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Reading: Nvidia’s Jensen Huang thinks $1 trillion received’t be sufficient to fulfill AI demand—and he is paying engineers in AI tokens value half their wage to show it | Fortune
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Asolica > Blog > Business > Nvidia’s Jensen Huang thinks $1 trillion received’t be sufficient to fulfill AI demand—and he is paying engineers in AI tokens value half their wage to show it | Fortune
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Nvidia’s Jensen Huang thinks $1 trillion received’t be sufficient to fulfill AI demand—and he is paying engineers in AI tokens value half their wage to show it | Fortune

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Last updated: March 17, 2026 6:05 pm
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Nvidia’s Jensen Huang thinks  trillion received’t be sufficient to fulfill AI demand—and he is paying engineers in AI tokens value half their wage to show it | Fortune
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Only a few quick years in the past, AI was a novel idea producing uncanny, sloppy photographs and movies that appeared throughout your social media feeds. Right this moment, it’s seemingly ubiquitous. New fashions are popping up virtually each month. There’s AI integration in pockets of Hollywood. And even when it’s to date failing to spice up your productiveness on the workplace, AI has probably already appeared in your office. That sprawling growth requires monumental infrastructure funding. And Nvidia CEO Jensen Huang stated his firm is anticipating to ship these constructing blocks at a large scale.

Throughout his keynote handle Monday at Nvidia’s GTC convention in San Jose, Huang stated the corporate doubled its demand forecast inside the subsequent yr. “I see through 2027 at least $1 trillion,” he stated. “In fact, we are going to be short. I am certain computing demand will be much higher than that.”

And he’s already getting ready for that actuality with an uncommon incentive to draw high expertise and wring extra computing energy from his workforce: providing engineers AI tokens value practically half their wage.

The AI increase is pushing infrastructure investments to new heights. Tech corporations are investing a staggering $700 billion into the info middle buildout, a sum that rivals the GDP of developed economies like Sweden, and is greater than double the full inflation-adjusted value of the Apollo missions—initiatives that despatched people to the moon. Nvidia is a essential provider in that buildout, offering the processors that energy AI factories. The $1 trillion demand determine is additional proof that the buildout is all gasoline, no brakes, whilst rivals like Superior Micro Gadgets (AMD) wrestle to shut the hole. All of this comes regardless of looming fears of an AI bubble, as flagged by enterprise leaders like Microsoft CEO Satya Nadella and “Big Short” investor Michael Burry.

Huang made the prediction alongside claims that AI brokers might quickly run the world, in addition to bulletins round space-based computing designed to launch AI into orbit, an idea Elon Musk has spotlighted as a possible resolution to the power calls for of increasing information facilities.

“We are completely resetting and starting the largest buildout of human history,” Huang stated. “Most of the world’s industries building AI factories, building chip plants, building computer plants are represented here today.”

The corporate’s current earnings stories have added credibility to Huang’s claims. Final month, Nvidia posted $215.9 billion in income for fiscal 2026, up 65% from a yr in the past, the very best annual end result ever. Knowledge middle income alone rose 75% from a yr in the past, reaching $62.3 billion.

AI tokens: the way forward for pay?

As enterprise leaders goal to harness AI to spice up employee productiveness, Huang supplied a glimpse at how Nvidia plans to operationalize that ambition: paying engineers in tokens—the foreign money of AI—to amplify their output. 

“I could totally imagine in the future every single engineer in our company will need an annual token budget,” he stated. “They’re going to make a few 100,000 a year as their base pay. I’m going to give them probably half of that on top of it as tokens so that they could be amplified 10 times.”

Tokens are the fundamental models of information or phrases that AI fashions use to course of language and acknowledge patterns, making them essential to the way forward for AI deployment. AI firm OpenAI estimates that one token is the same as roughly 4 characters, with a single one-to-two sentence immediate requiring about 30 tokens. “Fortune Magazine,” for instance, could also be damaged down into 5 tokens: “For” “tune” “Mag” “az” “ine.” 

On the allowance ranges Huang described, engineers would have entry to billions of tokens yearly, unleashing a torrent of compute energy. In Huang’s state of affairs, tokens can be an added employment perk for engineers at his agency, arming them with the facility wanted to conduct deep analysis for the corporate.

The Nvidia CEO stated different tech companies will rapidly observe go well with and use tokens as a recruiting software to draw high trade expertise. 

“It is now one of the recruiting tools in Silicon Valley: how many tokens come along with my job,” he stated. “The reason for that is very clear because every engineer that has access to tokens will be more productive.”

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TAGGED:demandandengineersFortunehesHuangJensenmeetNvidiaspayingprovesalarythinkstokenstrillionwontworth
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