How to Automate Data Entry in 2024 | AI Data Entry Automation

May 23, 2024
14 min

In document-heavy industries like finance, insurance, accounting, and real estate, the constant need to input data from hard copy or digital documents into systems is a major bottleneck for business operations.

Invoices, purchase orders, lease agreements – they all require human scanning, data capture, and input, often leading to errors. And that’s assuming your employees don’t miss anything or forget to input it into the system.

But with AI data entry, that’s a thing of the past. Powered by AI, data entry automation technology captures key data, extracts it, and automatically inputs necessary segments into relevant data fields in the system – a huge time-saver for employees and a money-saver for companies.

In this article, we explore how AI can revolutionize data entry processes by automating manual data entry and maintaining accuracy, precision, and efficiency for any document-heavy industry.

What is AI Data Entry Automation?

Automated data entry, also known as automated data capture, is the process of automatically collecting and inputting data into digital systems like CRM without manual intervention. This technology helps streamline repetitive tasks related to large dataset processing, reduce errors, save time, and improve productivity in data entry manual processes.

AI can automate data entry with artificial intelligence (AI) and machine learning (ML) algorithms. Using technologies like optical character recognition (OCR) data entry, natural language understanding (NLU), and natural language processing (NLP), AI data entry ensures high-quality data management and automates repetitive and time-consuming manual tasks. By integrating AI data entry tools, you can streamline your business processes and optimize workflows.

scheme showing how Ai data entry automation works

Automated data entry is versatile and can manage a wide range of data types and applications, including customer details, employee records, product information, financial transactions, and more. Due to this, data entry automation can be used in all industries that work with large amounts of data, for instance, in legal, tax, accounting, e-commerce, real estate, insurance, finance, HR, and many others.

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How Does AI Data Entry Automation Work?

AI data entry automation works by using AI algorithms to get the data from available sources and then insert it into CRM or databases. Optical Character Recognition (OCR) converts text from scanned documents into machine-readable format, while Natural Language Processing (NLP) extracts meaningful information from text to input into CRM or databases. The data is then cleansed, validated, transformed, sorted, and integrated into target systems.

Step 1. Document Upload:

The process begins with uploading the document containing the relevant data into the system or application. It may be a PDF, scanned image, handwritten notes, or other formats of collateral.

What Documents Can You Process with AI Data Entry

  • Scanned documents. With technology like Optical Character Recognition (OCR), data entry automation software can extract data from scanned documents such as invoices, receipts, agreements, forms, and contracts.
  • Digital documents. Data can be extracted from existing digital documents in various formats, including PDFs, PDFs, RTF, XLS, etc. Except for text documents, data entry automation tools can extract data from spreadsheets, presentations, or other digital sources.
  • Images. Just like with scanned documents, the OCR technology in AI data entry software will recognize and extract the structured data from the images. This can be especially useful for photographed documents, IDs, licenses, or any other visual information.
  • Emails. AI for data entry can analyze and extract data from email inbox, including attachments and text within the email body.
  • Web forms. Data entry automation tools can fill out and extract information from web forms on websites or applications. This may be helpful for businesses that use lead forms on their sites or emails along with other marketing methods, which doesn’t let you conduct the analytics accurately.
  • Audio. Similarly to OCR, AI for data entry can use speech recognition technology to transcribe spoken words from audio into text data, allowing for data entry automation from recordings such as meetings, interviews, customer calls, or dictations.
  • Video. AI data entry tools can analyze video content for data extraction using techniques like video analytics, object recognition, and text extraction from visuals. Automated data entry system can identify and extract text, numbers, or symbols displayed within the video recording.
  • Databases. Data can be retrieved from databases, either within the organization or external databases accessed through APIs.

 

 

Step 2. Data Extraction:

Next, Optical Character Recognition (OCR) technology scans the document, converting any text or images into digital format that the computer can understand. After OCR, Natural Language Processing (NLP) techniques analyze the text to understand its meaning and extract relevant information.

