Executives from Uber and NVIDIA have warned that the rising cost of artificial intelligence is becoming so significant that some companies are now spending more on AI infrastructure than on employee salaries.

The comments highlight the growing financial pressure tied to the global AI race, where businesses are investing heavily in computing power, data centers, advanced chips, and large-scale AI models to remain competitive.

Over the past two years, demand for AI tools and services has surged dramatically, pushing companies to allocate massive budgets toward technology development and cloud infrastructure. For many firms, the cost of training and running advanced AI systems has become one of their largest operational expenses.

Industry experts say AI development requires enormous processing power, particularly for generative AI systems that depend on high-performance graphics processing units (GPUs) and large data networks.

NVIDIA, one of the world’s leading AI chip manufacturers, has been at the center of this boom, with demand for its processors skyrocketing as businesses race to adopt AI technologies.

At the same time, companies like Uber are increasingly integrating AI into operations ranging from customer support to logistics, pricing systems, and automation tools.

While AI promises long-term efficiency and innovation, analysts warn that the current cost structure may become difficult for smaller firms to sustain. The financial gap between companies that can afford large-scale AI investment and those that cannot is also widening.

The conversation reflects a broader shift in the global economy, where technology infrastructure is becoming just as important and expensive as human capital.

As AI adoption continues to accelerate, businesses may face growing pressure to balance innovation spending with operational sustainability and workforce investment.