Jensen Huang has a prediction that should reframe how you think about Nvidia’s next chapter. Speaking in a recent interview, the Nvidia founder and CEO made a statement that cuts straight to the core of what agentic AI actually means for business:
“We’re going to see agents in every single part of every single company, and it’s going to help us become a lot more productive.”
Huang described two types of AI agents: physical agents (robots) and digital agents. Digital agents handle tasks like chip design optimization, software writing, trip planning, and day organization. The distinction matters because digital agents are deployable today, at scale, across every industry.
Nvidia isn’t just selling the infrastructure for this shift. The company already uses software agents for coding across the organization, making their software engineers “incredibly productive.” That’s not a roadmap item. That’s a live proof point from one of the most technically demanding engineering environments on earth.
The Numbers Behind the Vision
Nvidia (NASDAQ:NVDA | NVDA Price Prediction) reported Q4 FY2026 revenue of $68.13 billion, up 73.2% year-over-year, with data center revenue hitting $62.31 billion, representing 91.5% of total quarterly revenue. For the full fiscal year, Nvidia generated $215.94 billion in revenue.
On the Q4 earnings call, Huang framed the moment precisely: “Enterprise adoption of agents is skyrocketing. Our customers are racing to invest in AI compute — the factories powering the AI industrial revolution and their future growth.”
The hardware built specifically for this moment is already shipping. Blackwell Ultra delivers up to 50x better performance and 35x lower cost for agentic AI workloads compared to Hopper. That kind of cost reduction is what moves agentic AI from pilot programs to company-wide deployment.
Guidance for Q1 FY2027 calls for approximately $78 billion in revenue, and Morningstar upgraded Nvidia’s fair value to $260 from $240 following GTC 2026, citing the anticipated impact of agentic AI and a $1 trillion revenue forecast.
The analyst community is largely aligned: 58 analysts rate Nvidia a buy or strong buy, with an average target price of $267.54, against a current price of $181.93.
The interviewer’s observation cuts to something real: the full economic weight of what Huang is describing hasn’t fully landed in earnings yet. Much of what Huang discussed goes beyond Nvidia’s current valuation, with the full impact potentially showing up in earnings within the next 18 months. If agents truly penetrate every function of every company, the compute demand required to run them at scale flows directly to the infrastructure Nvidia builds. The thesis is that simple, and the internal proof is already running.
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