Artificial intelligence offers a potential solution to the pervasive issue of regulatory "sludge" – excessive and time-consuming bureaucratic hurdles that burden businesses and consumers alike. While public skepticism towards AI persists due to concerns over job losses and corporate power, its ability to streamline complex rule sets presents a tangible benefit. Institutions like the Met Office and the Natural History Museum are already demonstrating AI's power in areas like flood forecasting and artifact identification.

In finance, AI could significantly reduce the time and resources spent on compliance. Former regulator Michael Hsu highlighted AI's potential to cut through regulatory red tape, benefiting both financial institutions and consumers. The Asian Development Bank notes AI's role as a "force multiplier" in this context. The challenge of managing vast, often overlapping, and outdated regulations has historically been immense, with efforts like the Reserve Bank of India's consolidation of thousands of circulars proving highly labor-intensive.

AI's capacity to analyze massive volumes of text, identify inconsistencies, and synthesize information makes it uniquely suited to tackle this problem. A pilot program in San Francisco, using AI to review municipal rules, resulted in a 36% reduction in mandated reports. Regulators are now exploring similar applications in finance, with tools like Harvey and Kimi showing promise in handling complex legal texts. While challenges remain, including the adaptation of AI to legalese and the need for human oversight, the potential for AI to drive market efficiency by reducing friction is substantial.