Market Summary

The global Document AI Market size was valued at USD 5.20 billion in 2025 and is projected to reach USD 28.30 billion by 2033, growing at a CAGR of 24.40% from 2026 to 2033. The Document AI market is about using computer programs like Natural Language Processing and Machine Learning to look at documents. These programs can also use Optical Character Recognition and Computer Vision to find information sort documents and understand what they mean whether the documents are on a computer or on paper. The Document AI market is, about using these smart programs to work with documents. The Document AI market has solutions that help with data. This means they take text from things like invoices and contracts and emails. They turn this text into numbers and information that companies can use to make decisions. Document AI is really changing how we deal with documents in areas like money and health and law and insurance and even the government. Document AI is making a difference, in these fields by helping with document related data. Enterprises are dealing with a lot of problems because of the amount of data they have to handle how complicated it is and all the rules they have to follow. This is why the market for solutions to these problems is growing fast.

Market Size & Forecast

• 2025 Market Size: USD 5.20 Billion
• 2033 Projected Market Size: USD 28.30 Billion
• CAGR (2026-2033): 23.40%
• North America: Largest Market in 2026
• Asia Pacific: Fastest Growing Market

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Key Market Trends Analysis

• Lots of companies are now using document processing. This means they are using intelligence to do tasks that people used to do by hand when dealing with documents. The goal is to save time and reduce mistakes that people might make. Intelligent document processing helps with things like getting information out of documents putting documents into categories and checking to make sure documents are correct. Organizations are using document processing to automate these tasks. Intelligent document processing is very useful, for extraction, categorization, and validation of documents.
• The integration of natural language processing and machine learning tools is really cool. These tools help Document AI understand what people are saying when they write something. Research on natural language processing and machine learning has come a way. This means Document AI is now better at figuring out what words mean and how they relate to each other even when people write in a way that is not very organized. Natural language processing and machine learning are important for Document AI to understand text and the meaning, behind the words.
• People are moving to cloud-based Artificial Intelligence solutions. The thing is, more and more companies are using the cloud for Document Artificial Intelligence solutions. This is because the cloud is better, for making things bigger or smaller as needed it is cheaper.
• There is a need for Document AI in many areas. Important areas like banking, insurance, health, law and the government are starting to use Document AI technology. They want to use it to make customer onboarding better handle claims and manage documents. The use of Document AI technology is becoming very important in these areas, such as banking, insurance, health, law and the government to help with things like customer onboarding and document record management, for Document AI.

In conclusion, the market for Document AI is really taking off because companies need to automate tasks that involve a lot of documents. Companies are using document processing to get things done faster and with fewer mistakes. This helps with things like pulling out information from documents putting them into categories and checking if they are correct. Document AI is getting better at understanding texts because of advances, in Natural Language Processing and Machine Learning.

At the time more companies are moving to the cloud, which makes it easier to scale up and saves money so even more companies are starting to use Document AI. Notably, these factors are positioning Document AI as a strategic enabler of the digital transformation journey in banking, insurance, healthcare, legal, and the government.

Document AI Market Segmentation

By Document Type

• Structured

Structured documents have standardized formats like forms, invoices, and purchase orders, which have well-defined data fields. This data gets processed by the document AI service with ease, making automation very efficient, with faster results, in sectors such as finance.

• Unstructured

Unstructured documents, such as email, contract, reports, and text documents, lack a defined structure. Document AI uses NLP and ML to extract meaning and insights. This market is a major game-changer because of the application of Document AI.

• Semi- structured

Semi-structured documents mix the benefits of fixed documents with the use of free text such as bills, applications, and insurance claims. The technology benefits companies by recognizing patterns and adjusting for document formatting variations.

• Multimodal / Mixed Content

In multimodal documents like text, pictures, tables, handwriting, or scan documents are incorporated within a single file. The usage of Advanced Document AI involves the use of OCR, computer vision, as well as NLP processes.

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By Application

• BFSI

The BFSI segment is the heaviest user of Document AI as there is a massive volume of documents such as loan requests, KYC documentation, claims data, as well as financial statements. It assists with automating processing such as data extraction, fraud analysis, and customer onboarding.