Overall, the technologies, used for data extraction, may be:

  • Optical Character Recognition (OCR) for text extraction. OCR converts scanned documents, images, or text into digital format, and recognizes the text from the scans. This utilization of image processing algorithms enables the data entry AI to recognize and extract characters from images and scans of physical documents like invoices, forms, or receipts.
  • Natural Language Processing for understanding human language. NLP enables the automated data entry software to recognize human language and be able to process it appropriately. NLP facilitates text data extraction, interpretation, and processing in data entry tasks.
  • Speech-to-text for audio records. Speech-to-text is required for the AI data entry automation tools that streamline the process of transcribing spoken words from audio files like video meeting recordings or messages into text data. The technology employs acoustic and language models to recognize and convert speech to structured text data.
  • Video analysis for visual data. The AI video analysis technology may involve computer vision, object recognition algorithms, and optical flow analysis for recognizing objects and text from video content. The sources of data in this case might be the recordings of presentations, tutorials, meetings, etc.

graph showing how OCR technology is used in ai data entry automation tool

Step 3. Identifying Uncertain Segments:

As the process of data extraction happens, AI data entry tools can identify uncertain elements within the analyzed document and request the user to check and correct them:

data validation in data entry automation tool

If ambiguous elements are detected, like unclear handwriting or an ink stain, the AI data entry system generates a request to the user, highlighting the specific areas that require validation, and the user inserts the right information.

Such an approach not only improves the accuracy of data entry but also ensures that potential errors or inconsistencies are addressed promptly, leading to more reliable and accurate data processing outcomes.

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Step 4. Data Validation:

The extracted data is validated to ensure accuracy and consistency. Validation rules and algorithms are applied to identify and correct errors, missing information, or inconsistencies in the data. The validation process may also be conducted by the human operator after the previous step of identifying inconsistencies.

the list of documents avaiting for approval in an AI data entry automation tool

 

Step 5. Data Transformation:

After the data is validated and the errors and inconsistencies are corrected, the data may undergo transformation processes such as formatting, standardization, or cleaning to ensure uniformity and compatibility with target systems. This is an important step of AI for data entry, as it will define all the further processes of data entry into the CRM system.

Step 6. Data Export into CRM

The processed, standardized, and validated data is integrated into desired CRM systems, business databases, or any other applications. AI automated data entry frameworks may be integrated with existing software for data input, of the prepared data may be downloaded for any further use in convenient formats, like XLS, PDF, or others.

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Is Manual Or Automated Data Entry Better?

 

Manual vs Automated data entry

Unlike AI data entry, manual data entry is a more traditional way of inputting information into computer systems like databases. Manual data entry involves an employee – a data entry operator, who reads the information from physical documents and then types it into digital forms, spreadsheets, CRMs, or databases. Then, the manually entered data is sorted, and organized, and may be stored on servers, hard drives, or cloud platforms.

Making the correct choice between manual data entry and automated or AI data entry is crucial for businesses, as it will significantly impact operational efficiency and data management processes in the future.

Let’s compare aspects of manual and automated data entry to understand each approach’s strengths and limitations. This will help make an informed choice which will optimize data entry processes and enhance overall productivity.

Benefits of AI Data Entry Automation

AspectManual Data EntryAutomated (AI) Data Entry
Speed Relatively slow, prone to human errors and delays Fast data input, significantly shorter processing time
Accuracy Higher chance of errors due to human inputBetter accuracy provided that the AI is trained properly
Cost Cheaper at the beginning, but has higher operational cost in the long run, since it is more labor-intensive and takes more employees’ timeLower cost in the long run, but requires significant initial investment in AI at the beginning
Scalability Limited scalability due to reliance on human resources; requires qualified staff and finances for upscalingEasily scalable, as automated data entry is capable of handling large volumes of data
Integration with Systems Requires manual effort for integrationRequires manual effort for integration at the beginning
Learning and Adaptation Requires training and supervision by a more proficient employee Can learn and adapt over time, improving accuracy
Data Complexity May struggle with complex data formats or structuresHandles diverse data types and structures
Changes in Operations Needs little change or adaptation, requires extra trainingNeeds a lot of adaptation and change in the structure, software, and training
Compliance Regulation Depends on the quality of employee’s training and knowledge, may be susceptible to errorsHas minimum likelihood of compliance issues if trained properly

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Applications of AI Data Entry

Who Must Know How to Automate Data Entry?

