OpenAI has released new data showing a significant surge in enterprise usage of its AI tools over the past year, with ChatGPT message volume growing eightfold since November 2024. Workers report saving up to an hour daily through these tools.
Nearly 36 percent of U.S. businesses use ChatGPT Enterprise, according to the Ramp AI Index, compared to 14.3 percent for Anthropic. Despite this enterprise growth, most of OpenAI’s revenue continues to come from consumer subscriptions. Google’s Gemini poses a threat to that consumer base, while Anthropic relies mainly on business-to-business sales, and open-weight model providers vie for enterprise customers.
OpenAI has committed $1.4 trillion to infrastructure over the next few years, making enterprise expansion critical to the company’s business model. During a briefing, OpenAI’s chief economist Ronnie Chatterji discussed the economic impacts, stating, “If you think about it from an economic growth perspective, consumers really matter. But when you look at historically transformative technologies like the steam engine, it’s when firms adopt and scale these technologies that you really see the biggest economic benefits.”
The data indicates a deeper integration of OpenAI’s tools into enterprise workflows, with organizations using OpenAI’s API consuming 320 times more “reasoning tokens” than a year ago. This suggests use for complex problem-solving but could also reflect heavy experimentation without long-term value. Reasoning tokens link to higher energy usage, potentially raising costs for companies.
Companies are deploying OpenAI’s tools in new ways, with the use of custom GPTs increasing 19 times this year. These custom GPTs now make up 20 percent of enterprise messages and allow companies to embed institutional knowledge into assistants or automate workflows. OpenAI cited digital bank BBVA as an example, which uses more than 4,000 custom GPTs regularly.
Brad Lightcap, OpenAI’s chief operating officer, addressed this during the briefing, saying, “It shows you how much people are really able to take this powerful technology and start to customize it to the things that are useful to them.” Users report saving 40 to 60 minutes per day with OpenAI’s enterprise products, although this figure does not account for time spent learning the systems, crafting prompts, or fixing AI outputs.
Enterprise workers are using AI to build new skills, with three-quarters of surveyed workers stating that AI lets them perform tasks, including technical ones, that they could not do before. OpenAI noted a 36 percent rise in coding-related messages from outside engineering, IT, and research teams. This spread of coding could create more security vulnerabilities and errors. Lightcap referenced OpenAI’s agentic security researcher Aardvark, which detects bugs, vulnerabilities, and exploits and is currently in private beta.
Even top ChatGPT Enterprise users do not fully engage advanced features like data analysis, reasoning, or search. Lightcap explained that full adoption requires a shift in mindset and tighter links to enterprise data and processes, a process that will take time. The report points to a divide in AI adoption across enterprises, with “frontier” workers using more tools more frequently and saving more time than “laggards.”
Lightcap described the differences, stating, “There are firms that still very much see these systems as a piece of software, something I can buy and give to my teams and that’s kind of the end of it. And then there are companies that are really starting to embrace it, almost more like an operating system. It’s basically a re-platforming of a lot of the company’s operations.” OpenAI’s leadership views this gap as a chance for slower adopters to advance, but the company faces pressure from its $1.4 trillion infrastructure commitments.
The enterprise data release emphasizes OpenAI’s focus on business users, with message volume growth reflecting broader adoption. Time savings reports come from participants in OpenAI’s studies, and the 36 percent U.S. business figure stems from the Ramp AI Index. Anthropic’s 14.3 percent provides context for market position. Consumer subscriptions remain the primary revenue source, with Google’s Gemini competing directly in that area and Anthropic’s B2B focus challenging OpenAI in sales to businesses. Open-weight models attract enterprises seeking alternatives.
