The increasing use of artificial intelligence in financial systems is driving a shift towards a model where machines perform transactions on a large scale, creating 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 complex, with the tipping point occurring when latency, scale, and complexity begin to impact a company's ability to compete. This will force firms to reevaluate how their systems are built.
While automation has long been a part of finance, Borden noted 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, pointed to the crypto sector as 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 expect a mix of systems to coexist, with Levin predicting that the majority of commerce will be settled on public infrastructure in the next decade, while Borden envisions a more integrated approach linking public blockchains, private networks, and existing rails.