Ramp Debuts AI Agents Designed for Company Controllers

The new offering is designed for controllers, helping them to automatically enforce company expense policies, block unauthorized spending, and stop fraud, and is the first in a series of agents slated for release this year, the company said in a Thursday (July 10) news release.

“Finance teams are being asked to do more with less, yet the function remains largely manual,” Ramp said in the release. “Teams using legacy platforms today spend up to 70% of their time on tasks like expense review, policy enforcement, and compliance audits. As a result, 59% of professionals in controllership roles report making several errors each month.”

Ramp says its controller-centric agents solve these issues by doing away with redundant tasks, and working autonomously to go over expenses and enforce policy, applying “context-aware, human-like” reasoning to manage entire workflows on their own.

“Unlike traditional automation that relies on basic rules and conditional logic, these agents reason and act on behalf of the finance team, working independently to enforce spend policies at scale, immediately prevent violations, and continuously improve company spending guidelines,” the release added.

PYMNTS wrote earlier this week about the “promise of agentic AI,” systems that not only generate content or parse data, but move beyond passive tasks to make decisions, initiate workflows and even interact with other software to complete projects.

“It’s AI not just with brains, but with agency,” that report said.

Industries including finance, logistics and healthcare are using these tools for things like booking meetings, processing invoices or managing entire workflows autonomously.

But although some corporate leaders might hold lofty views for autonomous AI, the latest PYMNTS Intelligence in the June 2025 CAIO Report, “AI at the Crossroads: Agentic Ambitions Meet Operational Realities,” shows a trust gap among executives when it comes to agentic AI that highlights serious concerns about accountability and compliance.

“However, full-scale enterprise adoption remains limited,” PYMNTS wrote. “Despite growing capabilities, agentic AI is being deployed in experimental or limited pilot settings, with the majority of systems operating under human supervision.”

But what makes mid-market companies uneasy about tapping into the power of autonomous AI? The answer is strategic and psychological, PYMNTS added, noting that while the technological potential is enormous, the readiness of systems (and humans) is much murkier.

“For AI to take action autonomously, executives must trust not just the output, but the entire decision-making process behind it. That trust is hard to earn — and easy to lose,” PYMNTS wrote, noting that the research “found that 80% of high-automation enterprises cite data security and privacy as their top concern with agentic AI.”