Jensen Huang: In the AI era, what major you study doesn't matter. Storytelling, creativity, and judgment are the true moats.

NVIDIA CEO Jensen Huang, when interviewed by Singapore’s CNA this week, expressed anxiety about “what majors to study in the AI era,” saying: What you study isn’t important—what matters is the ability to tell stories, creativity, and judgment.
(Background: Nvidia’s Jensen Huang: The “bloodbath” in computer science will be for English majors; liberal arts students are the true tech elites of the AI era.)
(Additional context: Jensen Huang: AI Tokens should be included in engineers’ salary structures, and they’ve become a new condition for hiring in Silicon Valley.)

If you happen to have a student at home who is about to start university, you may recently be feeling anxious and asking, “What major should my child study so they won’t be replaced?” When asked this question this week, Nvidia CEO Jensen Huang responded very succinctly: “I think what you study isn’t important. Everything that mattered in the past will still matter in the future.”

He argues that instead of hiding in a subject that AI can’t touch, it’s better to learn how to use AI to deepen any field of study.

Telling stories—AI can’t do it for you.

In the interview, Huang pointed out several areas he believes will remain valuable in the AI era: journalism, narration, art, and design. At first glance, this list is exactly the opposite of the market mainstream logic of “study AI and you’ll be safe.”

His reasoning comes from the essence of a particular ability. Taking a news reporter as an example, he said that the best interviewers don’t just do their homework—they must also be able to “stay focused on the moment, listen carefully, and respond flexibly.”

When these three actions are put together, they actually describe a highly situational form of judgment: knowing when to follow up, when to stay silent, and when a single glance is more powerful than ten questions. AI can analyze transcripts and search background information, but it cannot sense the kind of pause that happens when a guest’s tone suddenly drops, nor can it tell whether that silence is evasion—or the brewing of a genuine heartfelt remark.

“The ability to tell stories will be just as important in the present and the future.” This is one of the few positions Huang directly asserts in this interview.

So he believes there’s no need to fret first about “which major to choose.” Instead, present your existing passions first—whether they’re literature, biology, music, or engineering—then go back and ask one thing: how far can AI push your learning speed down this path, how refined can your craft become, and how much can it elevate the meaning of life.

When the subject changes from “what I should avoid” to “what I can amplify,” the entire answer structure changes with it.

Does AI make people dumber? He directly dismisses this assumption.

Another anxiety about AI is that “people will regress because they rely too much on AI.” In this interview, Huang Huang took issue with this assumption.

His argument follows a historical analogy: every wave of major technological breakthroughs ultimately results in strengthening human ambition, rather than suppressing it. He didn’t use abstract theory—he brought this logic back to the PC era: it was those who refused to learn how to use personal computers who were ultimately replaced; those who learned to use PCs were then able to enter jobs that had previously been out of reach.

The same logic applies today: accountants who don’t know how to use Excel will lose to accountants who do; financial professionals who don’t use AI-assisted analysis will be overtaken by peers who know how to run models with AI and focus on interpreting the results. Different tools, same logic.

In the AI era, that analogy becomes his widely circulated saying: “You won’t lose your job because of AI—you’ll lose it because someone else knows how to use AI better than you.”

Huang Huang’s judgment is that after AI automates many aspects of task execution, it will push humans toward higher-level responsibilities—the parts that require judgment and creativity. This is an argument about a “change in the nature of work,” not an argument that “jobs disappear.”