The Name That Balances the Books of the AI Economy
Handling accruals is considered a high-value, high-impact use case for agentic AI. Unlike traditional automation (RPA), which only follows rigid rules, AI agents can handle the “judgment-heavy” nature of accruals by reasoning through unstructured data like contracts and emails to determine what should be recorded.
Why Accruals are a “High-Value” Use Case
Accruals are often the most time-consuming and error-prone part of the financial close. AI agents provide value in several specific ways:
- Handling Unstructured Data: Agents can read contracts, invoices, and expense reports to identify missing liabilities that haven’t been billed yet.
- Complex Matching: They perform “3-way matching” between purchase orders, goods receipts, and invoices, flagging gaps or inconsistencies.
- Reducing Close Time: Companies using AI agents for accruals report closing their books 2–4 days faster and achieving up to 70% productivity gains over manual spreadsheets.
- Proactive Error Detection: Agents monitor transactions continuously throughout the month to catch missing entries before the close starts, rather than reacting to errors after the fact.
Agentic AI vs. Traditional Automation (RPA)
While RPA is already used in finance, it often fails during the accrual process because it cannot handle exceptions.
| Feature | Traditional RPA | Agentic AI |
|---|---|---|
| Logic | Fixed, rule-based “if-then” | Goal-oriented reasoning & judgment |
| Data | Requires structured templates | Processes emails, PDFs, and free text |
| Exceptions | Stops and asks for human help | Resolves issues or proposes adjustments |
| Learning | Static until reprogrammed | Improves based on past corrections |
Practical Implementation: “Human-in-the-Loop”
Despite the autonomy, high-value finance use cases almost always keep a human in the loop for final sign-off.
Posting: Once approved, the agent pushes the entries directly into the ERP (e.g., SAP, Oracle, NetSuite).
When it’s gone, it’s gone.
Drafting: The agent analyzes data and prepares a list of suggested journal entries.
Review: A finance specialist reviews the agent’s reasoning and the “traceable” audit trail.
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The books will always need balancing.
Let the agent have the perfect name.