Finance Automation

What AI Agents do for Finance Teams (With Real Examples)

Learn how AI agents transform finance operations by executing core workflows like variance analysis, AR aging, and forecasting. This post breaks down real use cases from teams using agents to cut hours of manual work.

July 17, 2025

What AI Agents do for Finance Teams (With Real Examples)

Finance teams aren’t short on dashboards or data. What they’re short on is time. Despite decades of digital tooling, much of the work still looks the same: reconciling variances, formatting reports, chasing overdue invoices, compiling backup for audits. These tasks don’t drive insight—they delay it. And the systems teams rely on—from aging ERPs to fragile Excel models—were never built for the complexity, speed, and scrutiny of modern finance.

Meanwhile, AI is everywhere, but mostly as static copilots or smarter search bars. They suggest, summarize, or surface patterns, but rarely act. That’s the gap because without execution doesn’t solve the problem.

AI agents are built to close that gap. They don’t just flag variances—they explain them. They don’t just summarize data—they reconcile it. Agents work on top of your existing systems—ERPs, planning tools, spreadsheets—and execute real workflows: vendor reviews, AR aging cleanups, forecast refreshes, audit packet prep. They operate like embedded analysts, executing in minutes what used to take hours.

In June alone, Concourse agents eliminated over 600 hours of manual work across finance teams—time that would have been spent toggling between systems, formatting exports, and tracking down missing context. This post breaks down exactly what that looks like, with real prompts and use cases from teams deploying agents today.

What Are AI Agents for Finance Teams?

At their core, AI agents are not just copilots—they’re autonomous operators. They translate intent (“Explain why marketing spend is up”) into execution: querying the right systems, joining relevant data, running the logic, and returning a structured output in seconds.

AI agents in finance are autonomous tools that execute end-to-end workflows—such as variance analysis, vendor reviews, and forecasting—by directly connecting to your financial systems. Unlike dashboards or copilots, they don’t just summarize data; they perform the actual work.

They don’t ask you to define filters or load templates. They handle the “how” behind the scenes—joining GL and budget data, filtering for the right time period, mapping spend categories, then generating both the numbers and the narrative. And because they understand financial data structures—your chart of accounts, period logic, entity hierarchies—they work with precision, not just pattern-matching.

AI agents are stateful: they can track context across tasks, chain actions together, and respond dynamically when the data doesn’t fit the mold. You’re not programming a workflow—you’re assigning a task.

For finance teams, that distinction matters. It’s the difference between asking “what happened” and having an answer ready before you finish the question. Whether it's identifying untagged journal entries, building a vendor spend analysis, or flagging anomalies in the cash forecast, agents don’t just surface insights—they do the work.

This isn’t AI as a lens on your data. It’s AI as an execution layer across it.

Why Finance Teams Are Adopting AI Agents in 2025

Most finance teams don’t have a forecasting problem—they have a friction problem. Every question from the business triggers a cascade of manual steps: exports, reconciliations, formula checks, PowerPoint updates. It’s the same playbook, whether you’re chasing an accrual backup or preparing for a board meeting. The bottleneck isn’t analysis—it’s execution.

We’ve written before about the rising workload across finance—see how AI agents support FP&A and how they streamline accounting tasks for more detail on those workflows. Teams are expected to close faster, forecast continuously, and deliver real-time commentary. But 81% still rely on spreadsheets as their primary tool. The average team spends 30–90 days on budgeting, and 63% can’t forecast beyond six months. That’s not a capability gap—it’s an infrastructure failure.

Meanwhile, the pace of decision-making hasn’t slowed. CFOs are being asked to weigh in on spend within hours, not quarters. Treasury teams face daily questions about liquidity. Controllers are under pressure to support zero-day close models, even as headcount shrinks.

This is where AI agents fit—not as a replacement for your ERP or Excel models, but as a force multiplier. They sit on top of your stack, speak your data’s language, and do the work between the ask and the answer. Think of them as execution bandwidth: available on demand, always accurate, and never overwhelmed.

