세계의 문서 AI 시장 : 제공 유형별(IDP, 문서 워크플로 자동화, 생성형 AI 문서 생성, ECM, 거버넌스 도구), 활용 사례별(-2030년)

The global Document AI market is anticipated to grow at a compound annual growth rate (CAGR) of 13.5% over the forecast period, from an estimated USD 14.66 billion in 2025 to USD 27.62 billion by 2030.

The market is growing as adaptive document learning models enable systems to self-improve through real-time user feedback, reducing the need for manual retraining and improving accuracy across diverse document formats. Also, graph-based document intelligence is enhancing contextual understanding by linking entities and relationships within multi-page documents, which is particularly valuable for legal, insurance, and compliance workflows. However, limited standardization of document data formats across industries continues to restrain interoperability and hinders seamless model deployment at scale.

"IDP solutions dominate the Document AI market as enterprises prioritize end-to-end automation and compliance-ready data processing"

Intelligent Document Processing (IDP) solutions are projected to hold the largest market share in the Document AI market, driven by their ability to deliver complete automation across unstructured and semi-structured document workflows. IDP platforms integrate OCR, NLP, and machine learning to extract, classify, and validate data from invoices, forms, contracts, and compliance documents with high accuracy. Enterprises in sectors such as banking, insurance, and healthcare are adopting IDP to accelerate document turnaround times, reduce manual data entry, and maintain audit-ready digital records. The rapid expansion of remote operations and paperless initiatives has further increased demand for cloud-based IDP platforms. Vendors like UiPath, ABBYY, and Kofax are enhancing IDP solutions with generative AI, RPA integration, and pre-trained models for specific domains, enabling faster deployments and higher ROI. Additionally, the growing need for explainable AI and data lineage capabilities aligns with regulatory compliance requirements, reinforcing IDP's position as the preferred foundation for enterprise-scale document automation.

"Unstructured documents lead the Document AI market as enterprises automate complex, high-volume content processing"

Unstructured document types are expected to hold the largest market share in the Document AI market, reflecting the growing need to process emails, contracts, reports, handwritten notes, and multimedia-rich records that lack fixed templates. Across industries such as banking, healthcare, and government, most enterprise data remains unstructured, creating a significant demand for advanced AI models capable of understanding variable document formats. Recent advancements in layout-aware transformers, multimodal AI, and natural language understanding are allowing Document AI systems to accurately extract contextual information from text, tables, and images simultaneously. Vendors like Google, Microsoft, and AWS have expanded their solutions to handle multi-format documents using pre-trained models fine-tuned for specific industries. The adoption of unstructured document processing is also being accelerated by compliance-driven automation and data governance requirements, particularly for audit trails and customer communications. As enterprises focus on digitizing legacy archives and enabling searchable document repositories, unstructured document intelligence has become central to driving efficiency, improving decision-making, and ensuring regulatory transparency across large-scale digital ecosystems.

"Asia Pacific to witness rapid growth fueled by innovation and evolving strategies, while North America leads in market size"

The Document AI market exhibits strong regional differences, with the Asia Pacific region predicted to grow the fastest due to the rapid digital transformation in countries such as India, Indonesia, and Vietnam, supported by initiatives like Digital India and Japan's Society 5.0. Businesses are increasingly investing in cloud-based Document AI and IDP solutions to automate workflows in BFSI, healthcare, logistics, and government, driven by the need for multilingual OCR and natural language processing capabilities. The rise of fintech, digital payments, and e-governance is also driving the need for document automation in compliance, onboarding, and identity verification. Meanwhile, North America is expected to lead in 2025, thanks to its advanced infrastructure, early adoption, and vendors such as Google, Microsoft, AWS, IBM, and Adobe. Strict regulations, such as HIPAA, SOX, and GDPR, are driving the adoption of AI-driven compliance and audit solutions, particularly in the finance, insurance, and healthcare sectors, which utilize AI for classification, contract analysis, and claims processing. The integration of generative AI, RAG, and explainability models enhances document accuracy and understanding. Thus, North America's innovation and Asia Pacific's digital growth are jointly shaping the global Document AI landscape, driving market expansion.

Breakdown of primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the market.

• By Company: Tier I - 33%, Tier II - 44%, and Tier III - 23%
• By Designation: Directors - 36%, Managers - 41%, and others - 23%
• By Region: North America - 39%, Europe - 18%, Asia Pacific - 32%, Middle East & Africa - 4%, and Latin America - 7%

The report includes the study of key players offering solutions and services. It profiles major vendors in the Document AI market. The major players in the Document AI market include Google (US), Microsoft (US), SAP (Germany), IBM (US), AWS (US), Oracle (US), Adobe (US), ABBYY (US), Automation Anywhere (US), UiPath (US), Appian (US), H2O.ai (US), EdgeVerve (India), Super.ai (US), Rossum (UK), Tungsten Automation (US), OpenText (Canada), Hyland (US), Hyperscience (US), EXL (US), Snowflake (US), Salesforce (US), Grooper (US), DocDigitizer (US), Cinnamon (Japan), Docugami (US), Mistral AI (France), Upstage (US), DocByte (Belgium), Infrrd (US), Docketry (US), OpenAI (US), Gamma (US), AidocMaker (US), Anthropic (US), Checkbox (US), Docubee (US), DocuPilot (US), Docsumo (US), Formstack (US), HyperWrite (US), Lindy (US), QuillBot (US), and Scribe (US).

