The application of AI in word processing is becoming an inevitable trend as businesses have to handle a large volume of contracts, reports, and official documents every day. Thanks to AI applications, businesses can automate repetitive tasks, extract accurate information, and optimize workflows.

This article by 1C Vietnam will clarify the underlying technologies, practical applications, and value that AI brings to modern document management systems.

1. What are the applications of AI in word processing?

The application of AI in word processing involves integrating artificial intelligence technology into the process of reading, understanding, and processing document content, automating tasks such as recognition, classification, searching, extracting, or summarizing information quickly and accurately.

Unlike traditional methods and conventional document management software that only store, display, or search by fixed keywords, AI applications in document processing offer significant upgrades:

• How it works: Instead of simply storing documents or searching by fixed keywords, AI-powered document management systems can “understand” context and learn from processed data to analyze content, identify relationships between pieces of information, and make relevant suggestions.
• Document processing capabilities: The system can recognize characters and process various types of documents such as scanned documents, handwriting, images, PDF files, Excel spreadsheets, complex forms, or multilingual documents, instead of just processing paper documents or pre-structured files.
• Multitask automation: AI-powered word processing systems can automatically extract information, categorize by content, search by relevant or semantic keywords, answer questions, and generate summaries or translate documents directly on the platform.
• Output value: The system provides data that has been extracted, categorized, or summarized with key content, enabling users to quickly and conveniently access and utilize information.

2. Four core AI technologies used in word processing

To better understand how AI works in word processing, businesses need to grasp the following four foundational technologies:

OCR technology

OCR (Optical Character Recognition) is an optical character recognition technology that allows the conversion of text from paper documents, scanned PDFs, images, or handwriting into digital data that can be edited and searched on a system.

In businesses, OCR technology is often used for:

• Digitizing administrative paper documents such as contracts, official letters, invoices, certificates, etc.
• Extracting important information for managing and processing tasks on the system.
• Automatically fill in information on forms instead of manually entering it.

Optical Character Recognition (OCR) technology is capable of quickly and accurately recognizing document characters, with an accuracy rate of up to 98%. When integrated with advanced AI technology, the system not only recognizes text but also understands document structure and identifies the location of data fields such as contract numbers, signing dates, payment values, and partner names. This makes the processing of contracts, invoices, and administrative documents faster and more consistent.

NLP technology

NLP (Natural Language Processing) is a branch of AI specializing in processing and understanding human language. While OCR helps systems "read" text, NLP helps them "understand" the meaning and context of that content. This is a crucial foundation for AI to not only extract data but also analyze, classify, and process information contextually.

In document processing, NLP technology allows the system to:

• Identify the document's topic.
• Semantic analysis of content.
• Extract entities such as person's name, organization, validity period, and payment value.
• It helps in searching for and answering questions based on the content.

For example, instead of searching by exact keywords, users could ask a question like: "Find a contract worth 5 billion VND signed in Q1," and the system would still understand and return relevant results. This is a significant step forward in the application of AI to process text more accurately and efficiently.

Machine Learning Technology

Machine learning (ML) is a technology that allows systems to learn from historical data to improve accuracy over time without needing to reprogram.

In word processing, Machine Learning is applied to:

• Automatic document classification: distinguish between contracts, invoices, purchase orders, reports, etc., based on content and structure.
• Predictions and suggestions: suggest ways to categorize documents or assign responsible personnel, and predict appropriate approval flows based on history.
• Anomaly detection: identifying documents containing unusual content or information that require closer examination.

For example, if the system records contracts over 10 billion VND that typically require 5 levels of approval, AI can automatically suggest the corresponding approval process as soon as the document is created. Thanks to this, AI applications not only process documents but also optimize workflows.

Generative AI (Gen AI) technology

Generative AI (Gen AI) is a technology capable of generating new content based on input data. With the explosion of large language models like GPT and Claude, Gen AI opens up unprecedented possibilities in text processing.

Common Gen AI applications in word processing include:

• AI Chatbot: An AI application that allows users to ask and answer questions directly from attached documents.
• AI Summary: Summarizes text into key points, saving reading comprehension time.
• AI Translation: Translate multilingual documents directly within the system without needing to send files externally, ensuring data security.

These are the technologies that are rapidly developing within electronic office systems.

3. Tasks involving the application of AI in word processing.

Below are some common tasks where AI is applied in the daily document processing workflow of businesses:

Automatically extract and process text data.

If information from contracts, payment proposals, invoices, and personnel records still has to be manually entered into the system, the processing procedures are prone to errors and delays, especially in the reconciliation, payment, or approval stages.

