AI accounting agents are a new way to scale finance team capacity without adding headcount, and they’re changing how finance teams run month-end.

Finance teams run dozens of workflows every month — prepaids, accruals, deferred revenue, payroll, intercompany, AP/AR tie-outs, flux analysis, and countless custom schedules in Excel.

Each workflow is different, but they usually share a few common characteristics:

• They rely on data pulled from multiple systems (ERP, banks, payroll, billing, subledgers)
• The accounting logic sits in spreadsheets or manual checklists
• The outputs include artifacts, reconciliations, rollforwards, journal entries, or flux explanations
• Accounting teams spend too much of the close collecting and validating data, fixing spreadsheets, and assembling support, long before they get to the actual accounting analysis

This makes the work predictable — and ideal for AI agents.

AI accounting agents can read your working papers, apply your rules, calculate schedules, reconcile balances, draft entries, generate flux explanations, and even perform deterministic actions in your ERP. You stay in review-and-approval mode while the agent runs the workflow.

Below are nine core accounting workflows where teams using Ledge see the biggest impact from agents. Each one represents a month-end process, and shows how an agent can transform it from manual prep to automated execution.

1. AI Agent for Prepaid Amortization and Prepaid Rollforwards

(Instead of babysitting a giant amortization spreadsheet every month)

The challenge

Prepaids are one of those workflows that sounds simple in theory, but in practice you are:

• Maintaining a prepaid amortization schedule and monthly amortization table by vendor, bill, PO, and start / end dates
  
• Updating additions, monthly amortization, and ending balances
  
• Doing a prepaids rollforward and reconciling the GL balance against the amortization schedule
  
• Reviewing period-over-period amortization and ending balance variances and explaining spikes to FP&A and auditors
  
  

The detail lives in a spreadsheet. The system of record is NetSuite or another ERP. You are the glue.

How an AI agent solves this

A prepaid amortization agent:

• Connects to your ERP and pulls all prepaid-related bills and balances, or ingests your existing amortization schedule as a CSV or Excel file
  
• Identifies which bills should be amortized, over what period, and calculates the monthly amortization schedule
  
• Auto-builds the prepaid rollforward: prior balance, additions, amortization, ending balance
  
• Compares the amortization schedule to the GL and flags differences by vendor or account
  
• Prepares the monthly amortization journal entries with full audit backup
  

You review the proposed schedule and entries, make any overrides, then approve. The agent updates the working paper and can push the journal to your ERP.

With Ledge: creating a custom AI agent for Prepaids takes minutes to configure — upload your schedule or click to connect NetSuite, tell the agent your process once, and the agent maintains everything monthly.

2. AI Agent for Month-End Accrual Schedules and Accrual Rollforwards

(Rather than rebuilding the same accrual schedule and true-ups every close)

The challenge

Accruals are a classic spreadsheet workflow:

• Building an “accrual candidates” list from open POs, uninvoiced items, recurring services, prior period accruals, and inputs from team members and vendors
  
• Calculating accrual amounts and true-ups when invoices finally arrive
  
• Maintaining an accrued expenses rollforward, plus JE backup for auditors
  
• Explaining variances between estimates and actuals, month over month
  

The logic is repeatable, but it is trapped in spreadsheets and tribal knowledge. It's exhausting, and no one likes chasing people for info and answers… 

How an AI agent solves this

An accruals agent:

• Pulls open POs, GRNs, recurring contracts, and prior accruals from your ERP and other systems, or ingests your existing Excel template
  
• Applies your accrual logic by category, vendor, or threshold, and proposes accrual amounts
  
• Builds an accrual rollforward with additions, reversals, true-ups, and ending balance
  
• Prepares accrual and reversal journal entries with clear narrative support
  
• Analyzes estimate vs actual variances and highlights where your assumptions need updating
  

With Ledge: You can automate your accruals by configuring custom agents for your specific needs — the agent re-runs them every month and learns from your changes and feedback.

Ledge agents can also automatically attach relevant evidence — including screenshots or supporting documents from integrated systems — so the accrual package is fully backed up without manual hunting.

3. AI Agent for Deferred Revenue Schedules and Revenue Recognition

(Instead of hand-maintaining rev rec and deferred revenue waterfalls)

The challenge

Revenue deferrals often involve:

• A deferred revenue rollforward for each product, contract, or revenue stream
  
• A revenue recognition schedule with monthly amortization and a waterfall view
  
• Reconciliation between the deferral schedule and the GL
  
• Analysis of recognition variance, contract-level anomalies, and timing differences
  
  

It usually lives in a fragile workbook with multiple tabs and complex formulas.