Research coverage

This research report covers the Document AI market, which has been segmented by offering, document type, use cases, and vertical. The offering segment is split into solutions and services. The solutions segment is further split into IDP, Document Workflow Automation, Generative AI Document Generation, and ECM & Governance Tools. Services are segmented into professional and managed services. The market, by document type, includes structured, unstructured, semi-structured, and multimodal/mixed content. Use cases include finance & accounting, legal & compliance, customer service, marketing & sales, HR, and supply chain & logistics. The verticals covered are BFSI, healthcare & life sciences, government & public sector, retail & e-commerce, manufacturing, energy & utilities, telecommunications, transportation & logistics, education, and other verticals. The regional analysis covers North America, Europe, Asia Pacific, the Middle East & Africa (MEA), and Latin America.

Key Benefits of Buying the Report

The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the market's pulse and provides information on key market drivers, restraints, challenges, and opportunities.

The report provides insights into the following pointers:

• Analysis of key drivers (advancements in OCR+NER fusion pipelines delivering higher precision, growth of e-signature and e-workflow ecosystems tying documents to transactions, marketplace bundling of capture tools with analytics and BI tools), restraints (cross-border data residency limits for model training and telemetry, high annotation cost for rare and long-tail templates), opportunities (synthetic-document marketplaces for niche training datasets, generative-assisted contract drafting integrated with clause libraries, auto-remediation engines that self-heal extraction errors through feedback loops), and challenges (maintaining extraction stability as templates and forms evolve, securing annotation supply chains against malicious or low-quality labels)
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches
• Market Development: Comprehensive information about lucrative markets-the report analyses the Document AI market across varied regions
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments
• Competitive Assessment: In-depth assessment of market shares, growth strategies and offerings of leading players like Google (US), Microsoft (US), SAP (Germany), IBM (US), AWS (US), Oracle (US), Adobe (US), ABBYY (US), Automation Anywhere (US), UiPath (US), Appian (US), H2O.ai (US), EdgeVerve (India), Super.ai (US), Rossum (UK), Tungsten Automation (US), OpenText (Canada), Hyland (US), Hyperscience (US), EXL (US), Snowflake (US), Salesforce (US), Grooper (US), DocDigitizer (US), Cinnamon (Japan), Docugami (US), Mistral AI (France), Upstage (US), DocByte (Belgium), Infrrd (US), Docketry (US), OpenAI (US), Gamma (US), AidocMaker (US), Anthropic (US), Checkbox (US), Docubee (US), DocuPilot (US), Docsumo (US), Formstack (US), HyperWrite (US), Lindy (US), QuillBot (US), and Scribe (US)

The report also helps stakeholders understand the pulse of the Document AI market, providing them with information on key market drivers, restraints, challenges, and opportunities.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
  • 1.2.1 INCLUSIONS AND EXCLUSIONS
• 1.3 MARKET SCOPE
  • 1.3.1 MARKET SEGMENTATION
  • 1.3.2 YEARS CONSIDERED
• 1.4 CURRENCY CONSIDERED
• 1.5 STAKEHOLDERS
• 1.6 SUMMARY OF CHANGES

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 Breakup of primary profiles
    • 2.1.2.2 Key industry insights
• 2.2 MARKET BREAKUP AND DATA TRIANGULATION
• 2.3 MARKET SIZE ESTIMATION
  • 2.3.1 TOP-DOWN APPROACH
  • 2.3.2 BOTTOM-UP APPROACH
• 2.4 MARKET FORECAST
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN DOCUMENT AI MARKET
• 4.2 DOCUMENT AI MARKET, BY SOLUTION
• 4.3 NORTH AMERICA: DOCUMENT AI MARKET, BY TOP SOLUTIONS AND DOCUMENT TYPES
• 4.4 DOCUMENT AI MARKET, BY REGION

5 MARKET OVERVIEW

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Advancements in OCR+NER fusion pipelines delivering higher precision
    • 5.2.1.2 Growth of e-signature and e-workflow ecosystems tying documents to transactions
    • 5.2.1.3 Marketplace bundling of capture tools with analytics and BI tools
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Cross-border data residency limits for model training and telemetry
    • 5.2.2.2 High annotation cost for rare and long-tail templates
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Synthetic-document marketplaces for niche training datasets
    • 5.2.3.2 Generative-assisted contract drafting integrated with clause libraries
    • 5.2.3.3 Auto-remediation engines that self-heal extraction errors through feedback loops
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Maintaining extraction stability as templates and forms evolve
    • 5.2.4.2 Securing annotation supply chains against malicious or low-quality labels
• 5.3 UNMET NEEDS AND WHITE SPACES
  • 5.3.1 UNMET NEEDS IN DOCUMENT AI MARKET
  • 5.3.2 WHITE-SPACE OPPORTUNITIES IN DOCUMENT AI MARKET
• 5.4 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES
  • 5.4.1 INTERCONNECTED MARKETS
  • 5.4.2 CROSS-SECTOR OPPORTUNITIES
• 5.5 STRATEGIC MOVES BY TIER-1/2/3 PLAYERS
  • 5.5.1 KEY MOVES AND STRATEGIC FOCUS
• 5.6 TRANSITION FROM DOCUMENT PROCESSING TO ENTERPRISE KNOWLEDGE INTELLIGENCE
• 5.7 MOVEMENT TOWARD AUTONOMOUS DOCUMENT WORKFLOWS
• 5.8 AI GOVERNANCE AND ETHICAL CONSIDERATIONS IN DOCUMENT AI ADOPTION

