From skilled trades to startups, AI’s rapid expansion is the beginning of the next massive computing platform shift, and for the world’s workforce a move from tasks to purpose.
At a packed mainstage session at the annual meeting of the World Economic Forum in Davos, Switzerland, Huang described artificial intelligence as the foundation of what Huang called “the largest infrastructure buildout in human history,” driving job creation across the global economy.
Huang framed AI not as a single technology but as a “a five-layer cake,” spanning energy, chips and computing infrastructure, cloud data centers, AI models and, ultimately, the application layer.
Because every layer of AI’s five-layer stack must be built and operated, Huang said the platform shift is creating jobs across the economy — from energy and construction to advanced manufacturing, cloud operations and application development.
The application layer might focus on integrating AI into financial services, healthcare, or manufacturing. “This layer on top, ultimately, is where economic benefit will happen,” Huang said.
From energy and power generation to chip manufacturing, data center construction and cloud operations, Huang said the AI buildout is already creating demand for skilled labor. He added that the largest economic benefit will come from the application layer, where AI is transforming industries such as healthcare, manufacturing and financial services — and changing the nature of work across the economy.
Huang pointed to venture capital investment as a signal of how quickly AI is reshaping the global economy.
He said 2025 was one of the largest years for VC funding on record, with most of that capital flowing to what he described as “AI-native companies.”
These firms span healthcare, robotics, manufacturing and financial services — industries where, Huang said, “for the first time, the models are good enough to build on top of.”
That investment, Huang said, is translating directly into jobs.
He highlighted demand for plumbers, electricians, construction workers, steelworkers, network technicians and teams responsible for installing and operating advanced equipment.
Jobs with Purpose
AI, Huang said, likely won’t destroy jobs. Instead, it’s increasing demand in fields such as radiology, and helping handle administrative work in fields impacted by labor shortages – such as nursing.
AI has become a key tool in radiology, he said, yet there are now more radiologists than ever. “If you reason from first principles, not surprisingly, the number of radiologists has gone up,” Huang said.
He explained that the purpose of a radiologist’s job is to diagnose disease and help patients, while studying scans is just one task.
“The fact that they’re able to study scans now infinitely fast allows them to spend more time with patients,” he said, adding that AI enables greater interaction with patients and other clinicians. And because they can also see more patients, there is a need for more radiologists.
Huang said the same dynamic is playing out in nursing.
The U.S. faces a shortage of roughly five million nurses, in part because nurses spend nearly half their time on charting and documentation.
“Now they can use AI to do the charting and the transcription of patient visits,” he said, pointing to work being done by companies such as Abridge and its partners.
As productivity improves, Huang said, outcomes improve as well.
“Hospitals do better, and they hire more nurses,” he said. “Surprisingly — or not surprisingly — AI is increasing productivity, and as a result, hospitals want to hire more people.”
To illustrate the broader point, Huang joked that if someone simply watched him and Fink doing their jobs, “you would probably think the two of us are typists.”
Automating typing, he said, would not eliminate their jobs because that task is not their purpose. AI helps with tasks, enabling people to fulfill their purpose and become more productive, making workers more valuable.
“So the question is, what is the purpose of your job?” Huang said.
AI as Critical Infrastructure
Huang framed AI as essential national infrastructure. “AI is infrastructure,” he said, arguing that every country should treat AI like electricity or roads. “You should have AI as part of your infrastructure.”
He urged countries to build their own AI capabilities, drawing on local language and culture. “Develop your AI, continue to refine it, and have your national intelligence be part of your ecosystem,” he said.
Fink asked whether only the most educated people can use or benefit from AI. Huang countered that idea, emphasizing that AI’s rapid adoption stems from its accessibility.
“AI is super easy to use — it’s the easiest software to use in history,” he said, noting that in just two to three years, AI tools have reached nearly a billion people.
As a result, Huang said AI literacy is becoming essential. “It is very clear that it is essential to learn how to use AI — how to direct it, manage it, guardrail it, evaluate it,” he said, comparing those skills to leadership and people management.
Closing Technology Divides
For developing countries, Huang said AI offers a chance to narrow long-standing technology gaps. “AI is likely to close the technology divide,” he said, citing its accessibility and abundance.
Turning to Europe, Huang highlighted manufacturing and industrial strength as a major advantage. “You don’t write AI — you teach AI,” he said, urging countries to fuse industrial capability with artificial intelligence to unlock physical AI and robotics.
“Robotics is a once-in-a-generation opportunity,” he said, particularly for nations with strong industrial bases.
Fink summarized the discussion by saying that what he heard suggested the world is far from an AI bubble. Instead, he posed a different question: are we investing enough?
Huang agreed, saying large investments are required because “we have to build the infrastructure necessary for all of the layers of AI above it.”
The opportunity, he said, “is really quite extraordinary, and everybody ought to get involved.”
He reiterated that 2025 was the largest year for global VC investment, with more than $100 billion deployed worldwide, most of it into AI-native startups.
“These companies are building the application layer above,” Huang said, “and they’re going to need infrastructure — and investment — to build this future.”
Fink added that broad participation in that growth is critical.
“I actually believe it’s going to be a great investment for pension funds around the world to be a part of that, to grow with this AI world,” Fink said. “We need to make sure that the average pensioner and the average saver is part of that growth. If they’re just watching it from the sidelines, they’re going to feel left out.”
IMAGE CREDIT: World Economic Forum
