CEO Jensen Huang has argued that AI remains early in a multitrillion-dollar buildout, countering investor concerns that the sector may be overheating.
U.S. stocks edged higher late Wednesday as investors weighed another blockbuster earnings report from Nvidia against lingering concerns over the scale and sustainability of global AI investment.
Nvidia reported fourth-quarter revenue of $68.1 billion, up 73% from a year earlier, driven almost entirely by continued demand for data-center infrastructure.
Sales in that segment rose 75% to $62.3 billion, reinforcing the company’s central role in the artificial-intelligence buildout that has underpinned equity markets over the past year.
Net income nearly doubled to $43.0 billion, while gross margins held at about 75%, reflecting strong pricing power.
The results helped lift semiconductor shares and supported a modest rebound in broader equity benchmarks after a volatile start to the week.
The Nasdaq outperformed, advancing 1.26% while the S&P 500 closed higher at 0.8% as gains in megacap technology stocks offset weakness in more cyclical sectors. Shares for Nvidia in after-hours trading rose 1.37% to $198.31.
Crypto also saw major valuation gains in blue-chip assets, including Bitcoin and Ethereum, which jumped 7% and 12.5%, respectively, ahead of the earnings release.
Treasury yields fell across most maturities, signalling continued caution in rates markets even as equities stabilized.
Nvidia’s guidance, meanwhile, added to the sense that AI spending remains resilient.
The company forecast first-quarter fiscal 2027 revenue of about $78 billion, implying further sequential growth, despite excluding any contribution from China data-centre sales.
Management said customers continue to invest aggressively to scale inference and deploy so-called agentic AI systems.
The earnings echoed comments made last month by Nvidia Chief Executive Jensen Huang at the World Economic Forum in Davos, where he argued that AI is still in the early stages of what he described as the “largest infrastructure buildout in human history.”
Huang said trillions of dollars in additional investment would be needed across energy, chips, and data centres to support the technology’s long-term potential, pushing back against fears that the sector is already in a bubble.
Goldman Sachs has forecast that AI capital expenditure growth will peak in 2026 and then decelerate, which investors see as a mixed signal: growth will remain, but cash-flow visibility could improve only as spending slows.
Cathie Wood’s Ark Invest, by contrast, has argued that AI infrastructure spending is still in its early stages, framing the current surge in capital outlays by hyperscalers as the start of a multi-year investment cycle rather than a peak.