6 INDUSTRY TRENDS

• 6.1 PORTER'S FIVE FORCES ANALYSIS
  • 6.1.1 THREAT OF NEW ENTRANTS
  • 6.1.2 THREAT OF SUBSTITUTES
  • 6.1.3 BARGAINING POWER OF SUPPLIERS
  • 6.1.4 BARGAINING POWER OF BUYERS
  • 6.1.5 INTENSITY OF COMPETITION RIVALRY
• 6.2 SUPPLY CHAIN ANALYSIS
• 6.3 EVOLUTION OF DOCUMENT AI
• 6.4 ECOSYSTEM ANALYSIS
  • 6.4.1 INTELLIGENT DOCUMENT PROCESSING PROVIDERS
  • 6.4.2 GEN AI DOCUMENT GENERATION PROVIDERS
  • 6.4.3 DOCUMENT WORKFLOW AUTOMATION PROVIDERS
  • 6.4.4 ECM & GOVERNANCE PROVIDERS
• 6.5 PRICING ANALYSIS
  • 6.5.1 AVERAGE SELLING PRICE OF OFFERINGS, BY KEY PLAYER, 2025
  • 6.5.2 AVERAGE SELLING PRICE, BY USE CASE, 2025
• 6.6 INVESTMENT AND FUNDING SCENARIO
• 6.7 CASE STUDY ANALYSIS
  • 6.7.1 VERYFI ENABLES KOLLWITZOWEN TO PROVIDE FAIR PROMOTIONS WITH INSTANT RECEIPT VALIDATIONS
  • 6.7.2 INFRRD AI TRANSFORMS MEDTECH LEADER'S PURCHASE ORDER PROCESSING BY AUTOMATING MULTI-LANGUAGE DOCUMENTS
  • 6.7.3 DOCSUMO ACCELERATES NS TRUCKING'S DISPATCH TICKET PROCESSING BY 4X WITH AI DATA EXTRACTION
  • 6.7.4 INDICO DATA CUTS GLOBAL SPECIALTY INSURER'S SUBMISSION PROCESSING TIME TO UNDER 30 SECONDS WITH AI AUTOMATION
  • 6.7.5 ROSSUM BOOSTS VEOLIA'S INVOICE PROCESSING SPEED BY 8X WITH AI-DRIVEN WORKFLOW AUTOMATION
• 6.8 KEY CONFERENCES AND EVENTS, 2025-2026
• 6.9 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS

7 TECHNOLOGICAL ADVANCEMENTS, AI-DRIVEN IMPACT, PATENTS, INNOVATIONS, AND FUTURE APPLICATIONS

• 7.1 KEY EMERGING TECHNOLOGIES
  • 7.1.1 OCR
  • 7.1.2 NLP
  • 7.1.3 COMPUTER VISION
  • 7.1.4 NEURAL NETWORKS
  • 7.1.5 LLM
  • 7.1.6 KNOWLEDGE GRAPHS
• 7.2 COMPLEMENTARY TECHNOLOGIES
  • 7.2.1 RPA
  • 7.2.2 CLOUD COMPUTING
  • 7.2.3 DATA ANNOTATION AND LABELING
  • 7.2.4 CYBERSECURITY
  • 7.2.5 DATABASE & DATA LAKE TECHNOLOGIES
• 7.3 ADJACENT TECHNOLOGIES
  • 7.3.1 SPEECH-TO-TEXT AND VOICE RECOGNITION
  • 7.3.2 DIGITAL IDENTITY VERIFICATION
  • 7.3.3 BLOCKCHAIN
  • 7.3.4 INTERNET OF THINGS (IOT)
  • 7.3.5 AUGMENTED AND VIRTUAL REALITY (AR/VR)
• 7.4 PATENT ANALYSIS
  • 7.4.1 METHODOLOGY
  • 7.4.2 PATENTS FILED, BY DOCUMENT TYPE, 2016-2025
  • 7.4.3 INNOVATION AND PATENT APPLICATIONS
• 7.5 FUTURE APPLICATIONS

8 REGULATORY LANDSCAPE

• 8.1 REGIONAL REGULATIONS AND COMPLIANCE
  • 8.1.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 8.1.2 REGULATIONS
    • 8.1.2.1 North America
      • 8.1.2.1.1 Executive Order 14110 on Safe, Secure, and Trustworthy AI (US)
      • 8.1.2.1.2 Artificial Intelligence and Data Act-AIDA (Canada)
    • 8.1.2.2 Europe
      • 8.1.2.2.1 Europe Artificial Intelligence Act (European Union)
      • 8.1.2.2.2 General Data Protection Regulation (European Union)
      • 8.1.2.2.3 Data Protection Act 2018 (UK)
      • 8.1.2.2.4 Federal Data Protection Act (Germany)
      • 8.1.2.2.5 French Data Protection Act (France)
      • 8.1.2.2.6 Personal Data Protection Code-Legislative Decree 196/2003 (Italy)
      • 8.1.2.2.7 Organic Law 3/2018 (Spain)
      • 8.1.2.2.8 UAVG and Public-Sector Algorithm Transparency (Netherlands)
    • 8.1.2.3 Asia Pacific
      • 8.1.2.3.1 Interim Measures for the Management of Generative AI Services (China)
      • 8.1.2.3.2 Digital Personal Data Protection Act, 2023 (India)
      • 8.1.2.3.3 Act on the Protection of Personal Information (Japan)
      • 8.1.2.3.4 Basic Act on Artificial Intelligence (South Korea)
      • 8.1.2.3.5 Personal Data Protection Act (Singapore)
    • 8.1.2.4 Middle East & Africa
      • 8.1.2.4.1 Federal Decree-Law No. 45 of 2021 on the Protection of Personal Data (UAE)
      • 8.1.2.4.2 Personal Data Protection Law (KSA)
      • 8.1.2.4.3 Protection of Personal Information Act (South Africa)
      • 8.1.2.4.4 Personal Data Privacy Protection Law (Qatar)
      • 8.1.2.4.5 Law on the Protection of Personal Data No. 6698 (Turkey)
    • 8.1.2.5 Latin America
      • 8.1.2.5.1 General Data Protection Law - LGPD (Brazil)
      • 8.1.2.5.2 Federal Law on Protection of Personal Data Held by Private Parties (Mexico)
      • 8.1.2.5.3 Personal Data Protection Law No. 25,326 (Argentina)

