{"id":23704,"date":"2023-05-26T03:08:58","date_gmt":"2023-05-26T03:08:58","guid":{"rendered":"https:\/\/envoice.eu\/?p=23704"},"modified":"2025-11-24T16:37:11","modified_gmt":"2025-11-24T16:37:11","slug":"extract-data-from-invoice","status":"publish","type":"post","link":"https:\/\/envoice.eu\/en\/blog\/extract-data-from-invoice\/","title":{"rendered":"Extract Data from Invoice – A Simple Way to Do It"},"content":{"rendered":"

Using Artificial Intelligence and technologies like Optical Character Recognition is the easiest and fastest way to extract information from PDFs and images. Extracting information with AI is so common that you may have used this technology without realizing it.<\/span><\/p>\n

A lot of banks and fintech companies use OCR technology to speed up the signup process for clients. For instance, banking apps often ask you to take a photo of your identification card. Apps use extracted data from your ID to fill out specific fields automatically. You have to review information and edit fields when needed, but it reduces the time spent signing up for an account.<\/span><\/p>\n

Invoice data extraction follows the same process but instead of personal data, it captures information such as the invoice date, invoice number, amount, items purchased, and other invoice details.\u00a0\u00a0<\/span><\/p>\n

Why Automate Data Entry Now<\/b><\/h2>\n

Taking information from an invoice and entering it into accounting software is simple enough that anyone can do it. However, as transaction volumes increase, a manual data entry to process invoices takes a toll on the AP staff.<\/span><\/p>\n

Imagine this scenario.<\/span><\/p>\n

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An organization receives 500 invoices a month. If the average employee can process five invoices in an hour, an employee should complete invoice processing for 25 invoices in a day if there are 20 working days a month. Using the same assumption, an employee needs about 5 hours to enter information.<\/span><\/p>\n

What if the invoices received by the company increase to a thousand?<\/span><\/p>\n

Why AP Teams Struggle With Invoices<\/span><\/h2>\n

AP teams have to work extra hours to input data into the company software, often delaying processes that could be streamlined with invoice approval workflow software<\/a>. Since data entry is Step 1 in the process, delays in data processing can create a ripple effect on the invoice processing cycle.\u00a0\u00a0<\/span><\/p>\n

Unless the company adds another employee, it’s difficult to keep up with the workload. An Institute of Finance and Management survey reveals that 50% of AP staff compensate for the increasing volume of invoices by working longer hours.<\/span>[1]<\/span><\/p>\n

In some companies, only one employee handles processing about a hundred invoices a day. Employees often have extra responsibilities such as contacting vendors, requesting proof of delivery, and solving issues in the AP department on top of invoice processing. It\u2019s not unusual for an AP staff to work over 60 hours a week!<\/span><\/p>\n

As the workload increases for AP, employees almost always fall behind.<\/span><\/p>\n

And this is why AP employees have a never-ending to-do list. Scrambling to keep up when the month-end comes around is an issue most companies deal with. What’s worse is that data entry nightmares don\u2019t end with AP.<\/span><\/p>\n

\u00a0After invoices get approved, accounting departments must prepare cash disbursements. If your company maintains multiple systems that require invoice data, you need to enter information several times.<\/span><\/p>\n

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Courtesy of Getty Images\/Canva<\/figcaption><\/figure>\n

In small organizations with a few invoices to process, manual data processing may be the least of their problems, but it’s a different story for companies with high invoice volumes.<\/span><\/p>\n

Unsurprisingly, about half of AP staff have plans of leaving their current organization. Reasons cited include getting burned out or retirement.<\/span><\/p>\n

About a quarter of companies intend to use automation to make working conditions bearable. But how does automated data extraction reduce the burden for AP and accounting teams?<\/span><\/p>\n

Smart Invoice OCR – A Quick Overview<\/b><\/h2>\n

Smart technologies use <\/span>OCR<\/span><\/a> and Machine Learning (ML) to extract information from scanned copies of receipts.\u00a0\u00a0<\/span><\/p>\n

\u00a0Extracting data from invoices may not be the most glamorous application of artificial intelligence, but it brings significant changes to business operations.\u00a0<\/span><\/p>\n

