The computing revolution had disrupted a whole number of industries and sectors, and the AI revolution seems set to disrupt computing itself.
At the NVIDIA GTC March 2025 keynote, CEO Jensen Huang outlined his vision of the future of data centers. He predicted not only the imminent arrival of a trillion-dollar data center market but also a fundamental shift in their very nature, from information repositories to what he described as “AI factories”. His pronouncements, carrying the weight of NVIDIA’s prominent position in the AI hardware landscape, offered a glimpse into a rapidly approaching future shaped by generative AI.
“I’ve said before that I expect data center build out to reach a trillion dollars, and I am fairly certain we’re going to reach that very soon,” Huang began. “Two dynamics are happening at the same time. The first dynamic is that the vast majority of that growth is likely to be accelerated. Meaning we’ve known for some time that general-purpose computing has run its course, and we need a new computing approach.”
He continued, explaining the shift in computing paradigms: “The world is going through a platform shift from hand-coded software running on general-purpose computers to machine learning software running on accelerators and GPUs. This way of doing computation is at this point, past this tipping point, and we are now seeing the inflection point happening – the inflection happening in the world’s data center build-outs.” He emphasized the key takeaway from this first dynamic: “So the first thing is a transition in the way we do computing.”
Huang then articulated the second dynamic: “Second is an increase in recognition that the future of software requires capital investment. Now, this is a very big idea. Whereas in the past we wrote the software and we ran it on computers, in the future, the computer is going to generate the tokens for the software.” This shift, he explained, fundamentally changes the role of the computer itself: “And so the computer has become a generator of tokens, not a retrieval of files. From retrieval-based computing to generative-based computing, from the old way of doing data centers to a new way of building these infrastructures, and I call them AI factories.”
Now Huang does have an incentive to play up the importance of datacenters — it’s his NVIDIA chips that have a near-monopoly in the space. But it’s a compelling argument. The growing dominance of AI workloads, demanding specialized hardware like GPUs and accelerators, is likely to further solidify NVIDIA’s strategic position. Second, the concept of software development is already going through a transformative change, with AI models becoming the primary software creators. This shift, as Huang argues, necessitates significant capital investment in AI infrastructure, and his “AI factory” metaphor underscores the scale and industrialization of AI, suggesting a future where AI becomes a core component of production across various sectors, similar to electricity or the internet. And if AI does end up becoming as fundamental as electricity or the internet, it could end up not only enriching the companies that enable it, but also changing the world in ways that could be hard to envision at the moment.