9 CUSTOMER LANDSCAPE AND BUYER BEHAVIOR

• 9.1 DECISION-MAKING PROCESS
  • 9.1.1 STRATEGIC EVALUATION AND BUSINESS CASE ALIGNMENT
  • 9.1.2 TECHNICAL VALIDATION AND VENDOR DIFFERENTIATION
  • 9.1.3 PROCUREMENT, CHANGE MANAGEMENT, AND LONG-TERM VALUE REALIZATION
• 9.2 BUYER STAKEHOLDERS AND BUYING EVALUATION CRITERIA
  • 9.2.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 9.2.2 BUYING CRITERIA
• 9.3 ADOPTION BARRIERS AND INTERNAL CHALLENGES
• 9.4 UNMET NEEDS FROM VARIOUS END-USER VERTICALS
• 9.5 MARKET PROFITABILITY

10 DOCUMENT AI MARKET, BY OFFERING

• 10.1 INTRODUCTION
  • 10.1.1 DRIVERS: DOCUMENT AI MARKET, BY OFFERING
• 10.2 SOLUTIONS
  • 10.2.1 IDP
    • 10.2.1.1 Enabling high-accuracy extraction and automation of unstructured data
  • 10.2.2 DOCUMENT WORKFLOW AUTOMATION
    • 10.2.2.1 Bridging IDP and business operations for seamless processing
  • 10.2.3 GEN AI DOCUMENT GENERATION
    • 10.2.3.1 Redefining content creation and document authoring workflows
  • 10.2.4 ECM & GOVERNANCE TOOLS
    • 10.2.4.1 Ensuring security, compliance, and structured document management
• 10.3 SERVICES
  • 10.3.1 PROFESSIONAL SERVICES
    • 10.3.1.1 Enabling seamless implementation and strategic alignment of Document AI
    • 10.3.1.2 Consulting & advisory
    • 10.3.1.3 Deployment & integration
    • 10.3.1.4 Support & training
  • 10.3.2 MANAGED SERVICES
    • 10.3.2.1 Enabling scalable and cost-effective Document AI operations
• 10.4 DEPLOYMENT MODE
  • 10.4.1 CLOUD
    • 10.4.1.1 Accelerating time-to-value and global scalability of Document AI
  • 10.4.2 ON-PREMISES
    • 10.4.2.1 Essential for data-sensitive and regulated industries

11 DOCUMENT AI MARKET, BY DOCUMENT TYPE

• 11.1 INTRODUCTION
  • 11.1.1 DRIVERS: DOCUMENT AI MARKET, BY DOCUMENT TYPE
• 11.2 STRUCTURED
  • 11.2.1 DRIVING HIGH-VOLUME, HIGH-ACCURACY AUTOMATION AT SCALE
• 11.3 UNSTRUCTURED
  • 11.3.1 POWERING NEXT WAVE OF INTELLIGENT DOCUMENT UNDERSTANDING
• 11.4 SEMI-STRUCTURED
  • 11.4.1 BRIDGING RULE-BASED AUTOMATION AND ADAPTIVE AI MODELS
• 11.5 MULTIMODAL/MIXED CONTENT
  • 11.5.1 UNLOCKING NEW FRONTIERS IN COMPLEX DATA UNDERSTANDING