How an AI agent solves this

A deferred revenue agent:

• Reads your contract-level or product-level revenue data from your ERP, billing system, or CSV export
  
• Applies your deferral rules (by term, product, contract, or performance obligation) and generates the recognition schedule
  
• Maintains a def rev rollforward and waterfall view by account, entity, or customer
  
• Reconciles the deferred revenue balance in the GL with the agent-generated schedules
  
• Prepares monthly revenue recognition and deferral true-up entries, plus support for auditors
  

With Ledge: AI agents can be configured in a few minutes to automate deferred revenue schedules and revenue recognition. Because agents rebuild the schedule every month, teams avoid the risk of stale formulas or broken links that often accumulate in multi-tab revenue workbooks.

4. AI Agent for Payroll Reconciliation and Payroll Accruals

(Instead of manually tying payroll reports, JEs, and the GL together)

The challenge

Every month you have to:

• Reconcile payroll runs to the GL
  
• Build payroll accrual schedules for wages, taxes, benefits, commissions, and PTO
  
• Allocate payroll across entities, cost centers, and departments
  
• Investigate variances between payroll provider reports, journal entries, and the GL
  

There are multiple sources and formats, and the reconciliation logic is repetitive but time-consuming.

How an AI agent solves this

A payroll agent:

• Ingests payroll provider exports, GL balances, and prior payroll working papers
  
• Reconciles payroll runs to booked JEs and flags missing or duplicated entries
  
• Builds payroll accrual schedules based on cut-off, pay periods, and your policies
  
• Allocates costs across entities and cost centers according to your rules
  
• Prepares accrual and true-up entries, plus variance explanations for month-over-month or budget vs actual
  

With Ledge: agents can be configured easily to automate payroll reconciliation and payroll accruals. 

5. AI Agent for Intercompany Reconciliation and Due-To / Due-From Matching

(Instead of tracking due-to / due-from balances in a tangle of spreadsheets)

The challenge

Intercompany workflows usually involve:

• Matching intercompany transactions across entities and currencies
  
• Maintaining due-to / due-from rollforwards
  
• Building eliminations schedules for consolidation
  
• Investigating timing differences, mismatched amounts, and missing counterpart entries
  

Most of that ends up in spreadsheet trackers that quickly become unmanageable as you add entities.

How an AI agent solves this

An intercompany agent:

• Pulls intercompany transactions, balances, and FX rates from your ERP and bank data
  
• Matches transactions across entities, even when descriptions, amounts, or timing differ
  
• Maintains a due-to / due-from rollforward and flags breaks by pair of entities
  
• Suggests or prepares intercompany eliminations entries with proper metadata
  
• Surfaces recurring mismatch patterns so you can fix root causes in process or configuration
  

With Ledge: AI agents can be configured to automate intercompany reconciliation and due-to / due-from matching

6. AI Agent for AP and AR Subledger Reconciliation

(Instead of spending days tying aging reports back to the GL)

The challenge

Subledger reconciliation typically means:

• Downloading AP and AR aging reports
  
• Comparing them to GL balances and hunting for differences
  
• Creating discrepancy lists by vendor and customer
  
• Tracking timing differences, write-offs, and adjustments
  
• Explaining movement across aging buckets (current, 30, 60, 90)
  

Every step is spreadsheet driven, highly repetitive, and critical for audit and controls.

How an AI agent solves this

A subledger reconciliation agent:

• Ingests AP and AR aging reports and GL balances
  
• Automatically ties subledger totals to the GL and pinpoints discrepancies
  
• Groups breaks by driver: missing posting, timing difference, FX issue, misapplied payment, and so on
  
• Generates vendor and customer-level discrepancy lists with explanations
  
• Produces a subledger reconciliation package your auditors can follow at a glance
  
  

With Ledge: AP/AR subledger reconciliation can be automated with AI agents that run continuously and surface breaks instantly — no more from-scratch reconciliations.

7. AI Agent for GL Flux Analysis and Month-Over-Month Explanations

(Instead of manually slicing variances across accounts, entities, and drivers)

The challenge

Variance analysis is where your judgment really matters, but the prep work is tedious:

• Pulling GL balances by period and account
  
• Joining them with budgets, forecasts, or prior period actuals
  
• Segmenting by customer, vendor, product, or entity
  
• Identifying timing differences and one-off events
  
  

You spend more time on the mechanics of building the variance view than on explaining the story.

How an AI agent solves this

A variance analysis agent:

• Ingests GL, budget or forecast, and operational data from your systems or spreadsheets
  
• Produces standard variance views: GL vs source, period-over-period, budget vs actual, forecast vs actual
  
• Groups variances by driver: volume, price, mix, FX, timing, or classification
  
• Generates narrative explanations and suggested talking points for major swings
  
• Feeds those insights back into related working papers, so variances are documented where the work happens
  
  

With Ledge: flux explanations are automatically generated with AI and linked to support, so reviewers start with context and a really strong draft, not raw variances.You still own the message and decisions. The agent supplies the prepared analysis and draft commentary.

