Document Processing: How AI Transforms Accounting Workflows

Document processing uses AI to convert physical or digital documents into structured, usable data. It automates the extraction and classification of information from finance documents such as leases, invoices, or contracts, and integrates that data into ERP systems with speed, accuracy, and auditability.

Despite the rise of cloud ERPs, automation tools, and digital workflows, finance operations remain document-heavy. 

Invoices, lease agreements, payroll files, and intercompany contracts: these documents fuel the accounting process but often arrive in inconsistent, unstructured formats that delay reconciliation, close, and compliance.

Manual document work is time-consuming and high-risk. It requires trained eyes, tribal knowledge, and often, multiple rounds of back-and-forth. Finance teams spend hours transcribing, validating, and formatting documents into spreadsheets or posting them into ERP systems by hand.

AI-powered document processing changes that. It turns messy PDFs and spreadsheets into structured data that’s ready for ERP ingestion, accurately, quickly, and at scale. And it’s not theoretical. In this post, we’ll show how Nominal Copilot brings this to life using real examples from our Bottom Lines series.

What is AI-powered document processing?

AI-powered document processing uses natural language models and machine learning to read, interpret, and extract information from unstructured or semi-structured files. In finance, that means transforming leases, invoices, contracts, and more into structured journal entries or subledger records.

The core components of a modern AI document processing solution include:

• Data extraction: Identifying and pulling out key fields (amounts, dates, entities, terms)
• Data structuring: Converting the raw values into normalized formats that follow accounting rules
• System integration: Syncing the structured data into the ERP or GL as native objects

Unlike legacy OCR or rule-based automation, AI-driven systems understand document context. They can distinguish between similar forms, infer missing values, and even adapt to regional or entity-specific logic.

Compatibility with ERP workflows is crucial. Outputs must align with the existing chart of accounts, approval paths, and reconciliation logic to be useful. That is why Nominal Copilot does not just extract text. It generates ERP native records designed for real-world use.

Recommended read: The Real Impact of AI in ERP for Multi-Entity Teams

Why it matters for finance operations

Finance teams are under pressure to move quickly, maintain accuracy, and ensure compliance across increasingly complex environments. But manual document work introduces friction at every step, from invoice validation to lease scheduling to intercompany billing.

AI-powered document processing tackles this challenge by removing the operational bottlenecks that unstructured files create. 

Rather than depending on spreadsheets, email chains, and human memory, finance leaders can rely on automated systems that structure and standardize their data from the outset.

Turnaround time

Faster processing of leases, invoices, and contracts accelerates monthly and quarterly closes.

Consistency

Centralized interpretation logic ensures entity-wide consistency in how documents are handled and posted.

Audit readiness

All extracted records are traceable and built with embedded validation workflows, ready for audit without rework.

Cost savings

Automated document review and data entry reduce labor costs and free teams to focus on exceptions, not inputs.

Compliance confidence

AI helps maintain compliance across tax, intercompany, and regulatory frameworks by capturing the right terms, classifications, and supporting data.

The bigger picture: these benefits compound. Once your team can reliably generate ERP-ready records from documents, you improve not just speed but strategic visibility. 

Review cycles tighten. Controls improve. And most importantly, teams have time to focus on financial insight instead of formatting.

Real world example: Lease accounting with Nominal Copilot

In Bottom Lines Episode 2, we showcased how Nominal Copilot processes a lease agreement and turns it into an ASC 842-compliant schedule in just a few steps:

• Upload an unstructured lease agreement
• Extract payment terms, start and end dates, discount rate, and clauses using AI
• Validate missing or ambiguous values through guided human input
• Structure the extracted data into a compliant lease schedule
• Sync the schedule with the ERP as a native Nominal object

The result? A ready-to-use lease schedule is generated in minutes, not hours. Human review remains part of the loop, but rather than redoing work, teams simply approve and enhance what AI initiates.

And because Copilot supports bi-directional ERP sync, any downstream changes are reflected in your source systems without duplication or delay.

Curious how other finance teams are putting AI to work? Dive into more episodes from our Bottom Lines series:‍

• Generative AI for Flux Analysis
• AI Agents in Finance and Accounting: From Manual Tasks to Strategic Insights
• Understanding Agentic AI in Accounting

Nominal Copilot makes document processing available to every finance team with no migration required. It integrates with your ERP, generates structured records with full context, and supports audit-ready processes across subledgers.

AI document processing is no longer a future state vision. It is already transforming how finance teams work, helping them close faster, reduce risk, and operate with greater confidence at scale.

By automating document-heavy workflows like lease accounting, vendor billing, and intercompany reconciliation, Nominal helps finance teams move beyond spreadsheets and manual inputs. The result is structured, auditable, and ERP-ready data with significantly less effort.

Ready to eliminate manual document processing from your workflow? Book a demo to see how Nominal Copilot can streamline your operations today.