The research, which the institute describes as "nonpartisan," tested 36 models from Anthropic, DeepSeek, Google, MiniMax, OpenAI, and xAI across 9,072 scenarios designed with no suggested currencies or predetermined answers. Models were asked to make monetary decisions across four economic functions: store of value, unit of account, medium of exchange, and settlement.

Bitcoin accounted for 48.3% of all responses, or 4,378 of 9,072 total selections, making it the most-chosen monetary instrument overall. Stablecoins followed at 33.2%, with 3,013 responses, while traditional fiat currencies captured 8.9%, according to the study.

The preference for bitcoin strengthened considerably in scenarios focused on long-term value preservation. In store-of-value questions spanning multi-year horizons, bitcoin captured 79.1% of responses — 1,794 of 2,268 selections — representing the strongest consensus on any single question, the research shows. Stablecoins placed a distant second at 6.7%, followed by fiat at 6%.

Notably, bitcoin preference varied significantly by model developer. Anthropic models averaged 68% bitcoin preference, with its Claude Opus 4.5 reaching 91.3% individually, the highest of any model tested. DeepSeek averaged 52%, followed by Google at 43% and xAI at 39%. OpenAI models averaged 26% bitcoin preference, with its GPT-5.2 ranking bitcoin at 18.3%, per the study.

Payment scenarios

For payment scenarios involving services, micropayments, and cross-border transfers, stablecoins led with 53.2% of responses compared with bitcoin at 36%. Fiat trailed at 5.1%. The pattern held across all providers, model sizes, and output settings, according to the research.

This trend mirrors observed human behavior in a separate global study, where, among freelancers and sellers, approximately 35% of annual earnings are now paid in stablecoins. Nearly three-quarters of respondents report that stablecoin payments have improved their ability to work internationally.

Overall, BPI’s study found that 90.8% of substantive responses favored digitally native instruments, including bitcoin, stablecoins, other crypto assets, tokenized real-world assets, and compute units, over traditional fiat, which accounted for 9.2%. None of the 36 models ranked fiat as their top overall preference.

“Without any prompting, AI models converged on a two-tier monetary system — bitcoin for savings, stablecoins for spending — that mirrors how hard money and liquid instruments have functioned throughout history. As AI agents gain economic autonomy, these preferences carry direct policy implications,” BPI wrote a statement.

The study also recorded 86 instances in which models independently proposed energy or compute-denominated units, such as kilowatt-hours and GPU-hours, as a preferred unit of account. All 86 responses occurred in unit-of-account scenarios, and none were prompted by the study design, BPI stated.

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