The increasing use of artificial intelligence in financial systems is driving a shift towards machine-based transaction execution, posing new challenges for 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 escalating pressure as transaction demands become more complex, with the tipping point occurring when latency, scale, and complexity begin to impact competitiveness.
This forces firms to reassess their system architecture. The focus is now shifting from automation capabilities to trust, with the question being whether technology can be trusted, audited, and controlled. 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 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. Both executives expect a mix of systems to coexist 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.