의료 코딩용 AI 시장 규모, 점유율 및 동향 분석 보고서 : 컴포넌트별, 지역별, 주요 기업, 경쟁 분석 및 부문 예측(2026-2033년)

AI In Medical Coding Market Summary

The global AI in medical coding market size was estimated at USD 2.86 billion in 2025 and is projected to reach USD 8.62 billion by 2033, growing at a CAGR of 14.19% from 2026 to 2033. Rising administrative burdens and coding complexity, workforce shortages and productivity constraints, as well as cost containment and revenue cycle optimization, are significant factors contributing to market growth.

Healthcare organizations face strict billing timelines and reimbursement cycles. Delays in coding affect cash flow and operational planning. AI-assisted coding accelerates chart review and code assignment. Automation supports near-real-time coding workflows. Faster turnaround improves first-pass claim acceptance. Reduced rework lowers administrative overhead. Efficiency requirements strengthen market demand. For instance, in April 2025, Cleveland Clinic implemented generative AI for medical coding to automate code assignment from clinical documentation. The initiative aims to improve accuracy, reduce administrative workload, and accelerate billing processes.

Moreover, the increasing complexity of clinical documentation and coding systems is a significant driver of the AI in medical coding industry. There is a growing demand for a more streamlined and convenient coding and billing solution. Medical coding plays a crucial role in ensuring consistent documentation across various medical facilities. Medical coding companies enable healthcare administrators to analyze the frequency and effectiveness of treatments within their facilities, important for large medical establishments, such as tertiary-care hospitals.

Integration with revenue cycle systems enhances financial control and oversight. Organizations prioritize risk mitigation. Compliance-driven financial protection fuels market growth. For instance, in April 2025, RamSoft and Maverick Medical AI partnered to integrate AI-powered medical coding into RamSoft's radiology workflow. The solution delivers real-time coding at the point of care, improving accuracy, reducing administrative burden, and accelerating revenue cycle processes for imaging providers through automated, compliant code generation.

Global AI in Medical Coding Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI in medical coding market report based on component and region.

• Component Outlook (Revenue, USD Million, 2021 - 2033)
• In-house
• Outsourced
• Regional Outlook (Revenue, USD Million, 2021 - 2033)
• North America
  • U.S.
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Denmark
  • Sweden
  • Norway
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Thailand
• Latin America
  • Brazil
  • Argentina
• MEA
  • South Africa
  • Saudi Arabia
  • UAE
  • Kuwait

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Market Definitions
  • 1.2.1. Component Segment
• 1.3. Information analysis
  • 1.3.1. Market formulation & data visualization
• 1.4. Data validation & publishing
• 1.5. Information Procurement
  • 1.5.1. Primary Research
• 1.6. Information or Data Analysis
• 1.7. Market Formulation & Validation
• 1.8. Market Model
• 1.9. Total Market: CAGR Calculation
• 1.10. Objectives
  • 1.10.1. Objective 1
  • 1.10.2. Objective 2

Chapter 2. Executive Summary

• 2.1. Market Outlook
• 2.2. Segment Snapshot
• 2.3. Competitive Insights Landscape

Chapter 3. AI in Medical Coding Market Variables, Trends & Scope

• 3.1. Market Lineage Outlook
  • 3.1.1. Parent market outlook
  • 3.1.2. Related/ancillary market outlook.
• 3.2. Market Dynamics
  • 3.2.1. Market driver analysis
  • 3.2.2. Market restraint analysis
  • 3.2.3. Market opportunity analysis
  • 3.2.4. Market challenges analysis
• 3.3. AI in Medical Coding Market Analysis Tools
  • 3.3.1. Industry Analysis - Porter's Five Forces Analysis
    • 3.3.1.1. Supplier power
    • 3.3.1.2. Buyer power
    • 3.3.1.3. Substitution threat
    • 3.3.1.4. Threat of new entrant
    • 3.3.1.5. Competitive rivalry
  • 3.3.2. PESTEL Analysis
    • 3.3.2.1. Political landscape
    • 3.3.2.2. Technological landscape
    • 3.3.2.3. Economic landscape
    • 3.3.2.4. Environmental Landscape
    • 3.3.2.5. Legal Landscape
    • 3.3.2.6. Social Landscape

