The increasing use of artificial intelligence in financial systems is driving a shift towards a model in which machines execute transactions on a large scale, presenting new challenges related to control, oversight, and infrastructure, according to Microsoft and Chainalysis executives. Microsoft's Corporate Vice President of Worldwide Financial Services, Bill Borden, stated that legacy systems will face growing pressure as transaction demands become more complex, with the tipping point being reached when latency, scale, and complexity start to impact a company's ability to compete.
This will force firms to reevaluate how their systems are built. Borden noted that while automation has long been a part of finance, the focus is now shifting from capability to trust, with the question being whether one can trust and audit automated systems.
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 out 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. 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 10 years, while Borden envisioning a more integrated approach that links public blockchains, private networks, and existing rails.