The Highly Uncertain Future of OpenAI’s Dominance

Ben Lorica

Dan Schwarz on OpenAI Revenue, Competition, AI Agents, Future Projections.

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Dan Schwarz (CEO & Co-Founder, Futuresearch) explains why his firm finds OpenAI’s $125 billion revenue projection highly implausible, citing fierce competition, pressure on ChatGPT/API revenue, and fleeting technical advantages. FutureSearch forecasts a wide $10B−$90B range for 2027, reflecting deep uncertainty fueled by factors like talent drain and the competitive race among foundation model providers. While AI agents present a potential path to scale, the current dynamics suggest advantages are temporary and dominance is far from guaranteed.

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Transcript

Below is a heavily edited excerpt, in Question & Answer format.

What is your headline takeaway from your analysis of OpenAI’s revenue projections?

Futuresearch was the first to reverse-engineer OpenAI’s revenue streams before they were publicly disclosed, and we’ve been tracking them for over a year. OpenAI’s projection of $125 billion by 2029 is plausible in theory but highly implausible in practice. This relates to a recent report called AI 2027 that describes a scenario where a frontier lab experiences a runaway AI takeoff based on certain revenue projections. When we calibrate OpenAI’s projections against our expert forecasts, we find that hitting these numbers would require unprecedented exponential growth that doesn’t align with observed data or competitive realities.

What is your alternative revenue projection for OpenAI, and why is the range so wide?

Our 90% confidence interval for OpenAI’s 2027 revenue spans roughly $10 billion to $90 billion. This is an extraordinarily wide range because OpenAI is perhaps the most uncertain business possible to forecast. On one hand, they could monopolize multiple industries through rapid exponential growth. On the other hand, they could stumble due to ongoing litigation, talent exodus, and competition from other labs that already have better models in some categories. I personally lean toward the more bearish end of our internal forecasts. The uncertainty grows substantially when extending forecasts beyond 2027, making the 2029 projection even more speculative.

How is OpenAI’s revenue currently split between different sources?

Contrary to early assumptions, API calls account for no more than 15 percent of OpenAI’s revenue as of mid-2024. The bulk comes from ChatGPT’s consumer tier and increasingly from ChatGPT Enterprise. When we published our first analysis, many people thought API was the dominant source, but we demonstrated that ChatGPT was driving most of their revenue, and this pattern continues today.

What data sources and methods underpin your forecasts?

A good forecast blends data extrapolation with judgmental forecasting, adjusting for factors not captured in historical data. We start by extrapolating OpenAI’s initial revenue ramp (from $1B to $3.5B annually), but this provides only a crude baseline given the limited data points.

More importantly, we track competition closely by evaluating how good OpenAI’s models are compared to alternatives (Claude, Gemini, Llama, DeepSeek, etc.). This is challenging because benchmarks change constantly and don’t necessarily reflect actual user experience or specific use cases.

We also use judgmental forecasting techniques similar to prediction markets or Tetlock’s work for questions with limited direct data, such as lawsuit outcomes. This approach naturally yields wide intervals rather than spurious precision.

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