AI data automation tool will be the most beneficial for the big companies which handle large amounts of various documents and types of data and daily process the data, manage it, and work with the CRM or other types of databases.

How to Automate Data Entry in Different Industries?

Data entry automation is a versatile technology that can be applied successfully in any industry that involves extensive work with documents or handling big amounts of data. However, there are industries where it might seem the most effective.

application of AI Data entry in different industries

Finance and Accounting Data Entry Automation

Tasks performed by AI data entry tool:

  • Automated extraction of financial data from documentation.
  • AI-powered reconciliation of bank statements, credit card transactions, and accounting entries.
  • Data entry automation for payroll processing, tax filing, and financial reporting.
  • Automated insertion of data into the database or Excel for further calculations.

Documents processed:

  • Invoices;
  • Receipts;
  • Expense reports;
  • Balance sheets;
  • Cash-flow statements;
  • Tax returns;
  • Income statements;
  • Document scans.

Results:

  • Better accuracy due to a lower chance of human error;
  • Higher efficiency in processing the documents and therefore completing transactions;
  • Documents are always ready before the deadline;
  • Fewer employees are required for data entry tasks.

Healthcare Data Entry Automation

Tasks of AI data entry automation tool:

  • Extraction of patient data from medical records.
  • Automated entry of billing information, insurance claims, and reimbursement requests.
  • AI data entry for electronic health records (EHRs), patient management systems, and medical billing software.

Documents processed:

  • Medical records;
  • Prescriptions;
  • Test results;
  • Insurance policies;
  • Invoices;
  • Lab reports;
  • Patient IDs.

Results:

  • Easier and faster medical record management;
  • Increased accuracy and lower chance of mixed-up results;
  • Streamlined billing and insurance claim processing;
  • Improved patient care and compliance with healthcare regulations.

Retail and E-commerce Data Entry Automation

Tasks performed by automated data entry tool:

  • Data extraction from product catalogs, sales orders, and customer invoices.
  • Automated entry of inventory data, pricing information, and product descriptions.
  • Automated data entry for order fulfillment, shipping logistics, and customer support systems.

Documents processed:

  • Customer invoices;
  • Receipts;
  • Order confirmation emails;
  • Product descriptions;
  • Catalogs;
  • Sales orders;
  • Feedback forms and surveys.

Results:

  • Efficient management of product data and pricing;
  • Faster order processing, fulfillment, and delivery;
  • Improved customer satisfaction;
  • Better inventory control and supply chain management.

Real Estate Data Entry Automation

Tasks of automated data entry software:

  • Extraction of property details from listings, contracts, and rental agreements.
  • Automated entry of tenant information, lease terms, and property management data.
  • Data entry automation for real estate CRM systems, property databases, and rental marketplaces.

Documents processed:

  • Lease agreements;
  • Sale contracts;
  • Leads emails;
  • Scanned IDs of tenants and landlords;
  • Maintenance invoices;
  • Property deeds;
  • Closing disclosure agreements;
  • Property inspection reports;
  • Mortgage records;
  • Lien releases.

Results:

  • Streamlined real estate processes;
  • Improved accuracy in property-related operations;
  • Faster handling of required documents and shorter time of deal closing;
  • Enhanced customer service and responsiveness to client inquiries.

 

 

Legal Industries

Tasks of automated data entry tool:

  • Extraction of case details from legal documents, court records, and contracts.
  • Automated entry of client information, case updates, and billing records.
  • AI data entry into legal practice management software, document management systems, and compliance reporting.

