Jensen Huang has projected that the artificial intelligence (AI) computing market could generate up to $1 trillion in revenue by 2027, reflecting the rapid expansion of AI infrastructure worldwide.
Speaking at the company’s annual developer conference, Nvidia GTC in San Jose, Huang said the demand for AI chips and data-center systems is rising much faster than previously expected. The estimate is significantly higher than earlier projections and even exceeds the most optimistic forecasts from analysts.
Just last year, Nvidia had suggested that the market opportunity for AI data-center hardware could reach about $500 billion. However, Huang said accelerating investments by major technology companies and cloud providers have pushed the potential market size much higher.
Large technology firms are rapidly building AI infrastructure to train and deploy increasingly powerful AI models. This has led to strong demand for Nvidia’s advanced processors and integrated computing systems used in data centers around the world.
During his keynote address, Huang also introduced new AI platforms designed to support the next generation of computing workloads. These include systems based on Nvidia’s Blackwell architecture and future platforms such as Vera Rubin, aimed at powering large-scale AI data centers.
According to Huang, the AI industry is now entering a new phase focused on AI inference, the stage where trained models are deployed to perform real-time tasks. This includes applications such as digital assistants, automated software systems, robotics, and autonomous machines.
The shift toward inference computing is expected to significantly increase the demand for AI hardware and specialized data-center infrastructure. Nvidia believes this trend will drive the next wave of growth for the semiconductor industry.
