What are AI agents? A primer for finance and accounting managers

An introductory primer by Fenmo AI for finance and accounting managers on what AI agents really are and what it means for their teams.

TL;DR

AI agents (or co-workers) are not just fancy chatbots. Think of them as autonomous teammates that understand workflows, make decisions like humans, and help you eliminate repetitive tasks — from recon to close. They're changing the game for finance teams by owning full workflows: fetching, matching, following up, and reporting — all without dashboards or manual nudges. If you’ve heard of ChatGPT, this is like giving it a desk in your finance team and telling it: “Handle this.”

Table of Contents

• What Exactly Are AI Agents?

• Why Should Finance Teams Even Care?

• Where Can AI Agents Actually Help?

• How Are They Different From Rules-Based Automation or RPA?

• Real Examples of What Agents Can Do

• But… Are They Reliable?

• Final Thoughts: First They Reconcile, Then They Plan

What are AI Agents, exactly?

At their core, AI agents are like digital colleagues who can:

• Autonomously work without human triggers.

• Perceive and process data across formats—emails, spreadsheets, PDFs, dashboards.

• Reason based on past patterns and make smart decisions.

• Take actions like matching transactions, escalating mismatches, or updating ledgers.

Think of them like an ultra-efficient teammate who knows your SOPs but never complains.

👉 Would you rather sift through dozens of exception cases—or have an assistant do it, and just review the ones that matter?

Why Is This a Big Deal for Finance Teams?

AI agents transform how work gets done. Here's why it matters:

• Less grunt work: Offload repetitive tasks like statement downloads, ledger matching, or email parsing.

• Scale without burnout: Agents don’t slow down during peak close cycles.

• Higher accuracy: They don’t get tired or make copy-paste mistakes.

• More strategic output: Your team can focus on analysis, decision-making, and business partnering.

👉 How much more insight could you deliver if you weren’t bogged down by repetitive reconciliations?

How They Work – From First Principles

Here’s a simplified anatomy of an agent:

Input ➔ Processing ➔ Decision ➔ Action ➔ Output

Take AR reconciliation:

1. Input: ERP data, emails, remittance PDFs, and bank statements.

2. Processing: Reads files, extracts relevant data like invoice IDs, amounts, narration.

3. Decision-making: Uses logic + fuzzy matching to link transactions.

4. Action: Posts journal entries, marks invoices as paid, or raises flags.

5. Output: Updates ledgers, compiles reports, pings the team only if needed.

This loop keeps running — autonomously.

Beyond Reconciliation: Real-World Use Cases

Month-End Close

• Tracks what’s completed and pending.

• Gathers GLs, bank data, substantiation docs.

• Drafts journals or schedules tasks for manual review.

Cash Forecasting & FP&A Prep

• Pulls actuals vs plan.

• Groups transactions by vendor, payment category, cost center.

• Flags material deviations.

Audit & Compliance

• Highlights out-of-policy entries.

• Alerts on duplicate or round-number transactions.

• Keeps an audit trail of AI decisions.

Email Parsing & Vendor Follow-up

• Reads emails like "Payment done. Details attached."

• Downloads the PDF, parses it.

• Matches it to open invoices, closes the loop.

Ask yourself: 👉 Which repetitive part of your monthly cycle would you hand over—if you could?

How They’re Smarter Than Old-School Automation

RPA and macros are brittle. They follow if-else logic.

AI agents:

• Understand intent behind messy narration.

• Handle variations: vendor names, narration formats, partials.

• Get smarter every time you correct or approve their suggestions.

They mimic how your best team member reasons through a complex scenario—but 100x faster.

Common Concerns—Debunked

“Will AI take my job?” No—it replaces tasks, not your judgment. You get to review and sign-off.

“Is it secure?” Yes. Most tools have enterprise-grade security, full logging, and RBAC.

“What if it makes mistakes?” It can. But most start in draft/suggest mode—you still control final action.

Getting Started: A Simple Roadmap

1. Pick one workflow — like AR recon or vendor email handling.

2. Choose a platform — prioritize ones built for finance (with audit trail, approval layers).

3. Start in suggest mode — let the agent flag and match, while you approve.

4. Expand gradually — add multi-step actions like auto-emails or entry posting.

5. Measure impact — track hours saved, errors reduced, faster close time.

Challenge: 👉 Can you identify one process that eats more than 5 hours a month—and could be handed off?

Final Thoughts

AI agents aren’t here to replace finance teams. They’re here to remove the repetition and unlock better outcomes.

• Stop acting like bots.

• Start leading with insight.

• Let agents handle the mess, while you steer the ship.

Food for thought: 👉 If one AI agent saved your team 50 hours a week, what impactful work would you finally have time for?

Take the first step in your AI transformation journey with Fenmo AI. Schedule a use-case mapping call with us to identify the low hanging workflows for fastest ROI.

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written by Dhruv Goel (DG)

DG is the Founder & CEO of Fenmo AI. He leads solutions consulting and product vision at Fenmo. Before founding Fenmo, he was the youngest Director at a large SaaS + Services company, where he led Fundraising, Business Finance, and Customer Success functions. He is a second-time founder and has a bachelor's degree from the prestigious Indian Institute of Technology.