12 DOCUMENT AI MARKET, BY USE CASE

• 12.1 INTRODUCTION
  • 12.1.1 DRIVERS: DOCUMENT AI MARKET, BY USE CASE
• 12.2 FINANCE & ACCOUNTING
  • 12.2.1 INVOICES & TAX FORMS
    • 12.2.1.1 Streamlining payables with intelligent data extraction and validation
  • 12.2.2 RECEIPTS & REIMBURSEMENT CLAIMS
    • 12.2.2.1 Accelerating employee expense management through automated capture
  • 12.2.3 BANK STATEMENTS
    • 12.2.3.1 Enabling transparent financial reconciliation and anomaly detection
  • 12.2.4 FINANCIAL REPORTS & REGULATORY FILINGS
    • 12.2.4.1 Ensuring compliance and accuracy in complex disclosures
  • 12.2.5 EXPENSE FORMS
    • 12.2.5.1 Reducing manual entry and policy violations through context-aware automation
  • 12.2.6 OTHER FINANCE & ACCOUNTING USE CASES
• 12.3 HR
  • 12.3.1 RESUMES/CVS
    • 12.3.1.1 Accelerating talent acquisition with AI-driven resume intelligence
  • 12.3.2 ONBOARDING DOCUMENTS
    • 12.3.2.1 Streamlining employee onboarding with intelligent document automation
  • 12.3.3 PAYROLL
    • 12.3.3.1 Automating payroll documentation for compliance and accuracy
  • 12.3.4 POLICY DOCUMENT
    • 12.3.4.1 Enforcing policy compliance through AI-driven document governance
  • 12.3.5 OTHER HR USE CASES
• 12.4 LEGAL & COMPLIANCE
  • 12.4.1 CONTRACTS
    • 12.4.1.1 Automating contract lifecycle management for speed and risk reduction
  • 12.4.2 AGREEMENTS
    • 12.4.2.1 Streamlining agreement validation and compliance auditing through AI
  • 12.4.3 NDAS
    • 12.4.3.1 Enhancing confidentiality governance with automated NDA monitoring
  • 12.4.4 REGULATORY FILINGS
    • 12.4.4.1 Accelerating regulatory compliance through AI-enabled document intelligence
  • 12.4.5 COMPLIANCE REPORTS
    • 12.4.5.1 Ensuring continuous audit readiness with automated compliance documentation
  • 12.4.6 OTHER LEGAL & COMPLIANCE USE CASES
• 12.5 CUSTOMER SERVICE
  • 12.5.1 KYC DOCUMENTS
    • 12.5.1.1 Accelerating customer verification and compliance through AI-powered KYC automation
  • 12.5.2 CLAIM FORMS
    • 12.5.2.1 Streamlining claim processing through context-aware document understanding
  • 12.5.3 CUSTOMER FEEDBACK
    • 12.5.3.1 Turning unstructured customer feedback into actionable insights with AI
  • 12.5.4 SERVICE REQUEST
    • 12.5.4.1 Automating service request handling for faster and more personalized support
  • 12.5.5 OTHER CUSTOMER SERVICE USE CASES
• 12.6 MARKETING & SALES
  • 12.6.1 PROPOSALS
    • 12.6.1.1 Streamlining proposal creation and review with AI-powered document intelligence
  • 12.6.2 RFP RESPONSES
    • 12.6.2.1 Accelerating RFP lifecycle management with intelligent document automation
  • 12.6.3 SURVEY RESULTS
    • 12.6.3.1 Transforming customer insights from survey documents into strategic intelligence
  • 12.6.4 CAMPAIGN COLLATERAL
    • 12.6.4.1 Optimizing marketing content management with AI-driven document structuring
  • 12.6.5 OTHER MARKETING & SALES USE CASES
• 12.7 SUPPLY CHAIN & LOGISTICS
  • 12.7.1 PURCHASE ORDERS
    • 12.7.1.1 Automating procurement approvals and supplier coordination with intelligent PO processing
  • 12.7.2 DELIVERY NOTES
    • 12.7.2.1 Streamlining goods receipt and verification through automated delivery note processing
  • 12.7.3 BILLS OF LADING
    • 12.7.3.1 Ensuring shipping accuracy and regulatory compliance with intelligent bill of lading processing
  • 12.7.4 SHIPMENT MANIFESTS
    • 12.7.4.1 Enabling real-time cargo visibility and tracking with AI-enabled manifest digitization
  • 12.7.5 OTHER SUPPLY CHAIN & LOGISTICS USE CASES

13 DOCUMENT AI MARKET, BY VERTICAL

• 13.1 INTRODUCTION
  • 13.1.1 DRIVERS: DOCUMENT AI MARKET, BY VERTICAL
• 13.2 BFSI
  • 13.2.1 MODERNIZING HIGH-VOLUME FINANCIAL DOCUMENTATION WITH AI-DRIVEN PRECISION
• 13.3 TRANSPORTATION & LOGISTICS
  • 13.3.1 AUTOMATING SHIPMENT AND COMPLIANCE DOCUMENTATION FOR FASTER SUPPLY CHAIN FLOWS
• 13.4 HEALTHCARE & LIFE SCIENCES
  • 13.4.1 IMPROVING CLINICAL ACCURACY AND ADMINISTRATIVE EFFICIENCY WITH DOCUMENT AI
• 13.5 GOVERNMENT & PUBLIC SECTOR
  • 13.5.1 ACCELERATING ADMINISTRATIVE EFFICIENCY AND CITIZEN SERVICES THROUGH DOCUMENT INTELLIGENCE
• 13.6 RETAIL & E-COMMERCE
  • 13.6.1 ENHANCING TRANSACTION SPEED AND CUSTOMER EXPERIENCE WITH AUTOMATED DOCUMENT FLOWS
• 13.7 MANUFACTURING
  • 13.7.1 DRIVING PRODUCTION EFFICIENCY AND COMPLIANCE WITH AUTOMATED DOCUMENT INTELLIGENCE
• 13.8 ENERGY & UTILITIES
  • 13.8.1 STRENGTHENING REGULATORY COMPLIANCE AND ASSET MANAGEMENT WITH AI-DRIVEN DOCUMENT PROCESSING
• 13.9 TELECOMMUNICATIONS
  • 13.9.1 STREAMLINING SERVICE DOCUMENTATION AND REGULATORY PROCESSES THROUGH AUTOMATION
• 13.10 EDUCATION
  • 13.10.1 EMPOWERING EDUCATIONAL EFFICIENCY THROUGH AI-DRIVEN DOCUMENT INTELLIGENCE
• 13.11 OTHER VERTICALS