• Healthcare & Life Sciences

Healthcare providers rely on the use of Document AI in processing medical files, health insurance claims, prescriptions, and clinical trial documents. This enhances precision and documentation compliance with regulatory requirements.

• Government & Public Sector

The government sector uses the Document AI for the digitization of documents, handling citizen documents, and performing various paper works such as taxation, licensing, and social services.

• Retail & E-Commerce

Retail & E-Commerce Online shopping and retail companies use Document AI for document management in the areas of invoices, the supply chain, contracts, and consumer communication. Document AI assists in improving the accuracy of orders and the processing time of orders.

• Others

For other industries such as the legal sector, education, manufacturing, logistics, the uses of Document AI include contracts, classification, and document management. Due to the rise in digital transformation, the adoption of Document AI will keep increasing.

Regional Insights

North America is the place for Document AI technology. This is because people there started using intelligence early on. Also, huge companies are also trying to change the way they do things by using technology. There is a lot of demand for Document AI from areas like banking, healthcare, and the government. It is also easy for companies to use Document AI because they have internet connections and can find people who are good at artificial intelligence. The rules and regulations, in North America also make it easy for companies of all sizes to start using Document AI solutions.

Europe is a significant contributor to the market share of the global Document AI market due to the presence of high digitalization drives among enterprises and public sector organizations. Countries such as the UK, Germany, and France will invest in AI-powered document processing to create operational efficiencies, compliance, and customer experiences, particularly in regulated industries.

The fastest growth, meanwhile, is expected to take place in the Asia Pacific region, powered by rapid digital transformation, expanding use of AI technologies, and high demand for automated document workflows in emerging economies such as China, India, Japan, and South Korea. Growth in cloud computing, increasing enterprise IT spending, and government initiatives for modernization of public services are key contributors.

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Recent Development News

• In November 2025, Google expanded its Document AI capabilities by releasing general availability support for layout parsing of DOCX, PPTX, XLSX, and XLSM files. This enhancement improves extraction of paragraphs, tables, and structural elements, enabling better contextual understanding for AI applications. Additionally, Google deprecated its Human-in-the-Loop feature, signaling a shift toward more automated processes.

Source:https://docs.cloud.google.com/document-ai/docs/release-notes

• In September 2025, SAP launched SAP Document AI, a business solution focused on automating document data extraction and workflow integration across SAP applications. The Document Type promises improved accuracy and reduced manual effort, with plans to expand integration options later this year.

Source:https://www.sap.com/Document Types/artificial-intelligence/ai-foundation-os/document-ai.html

Key Document AI Company Insights

With its broad portfolio-including IoT-enabled precision equipment, autonomous machinery, and data analytics platforms-Deere & Company is a clear market leader. Its global presence and significant investment in research and development allow the company to continue to innovate, providing scalable solutions for farmers that help improve operational efficiency and sustainability. Deere's ability to integrate hardware and software ecosystems provides a competitive advantage, which fosters wide diffusion across large commercial farms worldwide.

Key Document AI Companies:

• Google
• Microsoft
• SAP
• Appian
• IBM
• ORACLE
• ADOBE
• EDGEVERVE SYSTEMS (INFOSYS)
• AWS
• UIPATH
• EXL
• APPIAN
• OPENTEXT
• ABBYY
• AUTOMATION ANYWHERE
• AI
• ROSSUM
• TUNSTEN AUTOMATION
• HYLAND
• HYPERSCIENCE
• SALESFORCE

Global Document AI Market Report Segmentation

By Document Type

• Structured
• Unstructured
• Semi-Structured
• Multimodal/Mixed Content

By Application

• BFSI
• Healthcare & Life Sciences
• Government & Public Sector
• Retail & E-Commerce
• Others

Regional Outlook

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • Germany
  • United Kingdom
  • France
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • Australia & New Zealand
  • South Korea
  • India
  • Rest of Asia Pacific
• South America
  • Brazil
  • Argentina
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • United Arab Emirates
  • South Africa
  • Rest of the Middle East & Africa