Jensen Huang proposes AI tokens worth half of salary as new compensation model for engineers

Nvidia's Huang pitches AI tokens on top of salary as agents reshape how humans work

Nvidia CEO Jensen Huang delivers the keynote address at the GTC AI Conference in San Jose, California, on March 18, 2025. The perks of working in Silicon Valley have long included high salaries. Now, some engineers may be offered a new incentive: artificial intelligence tokens. Nvidia CEO Jensen Huang on Monday floated a novel compensation model that would give engineers a token budget on top of their base salary, effectively paying them to deploy AI agents as productivity multipliers. Tokens, or units of data used by AI systems, can be spent to run tools and automate tasks and are becoming "one of the recruiting tools in Silicon Valley," Huang said. "[Engineers] are going to make a few hundred thousand dollars a year, their base pay," Huang said at the chipmaker's annual GPU Technology Conference. "I'm going to give them probably half of that on top of [their base pay] as tokens ... because every engineer that has access to tokens will be more productive." The pitch signaled Huang's broader vision of the workplace, in which engineers oversee a fleet of AI agents capable of completing complex, multi-step tasks autonomously with minimal user input. It is a vision that Huang has been building toward publicly. Last month, he told CNBC that Nvidia's employees would one day work alongside hundreds of thousands of AI agents. "I have 42,000 biological employees, and I'm going to have hundreds of thousands of digital employees," he said.

Nvidia CEO Jensen Huang says engineers may get half salary in AI tokens, what they are

Nvidia's Jensen Huang proposes annual token budgets for engineers. This new compensation model could become a key recruitment tool in Silicon Valley. Tokens, units of text for AI, are becoming a measure of productivity. Rising token costs are driving this shift. AI compute is emerging as a fourth compensation pillar. Jensen Huang, chief executive of Nvidia, has outlined a new approach to hiring engineers, suggesting companies may soon offer annual "token budgets" as part of compensation, where tokens are small units of text processed by AI systems and used to measure computing usage. Speaking during his keynote at the GPU Technology Conference, the 63-year-old said he could see a future where "every single engineer will need an annual token budget," adding that he is open to providing it as part of pay packages. Huang said engineers earning a few hundred thousand dollars annually could receive additional compensation in the form of tokens. "They're going to make a few hundred thousand dollars a year, 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 10X. Of course, we would," he said. Also Read: Nvidia bets on AI inference as chip revenue opportunity hits $1 trillion He added that token allocation is already emerging as a hiring differentiator. "It is now one of the recruiting tools in Silicon Valley: How many tokens comes along with my job? And the reason for that is very clear, because every engineer that has access to tokens will be more productive." Tokens are small units of text processed by AI systems, typically representing parts of words, and are used to measure computing usage. Since longer text requires more tokens, pricing is often tied to cost per thousand or million tokens. When users input prompts into AI tools such as ChatGPT or Claude, the system breaks text into tokens. For example, the word "unbelievable" may be split into "un," "believe," and "able." Generating around 750 words typically requires about 1,000 tokens, while more complex tasks like coding or running AI agents consume significantly more. Also Read: Nvidia gets Beijing's nod for H200 chip sales, adapts Groq chip for China AI companies charge based on token consumption. OpenAI, for instance, prices its most advanced model at $15 per million tokens. These costs can escalate quickly. One engineer at Vercel reportedly incurred a $10,000 bill in a single day while deploying AI agents to build a service. As AI adoption grows, companies are increasingly tracking token usage per employee. Firms such as Zapier and Kumo AI are monitoring consumption to identify inefficiencies and high-performing engineers. A previous report by Business Insider noted that Silicon Valley firms are exploring ways to compete for talent beyond salary, bonuses, and equity by incorporating AI inference power into compensation. Investors are beginning to view tokens as a "fourth component" in recruitment, with some suggesting companies should clearly specify token budgets in job listings. Thibault Sottiaux, engineering lead for Codex at OpenAI, said AI compute is becoming increasingly scarce and valuable. He noted that candidates are now asking about dedicated inference compute during interviews. Huang also highlighted expectations that purchase orders between Blackwell and Vera Rubin could reach $1 trillion by 2027, driven by their ability to generate tokens at scale. With AI workloads expanding rapidly, tokens are increasingly being seen as a new currency of productivity, and their inclusion in compensation packages could soon become standard across the industry. (With inputs from TOI) (You can now subscribe to our Economic Times WhatsApp channel)