They don’t just make workflows faster. They make modern finance possible.

What are the top AI agent use cases in finance?

Here are four high-impact workflows that Concourse agents are automating for finance teams today. These aren’t narrow use cases—they span across accounting, FP&A, and operational finance. What makes them powerful is that they all run through the same platform. One prompt in, one output out—whether you’re chasing collections, reviewing spend, or preparing for the board.

This isn’t “point solution” AI. This is your daily finance workflow—automated.

How to Automate Variance Analysis

Before: You export GL actuals, identify deltas, trace vendor-level details, dig through contracts, and then draft commentary. It’s manual, disjointed, and easily a 90-minute task per line item.

Prompt: “Highlight all expense categories in Q2 2024 that increased by more than 10% compared to Q1 2024. For each, explain the primary driver of the variance.”

With Concourse: The agent pulls actuals, identifies the delta, checks for major vendor or category shifts (e.g., a new Salesforce contract in April), calculates the net variance, and returns a full explanation, backed by invoice-level details in a downloadable workbook.

Outcome: A clean narrative, with data and context, ready for leadership review or audit backup—in less than a minute.

Curious what this could look like for your team? Finance teams using Concourse span SaaS, healthcare, manufacturing, and more.

→ Join the waitlist to see how these agents could plug into your current stack.

How to Track Overdue Payments with AI

Before: You export AR data from your ERP, apply aging buckets in Excel, filter manually, highlight overdues, and then format the results. It’s tedious, and every version is a snapshot that’s stale by the time it’s shared.

Prompt:“Generate an AR aging summary report as of July 17, 2024, using NetSuite transaction dates. Group all open balances into standard aging buckets (0–30, 31–60, 61–90, >90 days past due) and flag any transactions over 90 days.”

With Concourse: The agent accesses your AR ledger, calculates aging buckets, flags at-risk accounts, and returns a report with dynamic filters. You can export it, drill into specific customers, or route insights to collections—all from a single prompt.

Outcome: A real-time aging report, delivered daily, without needing to chase down IT or rebuild in Excel. Teams reclaim hours weekly and surface risk faster.

How to Generate Vendor Spend Reports Automatically

Before: You download transaction logs, VLOOKUP vendor names, tie them to departments, build a pivot, and create visuals for reviews. One miscode or missed join, and the whole analysis breaks.

Prompt:“Show vendor spend by department for Q3 2024 and compare it to Q2 2024. Highlight any vendors with significant increases.”

With Concourse: The agent joins vendor, GL, and department data from your ERP and expense tools, runs the comparison logic, and generates a variance summary, fully pivoted and formatted. Ready to drop into a budget review deck.

Outcome: A process that used to take a day now happens in under 30 seconds, with full audit trails and exportable workbooks.

How to Refresh Revenue Forecasts Using AI Agents

Before: You consolidate actuals manually, update Excel drivers, adjust assumptions, and rerun scenarios. Just getting to a “clean starting point” can take 4–6 hours across tabs and versions.

Prompt:“Refresh the revenue forecast using actuals from Q2 2024. Flag any assumptions that appear stale or inconsistent with recent performance trends.”

With Concourse: The agent loads actuals from your ERP, updates the forecast template or model logic, checks for assumption mismatches, and returns an updated version with flagged discrepancies. No copy-pasting. No broken links.

Outcome: Rolling forecasts become continuous. What once required an analyst’s full day now happens on demand.

These use cases aren’t demos—they’re live workflows from teams using Concourse every day. They reflect what modern finance work looks like when the friction is removed and the system executes for you.

How Concourse Transforms Finance Operations

Every finance team wants better insight, but insight without execution is just another to-do. That’s where Concourse stands apart. Across flux analysis, AR aging, vendor reviews, and forecasting, our agents aren’t giving you a chart—they’re giving you the answer, backed by data, logic, and context, ready to use.