AI applications enable systems to automatically identify and extract important data fields and directly transfer them to the document processing workflow. For example:

• Contract extraction: identifying key terms such as contract duration, value, payment terms, penalty clauses, termination clauses, etc.
• Invoice extraction: AI automatically identifies invoice number, issue date, supplier name, tax code, list of goods, unit price, total amount, VAT, gross amount, etc.
• Extract candidate CVs: automatically retrieve information such as name, date of birth, education level, work experience, skills, etc.

As a result, data is standardized right from the input stage, reducing errors and speeding up document processing between departments.

Search and retrieve text by semantics.

Searching by fixed keywords often yields limited results, especially when users don't remember the exact phrase used in the document. This makes information retrieval time-consuming and dependent on how the document is named.

AI applications allow systems to understand the meaning behind a question and find relevant results, even if the document doesn't contain the exact keyword. For example:

• When a user searches for "termination process," the system returns documents related to "termination of employment contract" or "job handover regulations."
• When a user searches for "contracts related to international freight transportation," the system will return logistics contracts, import/export contracts, or agreements with shipping agents.

This feature is particularly useful when new employees unfamiliar with internal terminology can still find the right document, or when users need to find related information but don't remember the exact keywords.

According to McKinsey research, semantic search can improve the accuracy of search results by approximately 40–60% compared to traditional keyword search, and reduce search time by up to 35%.

Summary of the text

Long documents such as contracts, project reports, or investment plans often contain a lot of important information but are time-consuming to read in their entirety. AI-powered text summarization applications can automatically generate comprehensive summaries of key points based on predefined structures.

Typical use cases include:

• Summarizing long reports: An 80-page market research report can be summarized by AI into a 2-3 page overview, highlighting key insights, main figures, and action recommendations.
• Meeting Minutes Summary: From the full transcript of the 2-hour meeting, AI generates a concise summary of the issues discussed, decisions reached, and next steps.

This is one of the most time-saving applications for employees and management.

Translation and multilingual support

For businesses with international operations or working with foreign partners, language processing often requires the use of third-party online translation tools. This disrupts processes and poses potential security risks.

AI enables direct translation of contextually and culturally relevant content to produce natural and accurate translations right within the system. This is especially important for sensitive documents such as contracts, financial reports, or customer information. Application scenarios:

• Contract and legal document translation: Translate contracts and agreements from English to Vietnamese (or vice versa) so that all parties involved clearly understand the content.
• Translating emails or business correspondence: Employees can write emails in Vietnamese, AI translates them into English for international partners, and translates the reply emails back – all seamlessly within the system.
• Translation of training materials: Multinational companies can quickly translate training materials, work procedures, and company policies into multiple languages for consistent application across branches.

As a result, the document processing workflow remains seamless, ensuring internal data security, shortening processing time, and supporting rapid decision-making in an international collaborative environment.

4. Benefits of businesses applying AI in word processing

The application of AI in word processing brings benefits to leaders, employees, and businesses, including:

• Enhancing decision-making capabilities: AI applications help retrieve, synthesize, and summarize information in a timely manner, enabling leaders to quickly grasp contract information, reports, or proposals.
• Enhanced operational control: Data is standardized and tracked throughout the document processing process, enabling management to monitor progress, responsibilities, and work status transparently and clearly.
• Reducing operational errors and risks: AI-powered systems automatically extract and process data, minimizing mistakes in payments, contract signing, or record management, thereby reducing financial and legal risks.
• Improve team productivity: By automating repetitive tasks, employees can focus on their core work instead of handling manual paperwork.
• Optimizing costs and resources: When processing and approval times are shortened, businesses respond faster, avoid delays due to internal processes, reduce overhead costs, and free up resources for the team to focus on higher-value tasks.

5. 1C:Document Management Digital Office Solution applies AI in document processing and workflow.

With over 30 years of experience implementing solutions for major domestic and international corporations, 1C Vietnam proudly introduces the 1C:Document Management Digital Office Solution , integrating advanced AI technology to automate and optimize document processing workflows. This solution is particularly suitable for organizations with multiple branches, departments, approval levels, and stringent control requirements.

Key AI application features of 1C:Document Management:

• Integrated OCR: Automatically recognizes and extracts information from paper documents, scanned PDFs, and images; supports rapid digitization and reduces manual data entry.
• AI Summary: Automatically summarizes the content of contracts, reports, or meeting minutes based on integrated AI models, allowing users to choose a summary style that suits the management and decision-making goals of each department and role.
• AI Translation: Directly translates multilingual documents within the system, minimizing the use of external tools and ensuring data security.
• AI Chatbot: allows users to ask questions and look up information from attached documents, supporting quick information retrieval and accurate decision-making.

In addition to AI, the system also manages documents centrally, automates approval processes, integrates digital signatures, and provides multi-dimensional reporting, helping businesses improve transparency, control progress, and accelerate decision-making.

Learn more about the 1C:Document Management Digital Office Solution and leave your information to effectively implement AI applications in document management and business operations today.