Nvidia CEO Jensen Huang Predicts AI Tokens Will Become a Standard Job Perk | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. Huang said Monday (March 16) during his keynote address at the Nvidia GTC AI Conference & Expo that tokens are becoming a recruiting tool in Silicon Valley, according to the report. Tokens are units of data used by AI systems, the report said. "I could totally imagine in the future every single engineer in our company will need an annual token budget," Huang said during his keynote. "They're going to make a few hundred thousand dollars a year, 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 10x. Of course we would. It is now one of the recruiting tools in Silicon Valley -- 'How many tokens comes along with my job?'" Huang told CNBC in February that a growing number of AI agents will work alongside Nvidia employees. "I have 42,000 biological employees, and I'm going to have hundreds of thousands of digital employees," he said, per the report. Huang also told CNBC in February that AI agents will have a beneficial impact on the software industry. Rather than reducing demand for the industry's products, AI agents will become its customers as they use programs, tools and computing resources, he said. "The number of C-compilers that we use, the number of Python programs that we have, the number of instances, are growing very, very fast -- because the number of agents we have that use these tools are going up," Huang said, per the report. PYMNTS reported Thursday (March 19) that Huang said during his keynote address that companies will shift from software that enables employees to do work, to software that does the work itself, autonomously, through AI agents executing tasks without continuous human input. Nvidia said in reports released earlier this month that AI is delivering measurable financial gains for businesses. Eighty-eight percent of organizations say AI has increased their annual revenue, and 87% say it has reduced their costs. In terms of AI adoption, 64% of companies are actively using AI, while 28% are evaluating potential deployments.

Every engineer will have 100 AI agents: Jensen Huang on future of work

Engineers will evolve into orchestrators of hundreds of AI agents at work There are many ways to measure the productivity of an engineer that earns $500,000 or ₹2.3 crore per year. NVIDIA's Jensen Huang, in his inimitable style and theatrical bluntness, has proposed a new one - token burn. "That $500,000 engineer at the end of the year, I'm going to ask him, how much did you spend in tokens?" The NVIDIA CEO was quoted while speaking on the All-In Pod on the final day of GTC 2026. "If that $500,000 engineer did not consume at least $250,000 worth of tokens, I am going to be deeply alarmed," emphasised Jensen Huang. If you think about the implication of what Huang is suggesting, it effectively inverts decades of enterprise thinking. Efficiency, in the classical sense, is all but dead in the age of AI. Under-utilisation of resources - not excess - is the bigger sin, according to NVIDIA CEO Jensen Huang. Tokens are not a cost centre, they need to be looked at as capability. "This is no different than one of our chip designers who says I'm just going to use paper and pencil," Huang said, with a deliberate example. You see, just as CAD tools became non-negotiable for chip design, AI agents are becoming the baseline tools for doing increasingly more knowledge work. Huang's comments aren't hot gas, there's data to back him up. A 2025 study by KPMG estimated that GenAI could add $2.84 trillion in GDP to the US by 2030 and $11.04 trillion to global GDP by 2050, with software engineering among the highest-impact domains. Meanwhile, GitHub's Copilot research found developers completing tasks up to 55% faster, with a majority reporting reduced cognitive load. However, Huang isn't just hinting about faster code, but a fundamental rewrite of what work truly means in the age of AI agents. "Things that are too hard, take too long, need a lot of people, those ideas are all gone," Huang points out. AI collapses human effort barriers in the same way machinery once did for physical labour. Also read: 'Are you insane?' Huang hits out at claims some Nvidia managers want reduced AI use "Every engineer is going to have a hundred agents," Huang predicted. The lone genius coder is being replaced by something closer to a conductor of a software-driven orchestra, which changes the job description entirely. "In the past, we code. In the future, we're going to write ideas, architectures, specifications... define what good looks like." This is less about typing syntax and more about shaping intent. Less mechanical keyboard tapping, more emphasis on thinking and automating. All of what Huang said brings us to an uncomfortable implication. If your value as a knowledge worker was linked to output volume, AI is already eating your lunch. But if your value is defined by taste, judgement, and creativity, your stock just went up. Huang isn't asking you to spend more on tokens as much as he's asking you to spend on possibility.