OpenAI could be on the brink of collapse with projected losses totaling $5 billion, according to analysis conducted by The Information that drew on previously undisclosed financial information.
This means the AI trailblazer could be on track to go bankrupt within the next 12 months, with details from the report putting OpenAI way out ahead in spending compared to counterparts in the generative AI space.
Its training and inference costs could reach as high as $7 billion this year, with an additional $1.5 billion in spending on staff (via X). This is in stark contrast with Anthropic, which has been projected to spend $2.7 billion.
OpenAI’s spending has been a recurring talking point over the last 18 months, with industry analysis underlining the steep costs associated with building and maintaining its flagship services such as ChatGPT.
Estimates put the cost of keeping ChatGPT up and running at nearly $700,000 ($694,444) a day in 2023.
By comparison, the firm’s revenue is just shy of $3.5 billion, creating potentially untenable margins for the company and prompting some industry analysts to question its entire business model.
OpenAI is reported to receive discounted access to Microsoft’s Azure cloud services as part of its relationship with the tech giant. Microsoft has also invested billions of dollars in the startup over the last two years yet despite this concerns are rising over the company's long-term viability.
OpenAI’s identity crisis is part of a brewing industry-wide problem
While OpenAI’s financial trouble centers around exorbitant operating costs, questions over its current predicament come amidst a period of wider concern in the AI industry.
Increasingly, industry stakeholders have begun questioning whether there are demonstrable returns on investment (ROI) and pointing toward a lack of clearly defined use-cases.
A recent study from software firm Ardoq found that ROI on adoption of technologies such as generative AI is often viewed as a “finger in the air” exercise among senior tech leaders.
This research pointed toward a prevailing sense of cynicism about the benefits of technologies such as generative AI, with only one-third of organizations achieving a tangible return on investment within the first 12 months.
Simon Bain, CEO of Omnilndex, told ITPro many tech leaders are beginning to acknowledge the reality of this, noting that AI’s “jack of all trades approach has failed”.
“While the flashy demos and impressive chat initially captured the headlines and free users, they have not provided many (if any) actual business solutions. As such, people have seen no reason to pay for it,” he added.
Getting value out of generative AI as an enterprise user is difficult and, with costs mounting up, many are starting to worry and opt for caution. As Dom Couldwell, Head of Field Engineering at DataStax, told ITPro it’s “hard work” getting to production.
“Until people … actually get to production and the business side actually sees the value, we're going to have this gap, and no one knows quite how long that gap's going to last,” Couldwell added.
Mark Rodseth, VP for technology, EMEA, at CI&T echoed Couldwell’s comments regarding ROI, noting that the technology “still needs to prove its worth”.
“Because AI is still in its early stages, proving ROI can be challenging – both to external and internal stakeholders,” he said. “But this doesn’t mean companies should stop embracing AI.
