As the financial authorities increase their use of artificial intelligence (AI), micro regulations, such as consumer protection and routine banking regulations, will benefit because of ample data, short time horizons, clear objectives, and repeated decisions, leaving plenty of data for AI to train on. It is different from macro, focused on the stability of the entire financial system, where AI can potentially undermine financial stability. Infrequent and mostly unique events frustrate AI learning and hence its use for macro regulations. Using distributed decision making, humans retain the advantage over AI for advising on and making decisions in times of extreme stress. Even if the authorities prefer a conservative approach to AI adoption, it will likely become widely used by stealth, taking over increasingly high level functions, driven by significant cost efficiencies, robustness and accuracy. We propose six criteria against which to judge the suitability of AI use by the private sector and financial regulation and crisis resolution.