Saylor: ChatGPT Helped Strategy Raise $15B for Bitcoin
Michael Saylor said he used ChatGPT to design preferred-stock structures that helped Strategy raise about $15 billion in securities for Bitcoin purchases, including $10.5 billion from STRC.
During a podcast appearance on Aug. 6, Michael Saylor described using ChatGPT to design preferred-stock structures that allowed Strategy to raise about $15 billion in securities to fund Bitcoin purchases. The company sold roughly $10.5 billion of a variable-rate preferred called STRC and about $4 billion of related preferred instruments.
According to Saylor, the effort began in early 2025 after common-stock sales and convertible bonds could not supply the scale of capital the company sought. Strategy had relied heavily on equity issuance and convertible debt to finance its Bitcoin accumulation and needed another credit source.
The first structure the company developed was STRK, a convertible preferred. Strategy later created STRC, a variable-rate preferred intended to act like short-duration credit and trade near its $100 stated value. STRC’s dividend rate can be adjusted as market conditions change; that mechanism was designed to help keep the preferred’s market price relatively stable.
Saylor described using generative AI to test whether the designs could fit within existing securities rules and market practice. He recounted asking the AI whether the structures were feasible and receiving an affirmative response. When the program host asked whether he meant ChatGPT and OpenAI, he confirmed those were the tools referenced.
Strategy raised about $2.5 billion in STRC in the initial offering and later issued roughly $8 billion more, taking STRC proceeds to about $10.5 billion. Combined with roughly $4 billion from other preferred securities, the total capital raised through those instruments was about $15 billion.
The preferred-stock offerings created an additional financing channel alongside common equity and convertible debt. Strategy holds more than 840,000 Bitcoin on its balance sheet.
“I used AI to make $15 billion last year,” he told listeners, repeating that the $15 billion referred to capital raised through securities rather than personal income or company profit.