8. AI Agent for Fixed Asset Capitalization, Depreciation, and Rollforwards

(Instead of hand-maintaining fixed asset schedules and depreciation workpapers)

The challenge

Fixed assets often involve:

• Identifying which purchases should be capitalized vs expensed based on thresholds and policy
  
• Creating and maintaining a fixed asset register with cost, useful life, and depreciation method
  
• Calculating monthly depreciation and tracking accumulated depreciation and net book value
  
• Building fixed asset rollforwards showing additions, depreciation, disposals, and ending balances
  
• Reconciling gross assets and accumulated depreciation to the GL
  
• Explaining period-over-period depreciation changes and asset additions to auditors and FP&A
  

The logic is repeatable, but the work usually lives across spreadsheets, ERP modules, and manual UI steps that have to be rechecked every close.

How an AI agent solves this

A fixed assets agent:

• Pulls asset candidates from AP bills, POs, card transactions, or ERP data based on your capitalization rules
  
• Applies your policies to determine asset class, useful life, depreciation method, and start date
  
• Builds and maintains a fixed asset register and monthly depreciation schedule
  
• Produces a fixed asset rollforward with additions, depreciation, disposals, and ending balances
  
• Reconciles gross assets and accumulated depreciation to the GL and flags any breaks
  
• Prepares monthly depreciation and disposal journal entries with clear audit support
  
  

With Ledge: teams can turn existing fixed asset registers or depreciation spreadsheets into agents in minutes. Because agents rebuild depreciation schedules and rollforwards every month from source data, teams avoid stale formulas, manual uploads, and missed asset changes as the business scales.

9. AI Agent to Automate Any Spreadsheet-Based Accounting Workflow

(Instead of rebuilding custom Excel logic for every new workflow)

The challenge

If you step back, most accounting workflows follow a common pattern:

• Inputs: data exports from ERP, payroll, billing, banks, or other systems
  
• Rules: your accounting logic, policy thresholds, allocation methods, and approvals
  
• Outputs: a working paper, a set of journal entries, a reconciliation, and a variance explanation
  

Today, that logic is trapped inside individual spreadsheets. Every new workflow means copying templates, tweaking formulas, and hoping nothing breaks.

How an AI agent solves this

With Ledge, you can:

• Upload an existing working paper as a CSV or Excel file
  
• Let the agent infer what the workflow is trying to achieve (for example, prepaid amortization, an accrual schedule, a payroll allocation, an IC reconciliation) based on structure and formulas
  
• Encode your logic as an “agent recipe”: which inputs to expect, which checks to run, how to calculate outputs, and what documentation to generate
  
• Run that agent on new data sets each month, with full versioning and audit history
  
• Iterate as your policies or thresholds change, without re-engineering the whole spreadsheet

With Ledge: if you can describe the workflow in a spreadsheet, you can turn it into a an AI agent that runs it for you. Agents can also pull in relevant context from email threads, shared folders, or team channels (for example, approvals, policy clarifications, or supporting evidence) and link it directly into the working paper.

10. AI Agent for ERP UI Automation (NetSuite Clicking, Vendor Creation, Imports)

(Instead of babysitting repetitive clicks that the system should handle)

The challenge

Some workflows are barely “accounting” problems at all. They are UX problems:

• Having to click through a NetSuite amortization module for every bill over a certain threshold, across hundreds of subsidiaries
  
• Manually creating new vendors or customers when integrations (for example, from a card or AP system) cannot handle complex entity setups
  
• Fighting with brittle import tools, where a single cryptic error message can cost you an afternoon trying to load journal entries or master data
  
  

These are small, repetitive, and incredibly annoying. They show up every day.

How a UI AI agent solves this

A UI automation agent:

• Uses controlled,  read-only access to your ERP’s UI and APIs to perform the same clicks you would do yourself across any ERP workflow
  
• Can search for bills that match your criteria (for example, “all bills over 5,000 that are not yet amortized”) and runs the relevant action, or any other equivalent workflow
  
• Can create vendors or customers based on structured data from systems like Ramp, AP platforms, or onboarding tools, following your entity and approval rules
  
• Many UI automations — like pulling attachments, retrieving bill details, or extracting metadata — require no write permissions at all, which makes them ideal starter workflows.

With Ledge: finance teams create AI agents that automate repetitive NetSuite actions, without writing scripts, custom code, or engineering support. Ledge UI automation always runs with read-only or tightly scoped permissions by default. The agent cannot post or modify data unless you explicitly configure it to, and most teams start with read-only extraction workflows.

Most teams start with read-only tasks like pulling attachments, retrieving metadata, or capturing screenshots into working papers as they build confidence. Every UI automation run can produce a click-level log or optional video replay, so reviewers can see exactly what the agent did inside NetSuite, step by step.

