The integration of artificial intelligence in financial systems is driving a shift towards a model where machines perform transactions on a large scale, presenting new challenges related to control, oversight, and infrastructure, as noted by Microsoft and Chainalysis executives. Bill Borden, Microsoft's corporate vice president of worldwide financial services, stated that legacy systems will face mounting pressure as transaction demands become more complex, with the tipping point occurring when latency, scale, and complexity begin to impact a company's ability to compete.
This forces firms to reassess how their systems are built. While automation has long been a part of finance, Borden emphasized that the focus is now shifting from capability to trust, with the question being whether technology can be trusted and audited. Microsoft is developing tools to manage 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 already offers a working model of automated finance, with blockchain networks processing large volumes of transactions through smart contracts and software-driven wallets. Levin pointed to efforts to track illicit funds as an example of the kind of monitoring needed in a system where transactions occur at scale without direct human input.
Both executives anticipate a mix of systems coexisting in the future, with Levin predicting that the majority of commerce will be settled on public infrastructure and Borden envisioning a more integrated approach linking public blockchains, private networks, and existing rails.