Companies can reduce hours spent on processing invoices by 30 to 40% – even with the most rudimentary AI techniques. <\/span>[2]<\/span><\/p>\n

Today, most expense management solutions are accessible through a website and a smartphone app.<\/span><\/p>\n

Envoice, for instance, allows users to upload PDFs or images containing invoice data through the website or send the attachment to a dedicated email address. Meanwhile, app users can take a photo of the receipt with the app.<\/span><\/p>\n

Technologies like automated invoice processing use AI to learn from human experience but it’s ultimately up to the user to make decisions.<\/span><\/p>\n

As teams move beyond basic data capture, they often start looking at how AI can support the full invoice lifecycle, from extraction through to checks and approvals. That is where ai invoice processing<\/a> becomes useful, combining smart data capture with automated validation and routing rules. Understanding how these tools work together helps finance leaders choose solutions that genuinely reduce manual effort rather than just shifting it around.<\/p>\n

Bots read information from an invoice line item and identify data automatically even if invoice layouts vary from one supplier to another. However, companies can still add human review to achieve even higher accuracy rates.<\/span><\/p>\n

OCR technologies also have an advantage over manual invoice processing since AI can handle receipts in multiple languages. Even if a receipt is not in a language you\u2019re familiar with, you can still map information to the correct field.<\/span><\/p>\n

Reducing time spent entering data or translating information from a foreign invoice frees up significant time for accounting and AP teams. More importantly, it solves some of the biggest pain points in a manual AP environment.<\/span><\/p>\n

How Does Manual Data Processing Hurt Your Business?<\/b><\/h3>\n

Entering invoices manually creates various problems for businesses. Here are some examples.<\/span><\/p>\n

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High error rates<\/b><\/h4>\n

Manual data entry is prone to errors. A survey finds that 47% of organizations encountered data entry errors for non-payroll expenses. Executives who participated in the study consider data entry mistakes as the most important challenge for their firm.<\/span><\/p>\n

Data entry mistakes can lead to problems like paying the incorrect vendor, issuing a check that is higher or lower than the invoice amount, and issuing duplicate payments. Fixing a mistake and identifying the cause can be time-consuming, especially for AP who already have too much on their plate.<\/span><\/p>\n

Higher Compliance Costs<\/b><\/h4>\n

Human errors increase inaccuracies in the information entered manually. Companies compensate by putting internal controls such as requiring employees to review invoices one by one to validate costs and ensure that information like invoice amount and payee are correct.<\/span><\/p>\n

To compensate for higher risk, companies spend money to perform transactional activities and make sure they’re correct. Accounting talent who may have contributed more to creating business strategies now perform manual verification to catch mistakes – a task that AI can do in less time.<\/span><\/p>\n

Time-consuming Process That requires a lot of Labor Hours<\/b><\/h4>\n

Invoices that take too long to approve have been one of the biggest pain points for companies. Creating a way to speed up the first step in the process – entering data into the system – gives companies a head start. With AI, invoice data extraction happens in seconds. Dealing with high-volume invoices and peak periods becomes more manageable since your accounting team needs to do less manual work.<\/span><\/p>\n

Strained Supplier Relationships<\/b><\/h4>\n

In manual AP environments, long invoice processing times are a common problem. Delays in getting invoice approvals lead to vendors getting paid late. As a result, your company can miss out on early payment discounts or worse pay penalties and late fees. Paying late can also cause friction with vendors, especially when they need to make constant follow-ups to receive payments.<\/span><\/p>\n

Increases Employee Attrition Rates<\/b><\/h4>\n
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AP employees feel tired, frustrated, and depressed about having too much work to do. Dealing with vendor queries and hunting for information on top of all the data entry work can demoralize employees. Companies that are not doing anything to ease the burden on their AP staff run the risk of losing people which can lead to issues in managing the AP function.<\/span><\/p>\n

Why Do Companies Still Extract Invoice Data Manually?<\/b><\/h3>\n

Companies can reduce labor hours, increase productivity, boost employee morale, and improve insights into costs by leveraging intelligent systems. Unfortunately, many corporate leaders don\u2019t utilize AI to automate data capture.<\/span><\/p>\n

A PWC survey finds that only 28% of executives prioritize deploying AAi and machine learning to extract structured data.[2] Possible reasons for this include the following:<\/span><\/p>\n