In the past 30 days alone, Concourse agents have:

Eliminated over 600 hours of manual work across finance functions—from reporting prep to variance commentary.
Helped a $120M SaaS company reduce their close review time by 40% by automating flux commentary and forecast refreshes.
Enabled a multi-entity logistics firm to centralize vendor reporting across six departments—replacing a full day of manual reconciliation with a single prompt.
Resolved high-friction workflows that used to delay close cycles, forecast updates, and review prep.
Increased execution velocity, enabling finance teams to move from question to action in minutes, not days.

This isn’t theoretical efficiency. These are real tasks, replaced in full—no manual exports, no pivot tables, no guesswork. Just a clean input (“Show me Q2 vendor variance”) and a usable output (narrative + workbook).

A New Operating Layer for Finance

Concourse isn’t another dashboard or tool to manage. It’s the connective tissue between your systems and your decisions—built for the work finance does every day. Teams aren’t logging in and navigating menus. They’re prompting, executing, and moving on.

You stay in control. The agent handles the friction.

Ready to See It in Action?

If you want to reduce reporting overhead, accelerate forecasting, and eliminate manual follow-ups across your finance workflows, Concourse is built for you.

Join the waitlist or reach out to hello@concourse.co to schedule a walkthrough tailored to your current stack.

Want more examples? See how other finance teams are using Concourse agents to automate workflows like close prep, forecasting, and vendor reviews.

Let your team focus on decisions. Let the agent handle the work.

Frequently Asked Questions About AI Agents for Finance

1. How can I automate flux analysis in our monthly close process?

Concourse automates flux analysis by pulling GL data, identifying deltas, and generating narrative-ready explanations backed by invoice-level detail. What used to take an hour per line item now runs in seconds, with full audit trails and exportable summaries.

2. What's the fastest way to get real-time AR aging reports by customer?

With Concourse, AR aging reports are generated from live ERP data, complete with dynamic filters and overdue account flags. Teams can route insights directly to collections and skip the manual Excel wrangling entirely.

3. How do AI agents improve finance workflows beyond just reporting?

Concourse agents don’t just summarize data—they execute tasks like reconciling entries, building forecast models, and preparing vendor spend analyses. They work across your ERP, Excel, and planning tools to automate the “work between the work.”

4. Can I use AI to refresh our revenue forecast with actuals automatically?

Yes—with Concourse, you can update revenue forecasts by pulling in ERP actuals, syncing with your forecast model, and flagging any broken assumptions. It replaces hours of manual updates with a single prompt.

5. How do AI agents compare to RPA or dashboard tools in finance?

Unlike RPA or BI tools that require predefined rules or templates, Concourse agents operate autonomously, using financial logic and system context to dynamically execute workflows, like vendor comparisons, AR tracking, or close prep.

6. What is financial variance analysis, and how can AI help?

Financial variance analysis is the process of comparing actual results to forecasts or budgets to explain discrepancies. It helps finance teams understand over- or under-performance and improve forecasting accuracy. With AI agents like Concourse, this analysis can be fully automated, eliminating manual exports and generating real-time, audit-ready explanations.

7. How do I reduce manual steps in preparing for board meetings or budget reviews?

Finance teams using Concourse eliminate hours of prep work by prompting agents to generate flux commentary, refresh forecasts, and export vendor summaries directly into review-ready formats—all from live data sources.

8. Can I get vendor spend breakdowns by department without building a custom report?

Yes. Concourse agents pull vendor, GL, and department data from your ERP, apply comparison logic, and return formatted summaries with variance insights. It’s board-ready analysis with no spreadsheet gymnastics.

9. How do finance teams scale execution without increasing headcount?

Concourse acts as an execution layer that extends your team’s bandwidth. Agents handle recurring tasks like AR tracking, flux analysis, and forecasting updates, so analysts and controllers can focus on decision-making, not formatting data.

10. What’s the most efficient way to spot issues in our forecast model assumptions?

With Concourse, agents can identify mismatches in assumptions, broken logic, or stale drivers during model refreshes. You get a clean, flagged version of your forecast with actionable insight, ready in minutes.