TL;DR
- Saylor says ChatGPT helped Strategy design a new financial instrument that unlocked roughly $15 billion in capital during 2025 after convertible financing neared limits.
- STRK reportedly bridges debt and equity, despite early resistance from lawyers and investment bankers who had never encountered a comparable structure before.
- Saylor argues bitcoin provides digital capital while AI provides digital intelligence, predicting both technologies will reshape finance, automate knowledge work, and preserve scarce assets.
Michael Saylor says ChatGPT helped Strategy engineer a financial instrument that unlocked roughly $15 billion in capital during 2025, presenting the result as evidence that artificial intelligence can reshape corporate finance. Speaking on The Diary of a CEO podcast, Strategy’s executive chairman framed the achievement through a striking pairing: bitcoin as digital capital and AI as digital intelligence. The surprising claim is that software helped solve a financing problem seasoned professionals had never confronted, allowing the company to keep supporting its bitcoin acquisition strategy after conventional pathways approached their limits within its established financing playbook.
AI and bitcoin converge in Saylor’s strategy
Strategy had become one of the world’s largest issuers of convertible bonds to finance additional bitcoin purchases, but Saylor said that route eventually reached a ceiling. The company then asked ChatGPT to explore structures that did not fit established templates. That process reportedly contributed to STRK, a preferred stock designed to sit between debt and equity, creating another channel for investor capital. Saylor said lawyers and investment bankers initially resisted because they had not encountered anything comparable, while the AI kept generating alternatives until a workable structure began to emerge for further bitcoin acquisition activity.
Saylor’s broader argument extends beyond one security. He described bitcoin as a transferable form of digital capital and AI as a force capable of expanding productivity. Rather than competing with automated systems, he urged entrepreneurs to use them for problems that previously appeared impossible. In his account, Strategy’s financing experiment demonstrates that approach in practice: the company did not ask AI to repeat an existing model, but to propose something new when standard financial expertise had exhausted familiar options. The implication is ambitious, even unsettling, for advisory professions.
The interview also returned to Saylor’s concern about preserving purchasing power. He contrasted cash with scarce assets such as stocks, commercial real estate, gold, and bitcoin, while arguing that property expenses can weaken residential returns. His central forecast is that AI and bitcoin will increasingly reinforce one another across finance, work, and entrepreneurship. He expects automation to transform accounting, legal research, and document preparation, leaving people to direct systems rather than repeat routine tasks. Yet he rejected the idea that abundance eliminates money, reasoning that scarce assets and capital will remain consequential over coming years.
