The increasing use of artificial intelligence in financial systems is driving the industry toward a model where machines handle transactions on a massive scale, posing new challenges related to control, oversight, and infrastructure, according to executives from Microsoft and Chainalysis. Bill Borden, Microsoft's corporate vice president of worldwide financial services, stated that legacy systems will face mounting pressure as transaction demands become more intricate, ultimately forcing companies to reassess their system architecture. The breaking point occurs when latency, scale, and complexity begin to hinder a company's ability to compete.
While automation has long been a part of finance, Borden emphasized that the focus is now shifting from capability to trust, with the primary concern being whether technology can be trusted, audited, and controlled. Microsoft is developing tools to facilitate this transition, including systems that assign identities and permissions to AI agents and track their actions. Jonathan Levin, co-founder and CEO of Chainalysis, noted that the crypto sector has already demonstrated a working model of automated finance, with blockchain networks processing large volumes of transactions through smart contracts and software-driven wallets.
Looking ahead, both executives anticipate a mix of systems coexisting, with Levin predicting that the majority of commerce will be settled on public infrastructure within the next decade, while Borden envisioning a more integrated approach that links public blockchains, private networks, and existing systems.