Announcing NVIDIA DLSS 5, an AI-powered breakthrough in visual fidelity for games, coming this fall.
DLSS 5 infuses pixels with photorealistic lighting and materials, bridging the gap between rendering and reality.
Learn More → https://t.co/yHON3nGyxE pic.twitter.com/UvF9G7tlZs— NVIDIA GeForce (@NVIDIAGeForce) March 16, 2026
NVIDIA GTC 2026: Jensen Huang Outlines Ambitious Future for Enterprise IT Fueled by Demand for AI Inference
The seemingly insatiable demand for compute that is currently being driven by generative and agentic AI has emboldened NVIDIA to position itself at the center of the AI age.
NVIDIA is a company that made massive inroads in the technology industry — initially, with the gaming community — thanks to the impressive power of its graphics processing units. And although its role in fueling the rise of artificial intelligence has now taken over the corporate narrative, the company made sure to acknowledge its gaming roots by showing off the power of its DLSS 5 3D-guided neural rendering, which adds further dimension to realism for gamers, during the NVIDIA GTC keynote address on Monday.
“AI will revolutionize how computer graphics is done altogether,” said NVIDIA CEO Jensen Huang proudly during his presentation.
And while it’s reassuring that NVIDIA has not forgotten its gaming roots, the company’s ambitions far exceed gaming or media.
“We are now a computing platform that runs all of AI,” said Huang. “We are a vertically integrated computing company.”
But this vision of being a grand cog in the wheel of AI does not mean Huang wants to lose the specialization or intimate knowledge of specific industries. He believes that “domain-specific” understanding is in fact key to delivering AI agents and experiences that generate real value.
“We need domain-specific libraries in each one of the verticals that we address,” said Huang.
He rattled off examples of AI use in in medicine, media, retail, manufacturing, financial services and even space exploration.
NVIDIA’s pioneer spirit was best exemplified when Huang talked about the company’s next frontier, which is to build a data center in space using its Vera Rubin Space-1 Module, a space-hardened version of its Vera Rubin superchip platform. While the conversation around how to cool AI-hungry data centers here on Earth already generates plenty of heartburn, it’s not stopping NVIDIA from taking a stab at the even more difficult problem of cooling IT systems in space.
“In space, there’s no conduction, no convection, there’s just radiation. We have to figure out how to cool these systems out in space,” said Huang.
The Fundamental Shifts AI Has Brought to Enterprise IT
While Huang was laser-focused on the agentic AI future that lies ahead, he also proved to be quite the historian as he reflected several times throughout the keynote on the investments and journeys that have led to this spotlight moment for AI. He started with the company’s prescient decision back in 2006 to invest in its Compute Unified Device Architecture, or CUDA.
“It all began here. This is the 20th anniversary of CUDA. We've been working on CUDA for 20 years. For 20 years, we've been dedicated to this architecture,” said Huang.
It was CUDA that allowed NVIDA’s GPUs to be used for AI and not just for gaming, essentially allowing NVIDIA to become the nucleus of the AI era.
Huang linked the arrival of OpenAI’s ChatGPT at the end of 2022 as a seminal moment in computing history.
“Generative AI is a capability of software, but it has profoundly changed how computing is done. Computing used to be retrieval-based, now it's generative,” said Huang.
“Everything that we do is going to change how computers are architected, how computers are provided, how computers are going to be built out, and what is the meaning of computing altogether,” he said.
Similarly, he believes Anthropic’s Claude Code, which rose to prominence last year, is another revolutionary accomplishment of the AI age.
“An AI that could generate became an AI that could reason, an AI that could reason became an AI that could actually do work,” said Huang.
The steps that NVIDIA took over its history have led up to this moment: the unveiling of its Vera Rubin platform, which promises to open “the next frontier of agentic AI” and is poised for release in Q3 this year.
“The platform brings together the NVIDIA Vera CPU, NVIDIA Rubin GPU, NVIDIA NVLink 6 Switch, NVIDIA ConnectX-9 SuperNIC, NVIDIA BlueField-4 DPU and NVIDIA Spectrum-6 Ethernet switch, as well as the newly integrated NVIDIA Groq 3 LPU,” according to a company press release.
“We created a brand-new CPU that’s designed for incredibly high single-thread performance, data output, data processing and extreme energy efficiency,” said Huang. “What used to take two days to install now takes two hours.”
AI Factories Represent a Renaissance for Enterprise IT
For years, structured corporate data stored in files has been the bedrock of enterprise IT. But with agentic AI, all of that goes out the window as data centers must now evolve into AI factories, according to Huang.
“Your data center used to be a data center for files. It’s now a factory for tokens,” he said.
“It used to be OK that we would accelerate so that we could do it more cheaply, do it more frequently per day. However, in the future, these data structures are going to be used by AI,” said Huang.
While the keynote is known for its emphasis on hardware, one of the most bullish aspects of Huang’s presentation was the announcement of NemoClaw, NVIDIA’s enterprise wrapper on the OpenClaw personal assistant. Built in collaboration with OpenClaw creator Peter Steinberger, who Huang shouted out during the presentation, OpenClaw makes creating AI agents accessible and scalable, and Huang believes that NemoClaw, which makes OpenClaw enterprise-ready, will be the dawn of a new age for the computing industry.
“This is a renaissance of enterprise IT,” said Huang. “This is as big of a deal as HTML. This is as big of a deal as Linux.”
Keep this page bookmarked for articles from the NVIDIA GTC 2026.
Ricky Ribeiro
