We are at an AI inflection point.
In the early years of NASA’s space program, the West Computing Group was a segregated division composed entirely of African American female mathematicians who performed critical mathematical calculations by hand. Their work was meticulous and essential, requiring exceptional mathematical ability and precision.
The group’s supervisor, Dorothy Vaughan, had the foresight to recognize that her team might be replaced by NASA’s new IBM computing machines. She taught herself FORTRAN, the computing language used by the machines, and led her team’s transition from human computers to computer operators. By teaching them to work with these new technologies rather than compete against them, Vaughn ensured the team’s continued relevance. If you’ve ever read the book or seen the movie Hidden Figures, you may remember this moving and powerful story.
As a finance professional, you may have noticed a similar inflection point developing with the adoption of artificial intelligence (AI). The rapid changes from global events, economic shifts, and rising workloads are increasing the complexity and volume of work. Companies are looking for solutions. And AI is the technology they’re turning to. Companies like AppZen that have spent the last decade building AI applications from the ground up are now creating the necessary infrastructure to expand the technology into many different areas.
The transition is well underway. AI is already working alongside people. It’s helping them draft emails, analyze spreadsheets, speed up workflows, and rapidly iterate on designs. Global finance teams are increasingly becoming strategic partners and tech-savvy problem-solvers within their companies.
At AppZen, we see even farther ahead, to finance teams transitioning from AI operators to managers of AI agents. AI agents are designed to be trusted digital partners that actively complement your work and improve decision-making, to help you and your team adapt to changing conditions.
What are AI agents, exactly? And how can they help you and your team?
How are AI agents different from “normal” AI?
Artificial intelligence is a set of models or algorithms that make predictions, classify data, or bring forward helpful insights.
AppZen’s core AI is the intelligence engine that powers many of the capabilities customers already know—it analyzes data, surfaces insights, flags issues, and improves its performance over time. For example, it can detect duplicate invoices, highlight policy violations, or score the risk level of an expense report.
But that’s where it stops.
On its own, AI doesn’t do anything with those insights—it still needs an external push, like a system or a person, to tell it what happens next. 
AI does the thinking. AI Agents do the work.
AI agents go further, combining intelligence with action—they don’t just analyze or recommend; they execute.
An AI agent is like a smart digital helper that can do specific tasks for you automatically. Instead of just following fixed instructions, it can understand information, make decisions, and take actions on its own, the way a human would—but faster.
AI agents can work within the guidelines set for them and have the flexibility to adapt to different situations. For example, AppZen’s AI will highlight when an invoice looks suspicious based on complex pattern recognition. An AI agent, on the other hand, will flag the invoice, stop payment, notify the right stakeholders, and draft an email asking the vendor for clarification—all without waiting for you to step in and tell it what to do next.
This is why AI agents are often described as the next evolution of automation. They bridge the gap between insight and action.
How can AppZen’s agentic AI help your finance team?
AppZen’s AI Agents (spelled with a capital “A”) take specific actions in real time and across systems, like approving invoices or rejecting noncompliant expenses. They send payment instructions to the ERP, escalate exceptions to a human, and can initiate outreach to a vendor. In short:
AppZen AI = “Here’s the insight, here’s what’s wrong.”
AppZen AI Agents = “Here’s the insight, and I’ve already taken care of it.”
After checking your AP inbox for supplier emails containing invoices, the AI Agent ① Scans the invoice for errors → ② Checks it against your purchase orders → ③ Approves it if everything matches → ④ Sends it to your ERP system for payment. Alternatively, if something looks off, it can independently alert a human operator and draft an email to the supplier with details about the exception.
For example, when an invoice arrives in your AP inbox, AppZen’s AI Agent Workbench for AppZen Inbox uses an advanced approach to handling emailed invoices that require approvals. It creates and assigns tasks for emailed invoices, using intelligent AP ticketing. It then routes invoices to the correct stakeholders so they can take action, and tracks those tickets to keep invoice processing moving smoothly.
In this conception, humans manage and optimize the work these Agents do.
Your future role in finance: AI Agent Boss
Finance teams may one day be managing cadres of these AI Agents, as organizations evolve into agentic teams, with human “managers” coordinating groups of AI agents.
“The [org chart] of the future will undoubtedly have more agents than humans - by 10x or 100x is hard to say. The leverage from AI is hard to overstate & expectations for speed, depth of thought, creativity, & effectiveness will surge as a result - a huge opportunity for those who understand how to use these new tools effectively.”
Tomasz Tunguz, venture capitalist and thought leader,
Like Tunguz, we imagine the organizational chart evolving to look something like this:
This org structure allows people to spend more time on high-value work. It leaves room for tasks that require “soft skills,” such as relationship building with vendors or compliance conversations with employees. As AI Agents share deeper data analysis, it also becomes easier for people to accurately adjust and optimize processes for compliance, cost savings, and overall efficiency.
3 common reactions to AI agents...
Like most innovations, there must be an advantage to adoption, or companies and individuals will resist new ways of working. Most companies take one of three paths when faced with the prospect of adopting AI Agents. The optimal approach depends on your organization’s risk tolerance, competitive position, and resource availability:
Wait and see - Observe the success of agentic AI adopted by others before considering any organizational or personal action.
Repercussions: Lost market share, loss of competitive advantage, talent moves to companies with better opportunities
Try and evaluate - Experiment with agentic AI on a trial basis to determine its effectiveness and value before committing to fully embracing the technology.
Repercussions: Analysis paralysis, suboptimal implementation, careful evaluation mistaken for indecision
Immersion - Immediately dive deeply into learning about and fully embracing agentic AI as an early adopter.
Repercussions: Implementation cost and risk, training challenges, culture shock of rapid change (At AppZen, we offer tools and training, simplified implementation, and ongoing support to reduce the effects of change management disorientation.)
Dorothy Vaughan did not take a “wait and see” approach to the IBM computers she saw set up on her campus. Nor was she offered an opportunity to try them and evaluate their effectiveness. Instead, she took the initiative to learn. She immediately dove into studying how they work and immersed her team in that process. These women then became a foundational part of the next wave of technology and space exploration.
AI is developing quickly and being adopted more widely than any technology since the internet or smartphones. Tools like ChatGPT, for example, hit 100 million users within two months, faster than any previous consumer technology. Finance teams that are early adopters are seeing rapid ROI and clear market advantages, such as speeding up business processes, cost-takeout, and the ability to rapidly scale, all of which translate into hard dollar savings. And for the people in those finance teams, learning how to use AI makes them more valuable employees.
…and 3 powerful lessons
Dorothy’s story presents powerful lessons for finance teams today. Just as she pivoted from manual calculations to computer programming, transitioning from spreadsheet-bound an analysis to AI-enhanced decision support is the only way to maintain relevance.
The story demonstrates the power of anticipating change by identifying which financial processes can be automated before they become obsolete. It highlights the importance of continuous learning, becoming AI orchestrators in order to configure and optimize AI systems. And it reminds us that finance teams that embrace new technologies can evolve from transaction processors to critical, strategic business partners, ready to meet modern challenges with real-time insights that drive competitive advantage and business growth.
Ready?
The shift to AI and the development of AI agents isn’t slowing down. Investment in AI is expanding, with one in three companies allocating over $25 million in AI investments for 2025. If you’re ready to extend your learning and discover how AI Agents can benefit your team in the face of this global change, we’re ready to elevate you to Agent Boss.
Contact us today for a live demonstration and explore what AI Agents can do for you.