Documents processed:

  • Contracts;
  • Agreements;
  • Wills;
  • Testaments;
  • Trusts;
  • Deeds;
  • Court pleadings;
  • Legal briefs;
  • Power of attorney;
  • Non-disclosure agreements.

Results:

  • Increased efficiency in case management;
  • Faster legal document processing;
  • Faster client onboarding, billing, and compliance reporting;
  • Improved accuracy in legal data entry and documentation.

Human Resources Management with Automated Data Entry

 

Tasks of data entry automation tools:

  • Extraction of employee data from resumes, job applications, and HR documents.
  • Automated entry of payroll information, performance reviews, and employee benefits.
  • Data entry automation for HRIS (Human Resources Information System), onboarding platforms, and workforce management tools.

Documents processed:

  • Employment contracts;
  • Employee forms;
  • Job applications;
  • Job offers;
  • Termination letters;
  • IRS documents;
  • Payroll records.

Results:

  • Automated employee data management, including HR documents and payroll;
  • Better compliance with HR regulations;
  • Faster employee onboarding and other HR-related processes;
  • Enhanced workforce management and employee engagement.

Logistics

 

Tasks:

  • Extraction of logistics data from shipping documents and invoices.
  • Automated entry of the information into the tracking system and CRM.
  • Validating and converting the data into easily trackable and stored formats.

Documents processed:

  • Invoices
  • Shipping documents;
  • Supplier contracts;
  • Delivery details;
  • Customs documentation;
  • Purchase orders;
  • Inventory records.

Results:

  • Increased accuracy in logistics operations due to reduced manual errors.
  • Faster processing of the orders and significantly shorter delivery lead time.
  • Reduced personnel costs and fewer labor-intensive tasks for employees.
  • Better customer experience and increased customer loyalty.

Save Time on Data Input into CRM with AI Data Entry Automation

AI data entry software is a game-changer for businesses managing extensive datasets in CRM systems. One of the best things about AI data entry automation tools in this context is their ability not just to extract data from documents but also to autonomously insert it into the CRM, saving countless hours of manual data entry.

AI data entry systems can accurately interpret and extract pertinent information from diverse documents like contracts, invoices, and forms. The data extracted may include customer details, transaction records, product information, and more. Data entry automation can streamline the entire data input process, eliminating the need for human intervention. This not only reduces the risk of errors but also significantly accelerates the speed at which data is processed and updated in the CRM.

Additionally, automated data entry systems can validate and standardize the extracted data against predefined criteria, ensuring accuracy, readability, and convenience in handling the data. The integration with CRM enables real-time updates, keeping customer profiles, sales records, and other vital information current and consistent.

This scalability and efficiency make AI data entry solutions a perfect solution for businesses aiming to optimize their CRM operations, improve productivity, and enhance decision-making.

Why Implement a Custom AI Data Entry Tool?

Implementing custom AI data entry automation software offers multiple advantages for large organizations with huge document workflows. A data entry automation tool can replace manual data entry and offers tailored solutions, improved accuracy, integration with existing software, cost-effectiveness, scalability, competitive advantage, and innovation opportunities, making it a strategic investment for businesses with specific data entry needs.

  • Tailored to the types of documents in your business. If your company deals with specialized or unique data sources that require specific data extraction and processing techniques, a custom automated data entry tool can be designed to handle this effectively.
  • Fits the industry-specifics. Different industries have varying data entry requirements and compliance standards. A custom data entry AI tool can be developed to align with industry-specific regulations and standards, ensuring accurate and compliant data processing.
  • Fully suits your needs. Industry-specific AI data entry automation tools utilize AI engines trained on industry-native data sets. This means the AI software fits your specific needs perfectly, just like an employee with 10-year experience in the industry. Moreover, if you want to enter the data into your CRM system or other databases, your data entry AI should be custom; otherwise, it will not understand and may not have permission to input data into the correct fields.
  • Easily integrates with existing systems. Custom automated data entry software can be integrated with your existing software, CRM platforms, or databases. This integration ensures smooth data flow and eliminates any compatibility issues, which often occur if you use a ready-made subscription-based solution.
  • Cost-effective and beneficial. While custom AI development may involve an initial investment, it will then lead to long-term cost savings by reducing manual labor costs, minimizing errors, and optimizing data processing workflows.
  • Better scalability. A custom AI data entry tool can be designed to scale according to your business growth and evolving data processing needs. This scalability ensures that the tool remains effective and efficient as your business expands.
  • Ensures your business’s competitive advantage. By leveraging a custom data entry automation solution, your business gains a competitive edge through faster data processing, improved data quality, and enhanced operational efficiency. The result is better decision-making and higher customer satisfaction.

