patching have surged in tandem. Development work that once took days can now be completed in hours or even less with AI assistance, meaning attackers have more opportunities to discover and exploit flaws, while defenders must patch at a much faster pace. “Cybersecurity is very likely to become the next major application scenario for AI,” he said.
Addressing the paradox of AI simultaneously creating problems and spawning market demand, Huang put it bluntly: “What better way to create demand than to create problems? What company wouldn’t want a market clamoring for its products, with customers lining up to buy? There are responsible ways to accomplish this, and there are less commendable ways.”
Huang’s remarks came after Nvidia last month issued a strong long-term sales forecast. That outlook further cemented Wall Street’s confidence that massive spending on AI data centers will continue to expand, and reinforced the market’s view that Nvidia will keep benefiting from that trend. Still, the tech industry continues to face a core investor question: whether the enormous capital being poured into AI infrastructure will ultimately generate sufficient economic returns. By pointing to cybersecurity as an application direction, Huang effectively offered a more concrete outlet for the commercial value of AI computing power.
Denies Circular Investment Concerns
Nvidia announced last week that it would acquire AI startup Hugging Face for approximately $13 billion (about NT$410 billion), further extending its footprint across the AI industry chain. The move prompted concerns among some market participants that a chip supplier investing in AI companies—which then channel large sums back into purchasing Nvidia chips and systems—could, to some degree, inflate the apparent demand in the AI market, creating what has been described as “circular transactions.”
Huang directly addressed those concerns during the conference, stressing that Nvidia’s investment decisions are grounded in a deep assessment of real demand. “It’s not circular, because we put in a little money and get back a lot of money. People are starting to realize that wherever I invest is not a bad investment target, because I am an informed investor. I take on no risk,” he said.
He further explained that before deploying company capital, he must see an opportunity that is “a sure thing.” He defined that standard as: the potential investment target must already have customers lining up to adopt its products or services, rather than taking on risk based purely on market narratives.
Market Impact and Observations
Huang’s positioning of cybersecurity as AI’s next major application scenario carries multiple implications for the market. Cybersecurity has long been a critical component of enterprise IT spending. If AI does indeed accelerate the emergence and evolution of security threats, enterprise demand for AI-driven security defense tools could see structural growth, opening up new revenue streams for Nvidia’s AI chips and related software ecosystem.
On the other hand, Nvidia’s expanding investment and acquisition footprint is prompting the market to re-examine capital flows within the AI industry chain. Huang’s assertion that he “takes on no risk” and only invests in “sure-win deals” appears aimed at assuaging investor concerns about M&A discipline, while also revealing Nvidia’s unique position within the AI ecosystem—as the core supplier of computing power, the company can directly observe actual customer demand, an informational advantage that gives it a level of visibility in investment decisions that ordinary investment institutions would find hard to replicate.
Notably, Huang’s logic that “creating problems is creating demand” also highlights the dual nature of AI’s development. While AI boosts productivity, it simultaneously creates new attack surfaces and risks—and those very risks become new market opportunities. For investors, whether AI applications in cybersecurity can truly translate into sustainable revenue growth will be a key area to watch going forward.
