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Dernière mise à jour :
June 16, 2025
5 minutes
In a context of strong evolution of accounting methods, the automation of imputation represents a major advance. It aims to simplify and secure the assignment of transactions to the correct accounting accounts, by considerably reducing processing time and the risk of error. Faced with this dynamic, a question naturally arises: **Can AI replace manual accounting entry? This is what we are going to see in this article.
Can AI and OCR replace manual accounting entry? Discover the future of automated accounting.
Accounting requires constant rigor, but it is still a particularly time-consuming activity today, especially when entering transactions. Despite technological developments, the majority of categorization operations are still carried out manually, requiring many hours to analyze invoices, identify the nature of expenses and assign them to the correct accounting account.
Long based on tedious manual entry, accounting is now undergoing a transformation driven by artificial intelligence and optical character recognition (OCR). These technologies go far beyond simple digitization: they now make it possible to automatically extract essential data: amounts, dates, references directly from the documents.
Before exploring the impact of AI and OCR on accounting, let's first recall what accounting entry exactly consists of.
Accounting entry consists in recording all the financial transactions of a company in the accounting books.
Each entry must include specific elements: date, amount, supplier or customer, and above all, the accounting account corresponding according to the nature of the operation.
To achieve this categorizing, the accountant relies on the information on the invoices (description of the product or service, type of service, VAT) as well as on context elements (sector of activity, internal projects, purchasing habits).
Practical illustrations of accounting entries
To better understand how the various entries are imputed, here are some examples illustrated using a specific color code.
🔴 In red : 606400 - Office supplies
🟢 In green : 218300 - Office furniture
🟣 In purple : 445660 - VAT deductible on other goods and services
The automation of accounting entries is now at the heart of concerns of the sector. Already begun with the rule engines found in many software programs, this transformation is accelerating thanks to advances in artificial intelligence.
New AI-based solutions are capable to automatically interpret The invoices, the Expense reports or even the bank statements, to extract useful data, perform bank reconciliations and offer adapted accounting assignments.
Ultimately, the entire entry process will be taken care of automatically, offering accounting firms considerable efficiency gains and allowing them to refocus on analysis and advice.
Faced with the challenges of manual invoice processing, accounting automation represents a major opportunity that firms must seize without delay.
Automatic imputation is a major advance, allowing accountants to classify and assign transactions to the appropriate accounts. This technology is particularly effective for managing purchasing accounts.
The integration of Accounting AI And of the OCR generates concrete benefits:
Accurate accounting accounting is essential to ensure the reliability of your company's financial statements. To accurately record each transaction, follow these key steps:
Artificial intelligence represents a major advance for the accounting sector. However, its adoption also raises a number of questions and challenges.
1- Protect the confidentiality of sensitive information
To be effective, AI algorithms require access to relevant and reliable data. This is a major problem for accounting firms, where compliance with professional secrecy is an absolute obligation.
Not all AI models provide a total transparency concerning the use of the data collected, their hosting or their storage period. Currently, it is for example unthinkable to transmit a complete customer file to a conversational AI such as GPT chat to extract specific elements. Strict measures must be put in place to regulate the use of these technologies.
2- Support organizational transformation
Beyond the question of data, the adoption of AI requires accounting firms to reorganize their functioning.
This involves:
The role of the human factor remains central: contrary to popular belief, AI is not intended to replace professionals, but to support them by automating repetitive tasks so that they can focus on missions to higher added value.
OCR is revolutionizing accounts payable management by automating the extraction and accounting of essential information:
Unlike many OCRs software, Koncile is distinguished by its ability to read and structure article lines on invoice.
This includes advanced invoice line item OCR capabilities, essential for processing multi-line invoices with detailed accounting needs.
Thanks to the combination of computer vision and intelligent analysis, the tool accurately extracts product descriptions, SKU references, quantities, unit prices, VAT rates, and discounts, even on varied layouts.
Our technology also analyzes the economic context of each transaction. It interprets the description of services or products to automatically offer an adapted accounting account (e.g. office supplies, maintenance expenses, subcontracting services).
Based on the supervised learning of thousands of categorized invoices, our AI detects recurring reasons, keywords and assignment logic in order to generate intelligent and reliable accounting pre-entry.
In concrete terms, instead of manually entering each piece of information, the user only has to validate or adjust the proposals that are already pre-classified.
1. Simple invoices (single entry) :
For a classic invoice, our AI extracts all the necessary information (amount, date, supplier, etc.) and directly proposes a single assignment to the appropriate accounting account.
2. Multi-line invoices (detailed entries) :
When an invoice contains several lines corresponding to different types of expenses (for example: purchase of equipment, services, delivery costs), our AI analyzes each line individually.
For each position, she:
If we take a new example of an invoice, here are the fields we can extract:
The process starts with the analysis of the document: characters and lines are detected, categorized, and then interpreted by artificial intelligence algorithms. Through linguistic and contextual analysis, the information extracted is refined.
With Koncile, OCR is no longer limited to extracting data: it becomes a real tool for intelligent automation of accounting entries, freeing up time for missions with higher added value.
It’s a complete ocr accounting solution designed to support accountants with accurate, context-aware suggestions.
Request your free demo today!
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