14 DOCUMENT AI MARKET, BY REGION

• 14.1 INTRODUCTION
• 14.2 NORTH AMERICA
  • 14.2.1 NORTH AMERICA: DOCUMENT AI MARKET DRIVERS
  • 14.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 14.2.3 US
    • 14.2.3.1 Innovation leadership and regulatory maturity to drive market
  • 14.2.4 CANADA
    • 14.2.4.1 Public sector digitization and cloud adoption to drive market
• 14.3 EUROPE
  • 14.3.1 EUROPE: DOCUMENT AI MARKET DRIVERS
  • 14.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 14.3.3 UK
    • 14.3.3.1 Early enterprise digitalization and regulatory clarity to strengthen market
  • 14.3.4 GERMANY
    • 14.3.4.1 Manufacturing leadership and data sovereignty to drive Document AI adoption
  • 14.3.5 FRANCE
    • 14.3.5.1 Public sector digitization and language localization to boost market
  • 14.3.6 ITALY
    • 14.3.6.1 Modernization of public administration and BFSI to drive market
  • 14.3.7 REST OF EUROPE
• 14.4 ASIA PACIFIC
  • 14.4.1 ASIA PACIFIC: DOCUMENT AI MARKET DRIVERS
  • 14.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 14.4.3 CHINA
    • 14.4.3.1 National digital ecosystem and e-government push to fuel demand for Document AI
  • 14.4.4 INDIA
    • 14.4.4.1 Digital governance and rapid cloud adoption to power Document AI uptake
  • 14.4.5 JAPAN
    • 14.4.5.1 Workforce automation and paperless initiatives to drive Document AI adoption
  • 14.4.6 SOUTH KOREA
    • 14.4.6.1 High digital readiness and AI integration to fuel market
  • 14.4.7 SINGAPORE
    • 14.4.7.1 Innovation-led adoption and regulatory clarity to strengthen market
  • 14.4.8 REST OF ASIA PACIFIC
• 14.5 MIDDLE EAST & AFRICA
  • 14.5.1 MIDDLE EAST & AFRICA: DOCUMENT AI MARKET DRIVERS
  • 14.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 14.5.3 SAUDI ARABIA
    • 14.5.3.1 National digitalization and Vision 2030 to catalyze Document AI ecosystem
  • 14.5.4 UAE
    • 14.5.4.1 Early government adoption and smart infrastructure programs to drive Document AI leadership
  • 14.5.5 SOUTH AFRICA
    • 14.5.5.1 Urban enterprise digitalization and BFSI modernization to fuel the market
  • 14.5.6 QATAR
    • 14.5.6.1 Vision 2030 and national digital infrastructure investments to market
  • 14.5.7 REST OF MIDDLE EAST & AFRICA
• 14.6 LATIN AMERICA
  • 14.6.1 LATIN AMERICA: DOCUMENT AI MARKET DRIVERS
  • 14.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 14.6.3 BRAZIL
    • 14.6.3.1 Strict e-invoicing regulations and tax modernization programs to drive market
  • 14.6.4 MEXICO
    • 14.6.4.1 Tax digitalization and e-signature expansion to accelerate Document AI adoption
  • 14.6.5 REST OF LATIN AMERICA