Ascendix – an Expert in AI Data Entry Automation

Ascendix is an AI pioneer in software development, which combines deep knowledge of modern technology with expertise in real estate. We have established unique and substantial experience in fostering transformative change with the help of AI-driven software for different industries. Moreover, we have built custom AI software ourselves for data entry in various industries, which gave us significant practical experience in building frameworks for AI search, lease abstraction tools, AI recommendations, and other advanced software.

Why choose Ascendix as your partner to automate data entry?

  • Extensive expertise in software development. With more than two decades of experience, we have developed software solutions for big enterprises and small startups, delivering high-quality and tailored tools for various industries – from real estate to logistics.
  • Collaborating with major players in the real estate industry. Companies like JLL and Colliers entrust developing in-house software solutions to us, together with more than 300 other clients worldwide.
  • International outreach. With 5 offices around the globe, we outsource from Europe and work with the US market, which provides your business with a huge diversity of skills, being connected 24/7, and incorporating knowledge of international trends and demand into your solution.

How Ascendix can help you in AI data entry automation:

  • Custom software development. We can build a custom AI data entry automation tool tailored to your business needs.
  • Integration of existing or custom solutions. If you have an existing solution in mind, that you would like to integrate into your software, we can do this for you, developing and optimizing all the features and customizing the solution for you.
  • Consultancy. We can help you choose the most suitable AI solution, suitable for your business needs.
  • Technical audit. The Ascendix team can perform the audit of your existing AI tool, if you are using one, and improve it with the help of artificial intelligence or other features per your request.

Hire Ascendix and get rid of manual data entry forever with your tailored AI data entry automation software. Schedule the free consultation today and investigate how to automate data entry with us.

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How to use AI for data entry?

To use AI for data entry, start by identifying the types of data you work with, such as documents, forms, or emails. Then, develop an AI data entry tool, ensuring it has the required capabilities, such as natural language processing (NLP), machine learning (ML), and optical character recognition (OCR). Train the AI model and integrate the AI tool with your existing systems, such as CRM or database platforms, to automate data entry. This way, AI data entry tool will be tailored for your business needs and will work effectively and efficiently.

Can AI do data entry?

Yes, AI can perform data entry tasks. AI data entry automation systems use natural language processing, machine learning, and optical character recognition to extract information from documents, forms, emails, and images. The system then inputs the data into databases, CRM systems, or other software platforms automatically, replacing manual data entry and improving accuracy and efficiency.

Will data entry jobs be replaced by AI?

While AI can automate manual data entry tasks, it will not fully replace data entry jobs. Instead, AI is more likely to streamline them by handling repetitive and routine data entry tasks. Human oversight and decision-making will still be required for handling exceptions, ensuring data quality, checking the inserted information, and interpreting nuanced information that AI may struggle with. While AI will transform the data entry processes, it’s more about reshaping the industry tasks than replacing data entry jobs.

Will AI replace data entry?

AI is highly likely to replace manual data entry. With the help of data entry automation software, the most repetitive tasks like inserting the data from documents into the CRM will happen automatically. However, there is yet no way how to automate data entry from hand-written or signed documents and seamlessly integrate them into the CRM. Some critical and dubious aspects of AI data processing and data entry automation must still be overseen by the human operator, who would ensure that the inserted data is right.

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