AI Hustle: OpenAI’s Profit Crisis Linked to Huge Microsoft Payments

Podcast: AI Hustle: Make Money from AI and ChatGPT, Midjourney, NVIDIA, Anthropic, OpenAI
Hosts: Jaeden Schafer, Jamie McCauley
Episode Date: November 18, 2025
Episode Focus: This episode dives deep into the recently leaked details about OpenAI’s massive payments to Microsoft, the impact of these costs on OpenAI’s profitability, previously undisclosed financial structures between the two tech giants, and the broader implications for the AI industry and its investors.

Episode Overview

The hosts explore:

The leaked financial arrangements between OpenAI and Microsoft
OpenAI’s surging costs, especially for compute (AI infrastructure)
Questions about OpenAI’s profitability and sustainability
The wider impact on AI industry valuations and the possibility of an "AI bubble"

Key Discussion Points & Insights

1. Leaked Microsoft Payments & Revenue Shares

[00:29–05:00]

Leaked documents reveal OpenAI paid Microsoft $493.8 million in revenue share in 2024.
In the first three quarters of 2025, OpenAI’s payments surged to $865.8 million—projected to surpass a billion for the full year.
Background: Microsoft’s total investment in OpenAI stands at $13 billion.
- The arrangement: OpenAI pays Microsoft 20% of its revenue in exchange for Azure compute, investment, and ongoing partnership.
There's a reciprocal arrangement where Microsoft shares revenue with OpenAI from Bing and Azure OpenAI Service (also around 20%).

"So at something like, you know, $865 million, you can assume it's going to be over a billion dollars that they're going to be paying Microsoft for this year alone."
— Host (Jaeden Schafer), [01:32]

2. Opaque Financial Reporting

[05:00–07:30]

Microsoft’s actual profit from these AI partnerships is unclear—payments reported are "net" of what Microsoft pays OpenAI for using its tech.
Microsoft doesn’t break out AI revenue in public financial reports, making it difficult to assess the business's true scale and profitability from the outside.
The hosts note complexity: revenue sharing happens in both directions—OpenAI to Microsoft for compute, Microsoft to OpenAI for embedding AI into Bing and Azure.

3. OpenAI’s Explosive Revenue Growth—and Massive Compute Costs

[07:30–12:00]

Estimated revenue: OpenAI hit at least $2.5 billion in 2024, likely $4.33 billion (first three quarters, 2025).
There are conflicting reports: some say $4 billion in 2024 revenue, some say $4.3 billion in the first half of 2025.
Sam Altman, OpenAI CEO, claims revenue is "well more" than $13 billion/year, with a $20 billion annualized run rate by end of 2025.

"He said that by the end of this year, they're going to end it above $20 billion in annualized revenue run rate. So what's interesting here, though, he's not saying how much money they're making. He's just giving a projection."
— Host (Jaeden Schafer), [09:55]

Altman predicts $100 billion annual run rate by 2026, which the hosts view skeptically.

4. Compute Spend: Training vs. Inference

[12:00–16:00]

OpenAI’s compute / inference costs are exploding: estimated $3.8 billion in inference spend last year, up to $8.65 billion just in the first three quarters of 2025.
Inference = running models to respond to users (as opposed to initial model "training").
Historically, OpenAI almost exclusively used Microsoft Azure for compute needs—now they are diversifying, with new deals including AWS (Amazon), CoreWeave, Oracle, Google Cloud.

5. Nature of AI Spend: Credits vs. Cash

[16:00–18:00]

Training spend: Mostly covered by Azure credits/grants from Microsoft (non-cash).
Inference (serving users): Requires real cash outlay; companies must pay Microsoft and other providers directly for cloud compute as user demand surges.

"Their training spend is tokens, but their inference, right, what they're using to service all of our requests when we're chatting with Chat GPT all day long, those are actually cash they got to pay."
— Host, [17:31]

6. Industry Implications: Profitability and ‘AI Bubble’ Concerns

[18:00–19:00]

The explosive spending raises concerns about profitability—if OpenAI isn’t profitable, this challenges the stratospheric valuations of many AI companies.
There's growing "AI bubble" chatter—significant investor cash based on future hopes, but ongoing losses could shake confidence.