Ledge turns accounting workflows into autonomous agents that run the close

Accounting AI agents are not limited to one feature or one module. They are a way to encode the work your team does today in spreadsheets and tools, and have a virtual assistant controller run that work for you.

A good way to think about it:

• Any workflow that lives in a spreadsheet can be automated by an agent
  
• Any repetitive action you take in your ERP UI can be automated by an agent
  
• Your role shifts from “building and maintaining working papers” to “designing, reviewing, and approving how the work gets done”
  

Instead of pre-built modules or rigid templates, each agent learns your workflow as you describe it or upload it — then generates the underlying code that will run the workflow the same way every period, giving reviewers full visibility into what will execute before anything happens. This lets teams automate processes even when they don’t match a vendor-defined structure.

With Ledge, finance teams can start with high-impact workflows like prepaids, accruals, deferred revenue, payroll, intercompany, and subledger reconciliation, then expand to custom working papers and UI automation as they go.

How Ledge makes it easy to create and deploy AI accounting agents

Agent Studio: Build and customize AI accounting agents in minutes, without writing code

Agent Studio — Create Powerful AI Accounting Agents in Minutes

Ledge’s Agent Studio is where finance teams turn their work into automation. It’s designed so that any accountant can build an agent, without engineering, scripting, or custom integrations.

Here’s what makes it different:

• Upload your working paper — or just describe your workflow: The agent can read your spreadsheet structure or take a natural-language description of the steps you follow each month. Either way, it extracts your logic, understands what you’re trying to achieve, and prepares a runnable workflow.
  
• Confirm the rules once: You tell the agent what matters: thresholds, timing, mapping, allocations, policies, reviewer steps.
  
• The agent now knows how to run that workflow forever: Each month it ingests new data, reruns the logic, rebuilds the schedule, and prepares the outputs.
  
• It learns from you: Every override, correction, or reviewer comment becomes part of how the agent behaves going forward.
  
• It works for any workflow: Prepaids, accruals, IC, payroll allocations, custom revenue models, multi-step reconciliations — if it lives in Excel, you can turn it into an agent.
  
• No black-box leaps: You can inspect every step, adjust the logic, and version changes.
  
• Agents can chain together: The output of one can feed another, powering multi-step, end-to-end workflows.

Most teams assume building an AI accounting agent requires deep technical expertise.  In Ledge, it doesn’t — because the agent generates the underlying code for the workflow, then re-uses that code safely and predictably every period.

You bring the workflow — whether it’s a spreadsheet you already maintain or a process you describe — and Ledge turns it into a repeatable agent you can refine, control, and reuse every month.

Agentic close checklist: Tasks run by AI agents before you even open them

In Ledge, the close checklist isn’t just a list of tasks – it’s the control panel for your agents.

Every checklist item can have an AI accounting agent behind it. At any time interval you set, those agents:

• Pull fresh data from NetSuite and other systems
  
• Refresh working papers and schedules
  
• Run reconciliations and checks
  
• Generate flux explanations
  
• Draft journal entries
  
• Attach the supporting evidence

By the time you open a task, most of the work is already done. The checklist clearly shows which tasks were prepared by an agent, which ones are waiting for human review, and which still need input from your team. 

You stay in review-and-approval mode: click into any task to see what the agent did, make edits if needed, and approve or post. Over time, agents learn from those edits, so each close gets lighter and more automated — without you having to rebuild workflows or rewrite rules.

Glassbox AI: Full visibility, control, and editability

Finance teams need to understand how numbers are produced — not just see an output. Ledge’s agents work in a glass box, meaning the full logic behind every step is visible and reviewable.

When an agent prepares a working paper, draft entry, reconciliation, or flux explanation, you can open it and see:

• The formulas it used
  
• The calculations it performed
  
• The data it pulled and where it came from
  
• The sequence of steps it followed
  
• Any assumptions or rules applied
  
• The evidence it attached

Nothing runs in the background without visibility. For every agent run or process automation, you can review the logic and every action it took. If something needs to change — a threshold, a method, a calculation — you can edit the spreadsheet output directly or give the agent feedback and tell it to re-run.

Each run produces a fully traceable record: what was executed, what data was used, what changed from the prior period, and what the final output represents. The result is automation you can audit, explain, and rely on.

Glass Box AI means the agent’s work is not hidden, abstract, or approximated. It’s transparent, verifiable, and designed so accountants can review it with the same rigor they apply to their own work.

Fast to adopt. Easy to scale. Built for real accounting workflows.

Agents can be configured and set up within minutes. Once they are set to run, they will run automatically at the interval you set - daily, weekly, monthly, etc. 

Most teams start with one workflow — prepaids, accruals, payroll, IC, subledgers, or flux — and quickly expand to dozens. Ledge agents learn from your overrides and keep your accounting policies embedded in every run.

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