Jensen Huang, chief executive officer of Nvidia, told Bloomberg that the company could sell up to twice as many AI-accelerator chips next year compared with this year, driven by rapid adoption of artificial intelligence across multiple industries. Huang made the comments on the sidelines of an event for King Charles III in Scotland.
Nvidia is the leading manufacturer of AI-accelerator chips, high-performance semiconductors that are central to training and running AI models. Huang’s optimistic outlook is based on demand that now comes not only from technology companies but also from a widening set of industries investing in AI infrastructure.
Safety and responsibility instead of a development moratorium
While several industry leaders have recently suggested slowing AI development because of potential risks, Huang argued that braking progress is not necessarily the right response. He said companies should take responsibility to ensure that the AI software and services they release are safe.
Financial signals and production limits
Nvidia’s business indicators so far support Huang’s expectations. Last month the company projected roughly 70 percent revenue growth for its next fiscal year, and stated that revenue could potentially double if sufficient chips were available to meet surging demand. The current AI boom is therefore constrained less by a lack of demand than by whether manufacturers can produce enough chips quickly enough.
Cloud providers, large technology firms and other companies are investing heavily in AI infrastructure, and Nvidia occupies a central supplier role in that market.
Market reaction and product developments
Investors have so far remained engaged with Nvidia’s story: the company’s shares in New York traded up as much as 2.8 percent on Thursday, partially recovering from a decline the previous week, and have risen roughly 17 percent year-to-date.
Separately, Nvidia is preparing a new PC platform called RTX Spark, which integrates a central processor, graphics unit and AI acceleration on a single platform. Its performance characteristics are expected to become clearer in October, a product that could challenge traditional PC configurations and affect competitors such as AMD and Intel.
In sum, Huang’s upbeat projection rests on rapidly expanding, cross-industry AI demand and on how effectively Nvidia can scale chip production to capture that demand; the company’s future revenue will depend heavily on chip supply as well as market uptake.