15 COMPETITIVE LANDSCAPE

• 15.1 OVERVIEW
• 15.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2022-2025
• 15.3 REVENUE ANALYSIS, 2020-2024
• 15.4 MARKET SHARE ANALYSIS, 2024
• 15.5 PRODUCT COMPARISON
  • 15.5.1 PRODUCT COMPARATIVE ANALYSIS, BY DOCUMENT AI SOLUTION TYPE (IDP)
    • 15.5.1.1 Document AI (Google)
    • 15.5.1.2 Azure AI Document Intelligence (Microsoft)
    • 15.5.1.3 Amazon Textract & Comprehend (AWS)
    • 15.5.1.4 ABBYY Vantage (ABBYY)
    • 15.5.1.5 Kofax TotalAgility (Tungsten Automation)
  • 15.5.2 PRODUCT COMPARATIVE ANALYSIS, BY DOCUMENT AI SOLUTION TYPE (DOCUMENT WORKFLOW AUTOMATION)
    • 15.5.2.1 UiPath Document Understanding (UiPath)
    • 15.5.2.2 IQ Bot (Automation Anywhere)
    • 15.5.2.3 Intelligent Capture & Magellan (OpenText)
    • 15.5.2.4 IBM Watson Discovery & Automation (IBM)
    • 15.5.2.5 Intelligent Document Processing Platform (Infrrd)
  • 15.5.3 PRODUCT COMPARATIVE ANALYSIS, BY DOCUMENT AI SOLUTION TYPE (GEN AI DOCUMENT GENERATION)
    • 15.5.3.1 Gamma's intelligent formatting and design tools (Gamma)
    • 15.5.3.2 GPT-4/ChatGPT Enterprise (OpenAI)
    • 15.5.3.3 Gen AI-enhanced IDP (Docsumo)
    • 15.5.3.4 AI Writing Suite (QuillBot)
    • 15.5.3.5 Claude AI (Anthropic)
  • 15.5.4 PRODUCT COMPARATIVE ANALYSIS, BY DOCUMENT AI SOLUTION TYPE (ECM & GOVERNANCE TOOLS)
    • 15.5.4.1 AI-powered Process & Content Governance (Appian)
    • 15.5.4.2 Document Data Governance Cloud (Snowflake)
    • 15.5.4.3 XtractEdge for Document Governance (EdgeVerve)
    • 15.5.4.4 OnBase & Alfresco ECM (Hyland)
    • 15.5.4.5 Intelligent Digital Preservation Platform (Docbyte)
• 15.6 COMPANY VALUATION AND FINANCIAL METRICS
• 15.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
  • 15.7.1 IDP, DOCUMENT WORKFLOW AUTOMATION, AND ECM & GOVERNANCE TOOLS
    • 15.7.1.1 Stars
    • 15.7.1.2 Emerging leaders
    • 15.7.1.3 Pervasive players
    • 15.7.1.4 Participants
  • 15.7.2 COMPANY FOOTPRINT: KEY PLAYERS, 2024
    • 15.7.2.1 Company footprint
    • 15.7.2.2 Regional footprint
    • 15.7.2.3 Offering footprint
    • 15.7.2.4 Use case footprint
    • 15.7.2.5 Vertical footprint
  • 15.7.3 GENERATIVE AI DOCUMENT GENERATION
    • 15.7.3.1 Stars
    • 15.7.3.2 Emerging leaders
    • 15.7.3.3 Pervasive players
    • 15.7.3.4 Participants
  • 15.7.4 COMPANY FOOTPRINT: KEY PLAYERS (GENERATIVE AI DOCUMENT GENERATION), 2024
    • 15.7.4.1 Company footprint
    • 15.7.4.2 Regional footprint
    • 15.7.4.3 Offering footprint
    • 15.7.4.4 Use case footprint
    • 15.7.4.5 Vertical footprint
• 15.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
  • 15.8.1 IDP, DOCUMENT WORKFLOW AUTOMATION, ECM & GOVERNANCE TOOLS
    • 15.8.1.1 Progressive Companies
    • 15.8.1.2 Responsive companies
    • 15.8.1.3 Dynamic companies
    • 15.8.1.4 Starting blocks
  • 15.8.2 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    • 15.8.2.1 Detailed list of key startups/SMEs
    • 15.8.2.2 Competitive benchmarking of key startups/SMEs
• 15.9 COMPETITIVE SCENARIO
  • 15.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS
  • 15.9.2 DEALS

