AI Revenue Growth Begins to Match Massive Data Center Spending

Jun 26, 2026
A new report from Exponential View finds that global AI revenue reached $25 billion in the first quarter of 2026, surpassing depreciation costs of major data center investments for the second consecutive quarter. The research suggests that demand for AI services is now large enough to sustain the industry's heavy infrastructure spending.
AI Revenue Growth Begins to Match Massive Data Center Spending

Revenue from artificial intelligence is beginning to offset the vast spending on chips and data centers, according to Exponential View. The firm’s new report shows that global AI sales, excluding China, reached $25 billion in the first quarter of 2026. That figure exceeded the industry’s estimated $21 billion in depreciation costs for a second straight quarter, suggesting the sector is starting to cover its infrastructure expenses.

Generative AI revenue totaled $110 billion over the past twelve months and is now on a $175 billion annualized run rate. The report’s dataset tracks spending across more than 1,000 companies, using public filings, executive statements, and cloud provider disclosures. It excludes chip manufacturing and advertising uplift to avoid double-counting between layers of the AI supply chain.

The analysis found that depreciation charges still consume about two thirds of revenue, leaving limited margin for other costs such as power and labor. However, demand remains strong. Rental prices for older NVIDIA GPUs like the H100 have stayed near 80 percent of their launch level, indicating persistent utilization despite new hardware releases.

The report also notes a shift among developers toward open-weight and Chinese models such as DeepSeek. Data from OpenRouter shows that the share of tokens processed by US models from Google, Anthropic, and OpenAI fell from 72 percent in mid-2025 to 33 percent in June 2026. This trend reflects users adopting lower-cost models for simpler workloads.

Exponential View concludes that AI demand is now more validated by realized revenue than any previous technology wave. Yet the industry’s ability to sustain its current pace will depend on how efficiently it can convert falling token prices and rapid hardware cycles into continued revenue growth.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.