OpenAI CFO Projects $11 Billion Revenue Potential

Image: OpenAI

OpenAI CFO Sarah Friar has indicated that the company could achieve $11 billion in revenue this year, highlighting significant growth in user numbers and enterprise clients.

OpenAI CFO Sarah Friar has stated that reaching $11 billion in revenue is "definitely in the realm of possibility" for the company this year. This statement was made during an interview with CNBC, where Friar discussed the company's financial outlook and growth trajectory.

OpenAI has seen a significant increase in its user base, with Chief Operating Officer Brad Lightcap reporting that the startup's weekly active users have reached 400 million, a 33% increase from December. Additionally, OpenAI's enterprise business now boasts 2 million paying users, doubling its numbers since September.

Despite these positive indicators, OpenAI is still facing financial challenges. The company is expected to incur substantial losses before becoming profitable by 2029, with projected revenues reaching $100 billion by that time.

We hope you enjoyed this article.

Consider subscribing to one of several newsletters we publish like Enterprise AI Brief.

Also, consider following us on social media:

Enterprise AI

AI Brief (X)

More from: Funding

Pimloc Secures €4.2 Million for AI Video Privacy Expansion

Jul 08

Mistral AI in Talks for $1 Billion Funding with MGX

Jul 08

Galbot Secures $151 Million to Expand AI Humanoid Robots

Jul 08

15below Acquires Airport AI to Enhance Air Travel Communication

Jul 08

Evogene Completes Sale of Lavie Bio to ICL

Jul 08

Subscribe to Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Market report

AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation

ModelOp

The 2025 AI Governance Benchmark Report by ModelOp provides insights from 100 senior AI and data leaders across various industries, highlighting the challenges enterprises face in scaling AI initiatives. The report emphasizes the importance of AI governance and automation in overcoming fragmented systems and inconsistent practices, showcasing how early adoption correlates with faster deployment and stronger ROI.