It started with a whisper in the tech underground: a single Reddit thread, buried beneath memes and memes, that exploded into a global firestorm. “Leaked documents shed light into how much OpenAI pays Microsoft,” read the headline. But what followed wasn’t just numbers. It was a story of ambition, dependency, and the fragile economics of artificial intelligence.
The Moment the Bubble Popped
Imagine a quiet office in San Francisco, late at night. A junior engineer at OpenAI, exhausted from another 14-hour shift, scrolls through Reddit. She stumbles upon the post. Her eyes widen. The numbers—$493.8 million paid to Microsoft in 2024, $865.8 million in just nine months of 2025—match the internal spreadsheets she’s seen. This isn’t speculation. This is real. And it’s terrifying.
Across the industry, the same scene plays out. Investors, journalists, and even Microsoft employees stare at their screens, realizing: the AI gold rush might be built on sand.
The Hidden Cost of Intelligence
Here’s the truth most people don’t know: running AI isn’t free. Every time you ask ChatGPT a question, a massive computer somewhere—usually in a Microsoft data center—wakes up, crunches numbers, and sends back an answer. This is called inference, and it’s expensive. In 2024, OpenAI spent $3.8 billion on inference. In the first nine months of 2025, that jumped to $8.65 billion.
Where does that money go? Mostly to Microsoft. OpenAI pays 20% of its revenue to Microsoft as part of a deal that saw the tech giant invest over $13 billion. In 2024, that meant $493.8 million. In 2025, it’s already $865.8 million—and climbing.
The Domino Effect
This isn’t just about OpenAI. It’s about the entire AI industry. If the most powerful AI company in the world is spending more on running its models than it’s earning, what does that mean for the startups raising billions at sky-high valuations? What does it mean for the future of AI?
“OpenAI is the canary in the coal mine,” says Dr. Elena Torres, a tech economist at Stanford. “If they’re not profitable, the whole sector is at risk.”
The Human Cost
Meet Amina, a data annotator in Nairobi. She works for Sama, a company that helps OpenAI label and clean data. She earns $1.32 an hour after taxes. “We see things no one should see,” she says. “People’s secrets, their fears. Sometimes, I feel like I’m carrying the weight of the world.”
OpenAI pays Sama $12.50 an hour, but most of that goes to infrastructure, management, and quality control. The human cost of AI isn’t just in dollars—it’s in the mental scars of the people who make it possible.
The Microsoft Connection
Microsoft isn’t just a landlord. It’s a partner, a financier, and, increasingly, a gatekeeper. OpenAI relies almost entirely on Microsoft Azure for its computing power. But the relationship is complex. Microsoft also shares revenue with OpenAI from Bing and Azure OpenAI royalties, but those numbers are hidden.
“Microsoft doesn’t break out how much it makes from Bing and Azure OpenAI in its financial statements,” says a source at TechCrunch. “So it’s difficult to estimate how much the tech giant is kicking back.”
The Ripple Effect
Governments are starting to take notice. The U.S. Securities and Exchange Commission subpoenaed OpenAI’s internal communications in 2024, looking into whether CEO Sam Altman misled investors. The European Union is drafting new regulations to cap AI inference costs and ensure transparency.
Industries are reacting too. Cloud providers like AWS and Google Cloud are offering more competitive deals to AI startups. OpenAI itself is trying to reduce its dependency on Microsoft by 2026, but the transition won’t be easy.
What’s Next
The big question is: can OpenAI—and the AI industry—become profitable? Or is this just the beginning of a bubble that will burst?
“OpenAI’s financial struggles are a wake-up call,” says Dr. Torres. “We need to rethink how we build and fund AI. Otherwise, we risk a crash that could set the industry back years.”
Could It Happen Again?
The answer is yes. As long as AI models get bigger and more complex, the cost of running them will keep rising. The only way to avoid another bubble is to innovate—not just in technology, but in business models.
The Final Question
If the most powerful AI company in the world is spending more than it earns, what does that mean for the future of artificial intelligence? Is it a revolution—or a mirage?
FAQ
Q: What is inference in AI?
A: Inference is the process of running a trained AI model to generate responses, like answering a question or creating text.
Q: Why does OpenAI pay Microsoft so much?
A: OpenAI uses Microsoft Azure for its computing power and pays 20% of its revenue as part of a deal where Microsoft invested over $13 billion.
Q: Is OpenAI profitable?
A: Leaked documents suggest OpenAI may be spending more on inference than it earns, raising concerns about profitability.
Q: What are the human costs of AI?
A: Data annotators, often in developing countries, earn very little and are exposed to sensitive, sometimes traumatic, content.
Q: How are governments reacting?
A: Governments are investigating OpenAI’s finances and drafting regulations to cap AI inference costs and ensure transparency.
Q: What’s next for OpenAI and the AI industry?
A: OpenAI is trying to reduce its dependency on Microsoft, but the industry faces a potential bubble if costs keep rising.
Q: Could another AI bubble happen?
A: Yes, as long as AI models get bigger and more complex, the cost of running them will keep rising, risking another bubble.