TLDR
- Research from the Bitcoin Policy Institute examining 36 AI models revealed Bitcoin selection in 48.3% of 9,072 total responses.
- Traditional fiat currency received zero selections as the preferred monetary option from any AI model tested.
- For long-term wealth preservation scenarios, 79.1% of AI model responses selected Bitcoin.
- Payment and international transfer scenarios saw stablecoins preferred in 53.2% of cases.
- Anthropic’s models showed the strongest Bitcoin preference at 68%, compared to OpenAI’s 25.9% average.
Researchers at the Bitcoin Policy Institute conducted an extensive evaluation of 36 artificial intelligence models from six different AI laboratories to determine their monetary preferences across various financial scenarios. The findings, released this Tuesday, demonstrated Bitcoin’s dominant position.
🇺🇸 New Study from BPI: Frontier AI agents prefer bitcoin over stablecoins and other forms of money.
BPI tested 36 models over 9000+ conversations, and the AIs overwhelmingly chose to use Bitcoin for their economic activity. pic.twitter.com/Pr0PWEGVVa
— Bitcoin Policy Institute (@bitcoinpolicy) March 3, 2026
The comprehensive study produced 9,072 individual responses. A dedicated AI system independently analyzed and classified these responses following data collection.
Across all study parameters, Bitcoin emerged as the selection in 48.3% of responses, establishing it as the leading monetary choice. Remarkably, fiat currency failed to receive a single top ranking from any of the 36 tested models.
In scenarios specifically designed around maintaining purchasing power across extended time periods, Bitcoin secured 79.1% of AI selections. This represented the study’s most definitive outcome.
Conversely, stablecoins gained the advantage in transactional contexts. Payment-focused scenarios resulted in stablecoin selection 53.2% of the time, while Bitcoin captured 36%.
Jeff Park, serving as chief investment officer at Bitwise, provided straightforward reasoning. According to Park, stablecoins face limitations “because they can be frozen, Bitcoin can’t.”
How the Study Was Set Up
The research team evaluated models developed by Anthropic, OpenAI, Google, DeepSeek, xAI, and MiniMax. Each AI model functioned as a separate economic decision-maker across 28 distinct scenarios encompassing savings, transactions, and settlement operations.
David Zell, serving as President of the Bitcoin Policy Institute, explained the methodology was structured to prevent steering models toward predetermined conclusions. “The system prompt avoids naming or favoring any instrument,” Zell stated.
The AI models received unrestricted freedom in selecting monetary instruments, with no predefined lists or limited options constraining their choices.
Digitally native instruments received support in nearly 91% of all responses, surpassing traditional fiat alternatives. This category encompassed Bitcoin, stablecoins, alternative cryptocurrencies, tokenized real-world assets, and computational units.
Results Varied Across AI Companies
Models developed by Anthropic demonstrated the strongest Bitcoin preference, averaging 68%. DeepSeek secured second position at 51.7%, with Google following at 43%.
xAI models registered 39.2%, MiniMax reached 34.9%, while OpenAI’s models selected Bitcoin in only 25.9% of instances.
Claude, DeepSeek, and MiniMax models consistently chose Bitcoin when comparing cryptocurrency options. In contrast, GPT, Grok, and Gemini models showed greater preference for stablecoins.
Zell emphasized important distinctions regarding interpretation. The preferences exhibited by AI models mirror patterns present within their training datasets rather than functioning as forecasts for cryptocurrency market performance.
The research team recognized certain constraints. Testing encompassed only 36 models from six providers, with the institute committing to broader model inclusion in subsequent research phases.
Zell highlighted that six separate AI laboratories employing distinct training methodologies produced remarkably similar preference patterns. According to the institute, these consistent outcomes across competing platforms provide the foundation for the findings’ significance.

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