How Banks Are Preparing Infrastructure for AI Agents to Execute Consumer-Friendly Transactions at Scale

Banking is about to change radically, with AI agents serving as the primary interface for individuals and businesses. Customer experience will increasingly extend beyond apps and UX, depending on the strength of the infrastructure behind the scenes. As automated systems begin executing financial tasks at machine speed, banks must build platforms that are scalable and interoperable enough to handle volumes far beyond human capacity.

Nate Gruendemann is a Product Manager at Grasshopper Bank, where he builds digital banking and lending products for startups, venture capital firms, and small businesses. A two-time venture-backed fintech founder, he previously founded Challenger, a platform for employer-sponsored emergency savings accounts that was acquired by TIFIN. His work increasingly centers on a core question for the industry: how banking infrastructure must evolve as AI begins to manage financial workflows.

"The relationship of the future will be built on reliability, yield, risk mitigation, and seamless interoperability with whatever AI tools the client prefers," Gruendemann says. For banks, this means prioritizing infrastructure that empowers AI agents rather than trying to lock down the user experience.

• Melting trench: The foundation of modern finance lies in invisible architecture. "The shift is cultural, forced by massive changes in consumer behavior. As humans delegate financial tasks to AI agents, they optimize for yield and complete tasks in parallel, generating far more transaction requests than humans can. If a bank doesn't see itself as an infrastructure company capable of that scale, its legacy protections won’t save it," Gruendemann explains.

• Towering wall: Refusing to modernize puts institutions at a strategic disadvantage. "The clearest signal a bank is in protection mode is manufactured friction. When clients struggle to access their own data, connect accounts, or integrate with new technologies, the bank is clinging to an outdated model. Overhauling technology, processes, and talent is very difficult if the culture and infrastructure aren’t already there," he continues.

Grasshopper Bank recently launched an MCP server, a protocol designed for agentic and autonomous AI tools. “MCP is a structured way for an LLM to interact with an API. It enables AI agents to retrieve context and act in the digital world,” Gruendemann explains, positioning the bank’s systems to support a future where financial activity is increasingly initiated and executed by software rather than people.

• Pioneering safety: "Moving from AI ‘analyst’ to ‘treasurer’ requires infrastructure to mitigate new risks. If an AI misinterprets a prompt, ignores instructions, or sends money to a fraudster, who is liable? Banks carry a heavier burden to protect clients than startups that can ‘move fast and break things.’ This transition requires safeguards: authority granting, audit logging, and human-in-the-loop veto power," says Gruendemann. He emphasizes that the regulatory and liability landscape is uncharted, and banks must pioneer frameworks for safety and transparency.

• Future time travel: "Community banks will persist through local roots and personalized expertise. However, as people and businesses increasingly rely on AI to automate their financial lives, the pie for legacy protectors will rapidly shrink. Human-to-human banking will become a premium niche, not the standard operating model," Gruendemann says. The AI-driver majority will leave traditional models behind.

Institutions that invest in resilient infrastructure, open interoperability, and client-controlled data will define the next era of banking. "As AI continues to take on a growing role in financial management, the institutions that lead will be those that design their systems for scale, transparency, and client empowerment. Banks that fail to do so risk becoming irrelevant in a world run by autonomous agents," Gruendemann concludes.