AI

OpenAI revenue hits $10 billion in third quarter as operating losses widen

The ChatGPT creator saw enterprise sales double quarter-on-quarter while its operating loss expanded to $10.9 billion.

By KaroStartup News Engine

OpenAI recorded a 50 per cent quarter-on-quarter increase in revenue to $10 billion for the third quarter, boosted by rapid adoption of its enterprise platforms and sustained expansion in consumer subscriptions. Speaking to Deirdre Bosa on Tuesday, OpenAI Chief Financial Officer Sarah Friar described the three-month period as a "blockbuster quarter" and confirmed that the company's annualised revenue run rate has now scaled to approximately $50 billion. The performance marks a notable operational acceleration from the second quarter, when revenue grew by 18 per cent quarter-on-quarter, according to financial disclosures reported by the Wall Street Journal.

However, the revenue expansion coincided with wider operating losses as compute costs and infrastructure investments weighed on the balance sheet. According to financial documents reviewed by the Wall Street Journal, OpenAI recorded an operating loss of $10.9 billion for the third quarter, expanding from $10.1 billion in the second quarter. Despite the widening cash deficit, the company told investors that unit-level operational efficiency showed signs of recovery. OpenAI's adjusted operating margin narrowed to -109 per cent in the third quarter, compared to -150 per cent reported in the prior quarter. OpenAI did not respond to requests for official comment on the loss figures.

Why it matters

For technology founders, enterprise software operators, and venture investors, OpenAI's latest financial update offers a detailed look at the economics of frontier artificial intelligence at scale. Achieving an annualised run rate of $50 billion reflects unprecedented market demand for artificial intelligence tools across retail consumers and corporate workflows.

At the same time, a quarterly operating loss of $10.9 billion underscores the capital intensity required to maintain leadership in frontier model development. The figures highlight a central challenge for AI platforms: building revenue scale rapidly while managing massive infrastructure commitments. For the broader venture ecosystem, OpenAI's results demonstrate that while top-line demand for AI models is expanding rapidly, achieving operating profitability remains a longer-term transition.

Enterprise momentum and product performance

The composition of OpenAI's revenue base underwent a significant shift during the period, driven by aggressive corporate adoption. Friar revealed that OpenAI's revenue is now split evenly, with 50 per cent derived from enterprise clients and 50 per cent from consumer products.

The enterprise division led overall growth, doubling its revenue quarter-on-quarter. Friar attributed this surge to targeted enterprise offerings, including specialised coding and cybersecurity tools, as well as Dots, OpenAI's enterprise AI agent platform.

"Our enterprise business doubled quarter over quarter," Friar explained during the interview, noting that products such as "Coding, Cyber, starting to get more virtual assistants like Dots into the enterprise" served as primary adoption drivers.

Small- and medium-sized business accounts also experienced accelerated growth during the quarter. Friar noted that OpenAI's small- and medium-business segment registered higher revenue growth in the third quarter than it had generated across the previous six quarters combined.

Meanwhile, the consumer business maintained robust user metrics. Consumer revenue expanded by 20 per cent quarter-on-quarter, propelled by paid subscriptions crossing 100 million users. Across both free and paid ChatGPT tiers, total engagement reached 1.2 billion weekly active users.

Strategic shift in cloud distribution

OpenAI's operational strategy is also undergoing a major structural shift in response to enterprise distribution dynamics. Friar acknowledged that rival Anthropic's enterprise strategy provided a clear template for reaching corporate buyers through third-party cloud providers, prompting OpenAI to rethink its own distribution setup.

Historically, OpenAI relied on an exclusive cloud distribution arrangement with Microsoft Azure. Friar noted that this arrangement created distribution bottlenecks for enterprise penetration compared to competitors who integrated directly into multi-cloud environments.

"Part of it was we were really stuck on this [Microsoft] Azure contract that we had," Friar said. "I think getting that unlocked, Anthropic showed me just the power of that model, and I think for us that can be a very big tailwind in 2027."

Anthropic IPO and comparative financials

The financial disclosures arrive as competing AI developer Anthropic initiates the formal process for a public listing. Anthropic commenced its investor roadshow on Tuesday, positioning for an initial public offering that could take place on 19 November or 20 November. Reports indicate the share sale could value Anthropic at approximately $1.4 trillion, establishing a high-water mark for public valuations in the artificial intelligence sector.

Financial data indicates Anthropic generated $33.2 billion in revenue through the first nine months of the year ending 30 September, representing a 1,206 per cent increase compared to prior periods. This represents a steep trajectory from the $16.3 billion recorded in the first six months of the year ending 30 June, and the $4.6 billion generated across the entirety of 2025. Unlike OpenAI, Anthropic operates exclusively in the business-to-business enterprise segment and does not offer a direct-to-consumer platform.

What happens next

OpenAI plans to finalise new non-exclusive cloud distribution agreements to expand enterprise access across multiple cloud platforms, a move expected to deliver substantial financial impact by 2027. Concurrently, the tech industry and institutional investors will evaluate Anthropic's planned public market debut on 19 or 20 November, which will serve as a crucial test of public equity demand for pure-play enterprise AI platforms.