16 COMPANY PROFILES

• 16.1 INTRODUCTION
• 16.2 INTELLIGENT DOCUMENT PROCESSING
  • 16.2.1 KEY PLAYERS
    • 16.2.1.1 Google
      • 16.2.1.1.1 Business overview
      • 16.2.1.1.2 Products/Solutions/Services offered
      • 16.2.1.1.3 Recent developments
        • 16.2.1.1.3.1 Product launches and enhancements
        • 16.2.1.1.3.2 Deals
      • 16.2.1.1.4 MnM view
        • 16.2.1.1.4.1 Key strengths
        • 16.2.1.1.4.2 Strategic choices
        • 16.2.1.1.4.3 Weaknesses and competitive threats
    • 16.2.1.2 Microsoft
      • 16.2.1.2.1 Business overview
      • 16.2.1.2.2 Products/Solutions/Services offered
      • 16.2.1.2.3 Recent developments
        • 16.2.1.2.3.1 Product launches and enhancements
        • 16.2.1.2.3.2 Deals
      • 16.2.1.2.4 MnM view
        • 16.2.1.2.4.1 Key strengths
        • 16.2.1.2.4.2 Strategic choices
        • 16.2.1.2.4.3 Weaknesses and competitive threats
    • 16.2.1.3 Hyland
      • 16.2.1.3.1 Business overview
      • 16.2.1.3.2 Products/Solutions/Services offered
      • 16.2.1.3.3 Recent developments
        • 16.2.1.3.3.1 Product launches and enhancements
        • 16.2.1.3.3.2 Deals
      • 16.2.1.3.4 MnM view
        • 16.2.1.3.4.1 Key strengths
        • 16.2.1.3.4.2 Strategic choices
        • 16.2.1.3.4.3 Weaknesses and competitive threats
    • 16.2.1.4 IBM
      • 16.2.1.4.1 Business overview
      • 16.2.1.4.2 Products/Solutions/Services offered
      • 16.2.1.4.3 Recent developments
        • 16.2.1.4.3.1 Product launches and enhancements
        • 16.2.1.4.3.2 Deals
      • 16.2.1.4.4 MnM view
        • 16.2.1.4.4.1 Key strengths
        • 16.2.1.4.4.2 Strategic choices
        • 16.2.1.4.4.3 Weaknesses and competitive threats
    • 16.2.1.5 AWS
      • 16.2.1.5.1 Business overview
      • 16.2.1.5.2 Products/Solutions/Services offered
      • 16.2.1.5.3 Recent developments
        • 16.2.1.5.3.1 Product launches and enhancements
        • 16.2.1.5.3.2 Deals
      • 16.2.1.5.4 MnM view
        • 16.2.1.5.4.1 Key strengths
        • 16.2.1.5.4.2 Strategic choices
        • 16.2.1.5.4.3 Weaknesses and competitive threats
    • 16.2.1.6 Snowflake
      • 16.2.1.6.1 Business overview
      • 16.2.1.6.2 Products/Solutions/Services offered
      • 16.2.1.6.3 Recent developments
        • 16.2.1.6.3.1 Product launches and enhancements
        • 16.2.1.6.3.2 Deals
    • 16.2.1.7 Oracle
      • 16.2.1.7.1 Business overview
      • 16.2.1.7.2 Products/Solutions/Services offered
      • 16.2.1.7.3 Recent developments
        • 16.2.1.7.3.1 Product launches and enhancements
        • 16.2.1.7.3.2 Deals
        • 16.2.1.7.3.3 Other developments
    • 16.2.1.8 Adobe
      • 16.2.1.8.1 Business overview
      • 16.2.1.8.2 Products/Solutions/Services offered
      • 16.2.1.8.3 Recent developments
        • 16.2.1.8.3.1 Product launches and enhancements
        • 16.2.1.8.3.2 Deals
    • 16.2.1.9 ABBYY
      • 16.2.1.9.1 Business overview
      • 16.2.1.9.2 Products/Solutions/Services offered
      • 16.2.1.9.3 Recent developments
        • 16.2.1.9.3.1 Product launches and enhancements
        • 16.2.1.9.3.2 Deals
    • 16.2.1.10 Automation Anywhere
      • 16.2.1.10.1 Business overview
      • 16.2.1.10.2 Products/Solutions/Services offered
      • 16.2.1.10.3 Recent developments
        • 16.2.1.10.3.1 Product launches and enhancements
        • 16.2.1.10.3.2 Deals
    • 16.2.1.11 UiPath
      • 16.2.1.11.1 Business overview
      • 16.2.1.11.2 Products/Solutions/Services offered
      • 16.2.1.11.3 Recent developments
        • 16.2.1.11.3.1 Product launches and enhancements
        • 16.2.1.11.3.2 Deals
    • 16.2.1.12 Appian
      • 16.2.1.12.1 Business overview
      • 16.2.1.12.2 Products/Solutions/Services offered
      • 16.2.1.12.3 Recent developments
        • 16.2.1.12.3.1 Product launches and enhancements
        • 16.2.1.12.3.2 Deals
    • 16.2.1.13 EdgeVerve (Infosys)
    • 16.2.1.14 Tungsten Automation
    • 16.2.1.15 OpenText
    • 16.2.1.16 SAP
    • 16.2.1.17 EXL
    • 16.2.1.18 Salesforce
    • 16.2.1.19 H20.ai
    • 16.2.1.20 Scribe
    • 16.2.1.21 Docketry
    • 16.2.1.22 Cohere
  • 16.2.2 OTHER PLAYERS
    • 16.2.2.1 Grooper
    • 16.2.2.2 Hyperscience
    • 16.2.2.3 DocDigitizer
    • 16.2.2.4 Super.ai
    • 16.2.2.5 Cinnamon AI
    • 16.2.2.6 Docugami
    • 16.2.2.7 DocByte
    • 16.2.2.8 Infrrd
    • 16.2.2.9 Rossum
    • 16.2.2.10 Docubee
    • 16.2.2.11 Docsumo
    • 16.2.2.12 Checkbox
    • 16.2.2.13 Mindee
• 16.3 GENERATIVE AI DOCUMENT GENERATION
  • 16.3.1 KEY PLAYERS
    • 16.3.1.1 OpenAI
      • 16.3.1.1.1 Business overview
      • 16.3.1.1.2 Products/Solutions/Services offered
      • 16.3.1.1.3 Recent developments
        • 16.3.1.1.3.1 Product launches and enhancements
        • 16.3.1.1.3.2 Deals
    • 16.3.1.2 Gamma
    • 16.3.1.3 Upstage
    • 16.3.1.4 Aidocmaker
    • 16.3.1.5 Anthropic
    • 16.3.1.6 Mistral AI
    • 16.3.1.7 DocuPilot
    • 16.3.1.8 Intellistack
    • 16.3.1.9 HyperWrite (OthersideAI)
    • 16.3.1.10 Lindy
    • 16.3.1.11 QuillBot

17 ADJACENT AND RELATED MARKETS

• 17.1 INTRODUCTION
• 17.2 ARTIFICIAL INTELLIGENCE MARKET - GLOBAL FORECAST TO 2032
  • 17.2.1 MARKET DEFINITION
  • 17.2.2 MARKET OVERVIEW
    • 17.2.2.1 Artificial intelligence (AI) market, by offering
    • 17.2.2.2 Artificial intelligence (AI) market, by technology
    • 17.2.2.3 Artificial intelligence (AI) market, by business function
    • 17.2.2.4 Artificial intelligence (AI) market, by enterprise application
    • 17.2.2.5 Artificial intelligence (AI) market, by end user
    • 17.2.2.6 Artificial intelligence (AI) market, by region
• 17.3 AI DETECTOR MARKET - GLOBAL FORECAST TO 2030
  • 17.3.1 MARKET DEFINITION
  • 17.3.2 MARKET OVERVIEW
    • 17.3.2.1 AI detector market, by offering
    • 17.3.2.2 AI detector market, by detection modality
    • 17.3.2.3 AI detector market, by application
    • 17.3.2.4 AI detector market, by end user
    • 17.3.2.5 AI detector market, by region

18 APPENDIX

• 18.1 DISCUSSION GUIDE
• 18.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 18.3 CUSTOMIZATION OPTIONS
• 18.4 RELATED REPORTS
• 18.5 AUTHOR DETAILS