OpenAI is reportedly on the road to reaching $1 billion in yearly revenue.
The maker of the generative artificial intelligence (AI) bot ChatGPT is taking in roughly $80 million in revenue per month, Bloomberg News reported late Tuesday (Aug. 29), citing a source familiar with the matter.
ChatGPT’s debut last fall has ushered in a flurry of investment in the generative AI sector, with OpenAI — backed by Microsoft — among the standouts in the field. PYMNTS has contacted OpenAI for comment but has not yet received a reply.
Earlier this week, OpenAI released ChatGPT Enterprise, a corporate version of the tool which the Bloomberg report argues is the company’s largest effort thus far to draw a wide range of business clients and increase revenue from its flagship offering.
The company said Monday (Aug. 28) that since debuting ChatGPT, the tool has been adopted by more than 80% of the companies on the Fortune 500. This new version was created to give companies a way to deploy the technology safely and quickly, using it to improve communication, speed up coding tasks, deal with complex business questions and help with creative work.
Meanwhile, research by PYMNTS shows that many companies are uncertain of where they stand when it comes to generative AI, though they feel a pressing need to adopt it.
The PYMNTS/AI-ID collaboration “Understanding the Future of Generative AI” found that 62% of executives don’t think their companies have the expertise to use the technology effectively, with questions about regulating AI still unanswered.
“I don’t think that we can expect any one single institution to have the kind of knowledge and capacity to address the varied problems [of AI regulation],” Cary Coglianese, founding director of the Penn Program on Regulation, told PYMNTS. “If there was an equivalent of a seat belt that we could require be installed with every AI tool, great. But there isn’t a one-size-fits-all action that can be applied [to regulating AI].”
“[Overseeing AI] relies on technical standards that will have to be developed to implement it,” Dr. Johann Laux told PYMNTS in a separate interview earlier this week. “If you want to audit AI systems, we need an audit industry to emerge.”
And as noted here earlier this month, not all applications will need the most cutting-edge and costly large language models (LLMs) on the market.