"If OpenAI is really still running their models at a loss, that... is like a massive deal for the investment world who is spending tons of money on these AI models. The valuations are absolutely insane."
— Host, [18:38]

Both Microsoft and OpenAI declined to comment on the leaked financials.

Notable Quotes & Memorable Moments

On the scale of recurring payments:
"You can assume it's going to be over a billion dollars that they're going to be paying Microsoft for this year alone." [01:32]
On financial reporting fuzziness:
"Microsoft never breaks down how much money they're actually making from Bing and Azure OpenAI in their financial statement. So it's pretty hard to get a good estimate..." [04:45]
On Altman’s ambitions:
"By the end of this year, they're going to end it above $20 billion in annualized revenue run rate... [but] he's just giving a projection." [09:55]
On the sustainability question:
"If OpenAI is not running at a profit, that means a lot of other people are not [profitable] as well." [18:53]

Timestamps for Key Segments

[00:29] – Introduction to leaked Microsoft-OpenAI payments
[01:32] – Breakdown of revenue-sharing arrangements
[05:00] – Limitations of available financial data
[07:30] – OpenAI’s estimated and projected revenues
[09:55] – Sam Altman’s ambitious projections
[12:00] – Surging compute (inference) spend
[17:31] – Distinction between non-cash (training) and cash (inference) costs
[18:38] – Broader implications for the AI investment landscape

Overall Tone & Takeaways

The hosts present the episode with an intuitive, skeptical, and approachable tone—aiming to both inform and spark critical thinking about the true economics behind the AI boom. The discussion reflects both excitement at AI’s potential and warnings about unchecked hype, especially regarding unsustainable business models.

Bottom line: OpenAI’s swelling payments to Microsoft highlight an ongoing struggle with profitability in the AI sector, challenging the idea that exponential user growth and massive investments automatically produce sustainable, profitable companies—a reality check for AI entrepreneurs and investors alike.

AI Hustle: OpenAI’s Profit Crisis Linked to Huge Microsoft Payments

Episode Overview

The hosts explore:

The leaked financial arrangements between OpenAI and Microsoft
OpenAI’s surging costs, especially for compute (AI infrastructure)
Questions about OpenAI’s profitability and sustainability
The wider impact on AI industry valuations and the possibility of an "AI bubble"

Key Discussion Points & Insights

1. Leaked Microsoft Payments & Revenue Shares

[00:29–05:00]

Leaked documents reveal OpenAI paid Microsoft $493.8 million in revenue share in 2024.
In the first three quarters of 2025, OpenAI’s payments surged to $865.8 million—projected to surpass a billion for the full year.
Background: Microsoft’s total investment in OpenAI stands at $13 billion.
- The arrangement: OpenAI pays Microsoft 20% of its revenue in exchange for Azure compute, investment, and ongoing partnership.
There's a reciprocal arrangement where Microsoft shares revenue with OpenAI from Bing and Azure OpenAI Service (also around 20%).

"So at something like, you know, $865 million, you can assume it's going to be over a billion dollars that they're going to be paying Microsoft for this year alone."
— Host (Jaeden Schafer), [01:32]

2. Opaque Financial Reporting

[05:00–07:30]

Microsoft’s actual profit from these AI partnerships is unclear—payments reported are "net" of what Microsoft pays OpenAI for using its tech.
Microsoft doesn’t break out AI revenue in public financial reports, making it difficult to assess the business's true scale and profitability from the outside.
The hosts note complexity: revenue sharing happens in both directions—OpenAI to Microsoft for compute, Microsoft to OpenAI for embedding AI into Bing and Azure.

3. OpenAI’s Explosive Revenue Growth—and Massive Compute Costs

[07:30–12:00]

Estimated revenue: OpenAI hit at least $2.5 billion in 2024, likely $4.33 billion (first three quarters, 2025).
There are conflicting reports: some say $4 billion in 2024 revenue, some say $4.3 billion in the first half of 2025.
Sam Altman, OpenAI CEO, claims revenue is "well more" than $13 billion/year, with a $20 billion annualized run rate by end of 2025.

