The increasing use of artificial intelligence in financial systems is driving a shift towards a model where machines handle transactions on a large scale, creating new challenges related to control, oversight, and infrastructure, according to Microsoft and Chainalysis executives. Bill Borden, Microsoft's corporate vice president of worldwide financial services, 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 begin to impact a firm's ability to compete.
This forces companies to reevaluate how their systems are built. While automation has long been present in finance, the focus is now shifting from capability to trust, with the question being whether technology can be trusted to execute tasks such as hedging strategies, and whether its actions can be audited and controlled. To manage this transition, Microsoft is developing tools that assign identities and permissions to AI agents and track their actions, enabling firms to demonstrate what controlled a system and whether it followed policy when decisions are made without human input. Jonathan Levin, co-founder and CEO of Chainalysis, noted that the crypto sector already provides a working model of automated finance, with blockchain networks processing large volumes of transactions through smart contracts and software-driven wallets, creating an environment similar to agent-based systems.
Levin pointed to efforts to track illicit funds across thousands of wallets as an example of the kind of monitoring needed in a system where transactions occur at scale without human input. Looking ahead, both executives anticipate a mix of systems coexisting, with Levin predicting that the majority of commerce will be settled on public infrastructure in 10 years, while Borden envisions a more integrated approach linking public blockchains, private networks, and existing rails, with traditional rails continuing to exist and software acting as the connecting layer.