"He said that by the end of this year, they're going to end it above $20 billion in annualized revenue run rate. So what's interesting here, though, he's not saying how much money they're making. He's just giving a projection."
— Host (Jaeden Schafer), [09:55]

Altman predicts $100 billion annual run rate by 2026, which the hosts view skeptically.

4. Compute Spend: Training vs. Inference

[12:00–16:00]

OpenAI’s compute / inference costs are exploding: estimated $3.8 billion in inference spend last year, up to $8.65 billion just in the first three quarters of 2025.
Inference = running models to respond to users (as opposed to initial model "training").
Historically, OpenAI almost exclusively used Microsoft Azure for compute needs—now they are diversifying, with new deals including AWS (Amazon), CoreWeave, Oracle, Google Cloud.

5. Nature of AI Spend: Credits vs. Cash

[16:00–18:00]

Training spend: Mostly covered by Azure credits/grants from Microsoft (non-cash).
Inference (serving users): Requires real cash outlay; companies must pay Microsoft and other providers directly for cloud compute as user demand surges.

"Their training spend is tokens, but their inference, right, what they're using to service all of our requests when we're chatting with Chat GPT all day long, those are actually cash they got to pay."
— Host, [17:31]

6. Industry Implications: Profitability and ‘AI Bubble’ Concerns

[18:00–19:00]

The explosive spending raises concerns about profitability—if OpenAI isn’t profitable, this challenges the stratospheric valuations of many AI companies.
There's growing "AI bubble" chatter—significant investor cash based on future hopes, but ongoing losses could shake confidence.

"If OpenAI is really still running their models at a loss, that... is like a massive deal for the investment world who is spending tons of money on these AI models. The valuations are absolutely insane."
— Host, [18:38]

Both Microsoft and OpenAI declined to comment on the leaked financials.

Notable Quotes & Memorable Moments

On the scale of recurring payments:
"You can assume it's going to be over a billion dollars that they're going to be paying Microsoft for this year alone." [01:32]
On financial reporting fuzziness:
"Microsoft never breaks down how much money they're actually making from Bing and Azure OpenAI in their financial statement. So it's pretty hard to get a good estimate..." [04:45]
On Altman’s ambitions:
"By the end of this year, they're going to end it above $20 billion in annualized revenue run rate... [but] he's just giving a projection." [09:55]
On the sustainability question:
"If OpenAI is not running at a profit, that means a lot of other people are not [profitable] as well." [18:53]

Timestamps for Key Segments

[00:29] – Introduction to leaked Microsoft-OpenAI payments
[01:32] – Breakdown of revenue-sharing arrangements
[05:00] – Limitations of available financial data
[07:30] – OpenAI’s estimated and projected revenues
[09:55] – Sam Altman’s ambitious projections
[12:00] – Surging compute (inference) spend
[17:31] – Distinction between non-cash (training) and cash (inference) costs
[18:38] – Broader implications for the AI investment landscape

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OpenAI’s Profit Crisis Linked to Huge Microsoft Payments

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Summary

AI Hustle: OpenAI’s Profit Crisis Linked to Huge Microsoft Payments

Episode Overview

Key Discussion Points & Insights

1. Leaked Microsoft Payments & Revenue Shares

2. Opaque Financial Reporting

3. OpenAI’s Explosive Revenue Growth—and Massive Compute Costs

4. Compute Spend: Training vs. Inference

5. Nature of AI Spend: Credits vs. Cash

6. Industry Implications: Profitability and ‘AI Bubble’ Concerns

Notable Quotes & Memorable Moments

Timestamps for Key Segments

Overall Tone & Takeaways

Summary

AI Hustle: OpenAI’s Profit Crisis Linked to Huge Microsoft Payments

Episode Overview

Key Discussion Points & Insights

1. Leaked Microsoft Payments & Revenue Shares

2. Opaque Financial Reporting

3. OpenAI’s Explosive Revenue Growth—and Massive Compute Costs

4. Compute Spend: Training vs. Inference

5. Nature of AI Spend: Credits vs. Cash

6. Industry Implications: Profitability and ‘AI Bubble’ Concerns

Notable Quotes & Memorable Moments

Timestamps for Key Segments

Overall Tone & Takeaways