Chapter 4. AI in Medical Coding Market: Component Estimates & Trend Analysis

• 4.1. Segment Dashboard
• 4.2. Global AI in Medical Coding Market Component Movement Analysis
• 4.3. Global AI in Medical Coding Market Size & Trend Analysis, by component, 2021 to 2033 (USD Million)
• 4.4. In-house
  • 4.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
• 4.5. Outsourced
  • 4.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)

Chapter 5. AI in Medical Coding Market: Regional Estimates & Trend Analysis

• 5.1. Regional Market Share Analysis, 2025 & 2033
• 5.2. Regional Market Dashboard
• 5.3. Market Size & Forecasts Trend Analysis, 2021 to 2033:
• 5.4. North America
  • 5.4.1. U.S.
    • 5.4.1.1. Key country dynamics
    • 5.4.1.2. Regulatory framework
    • 5.4.1.3. Competitive scenario
    • 5.4.1.4. U.S. market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.4.2. Canada
    • 5.4.2.1. Key country dynamics
    • 5.4.2.2. Regulatory framework
    • 5.4.2.3. Competitive scenario
    • 5.4.2.4. Canada market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.4.3. Mexico
    • 5.4.3.1. Key country dynamics
    • 5.4.3.2. Regulatory framework
    • 5.4.3.3. Competitive scenario
    • 5.4.3.4. Mexico market estimates and forecasts, 2021 to 2033 (USD Million)
• 5.5. Europe
  • 5.5.1. UK
    • 5.5.1.1. Key country dynamics
    • 5.5.1.2. Regulatory framework
    • 5.5.1.3. Competitive scenario
    • 5.5.1.4. UK market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.2. Germany
    • 5.5.2.1. Key country dynamics
    • 5.5.2.2. Regulatory framework
    • 5.5.2.3. Competitive scenario
    • 5.5.2.4. Germany market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.3. France
    • 5.5.3.1. Key country dynamics
    • 5.5.3.2. Regulatory framework
    • 5.5.3.3. Competitive scenario
    • 5.5.3.4. France market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.4. Italy
    • 5.5.4.1. Key country dynamics
    • 5.5.4.2. Regulatory framework
    • 5.5.4.3. Competitive scenario
    • 5.5.4.4. Italy market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.5. Spain
    • 5.5.5.1. Key country dynamics
    • 5.5.5.2. Regulatory framework
    • 5.5.5.3. Competitive scenario
    • 5.5.5.4. Spain market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.6. Norway
    • 5.5.6.1. Key country dynamics
    • 5.5.6.2. Regulatory framework
    • 5.5.6.3. Competitive scenario
    • 5.5.6.4. Norway market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.7. Sweden
    • 5.5.7.1. Key country dynamics
    • 5.5.7.2. Regulatory framework
    • 5.5.7.3. Competitive scenario
    • 5.5.7.4. Sweden market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.5.8. Denmark
    • 5.5.8.1. Key country dynamics
    • 5.5.8.2. Regulatory framework
    • 5.5.8.3. Competitive scenario
    • 5.5.8.4. Denmark market estimates and forecasts, 2021 to 2033 (USD Million)
• 5.6. Asia Pacific
  • 5.6.1. Japan
    • 5.6.1.1. Key country dynamics
    • 5.6.1.2. Regulatory framework
    • 5.6.1.3. Competitive scenario
    • 5.6.1.4. Japan market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.6.2. China
    • 5.6.2.1. Key country dynamics
    • 5.6.2.2. Regulatory framework
    • 5.6.2.3. Competitive scenario
    • 5.6.2.4. China market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.6.3. India
    • 5.6.3.1. Key country dynamics
    • 5.6.3.2. Regulatory framework
    • 5.6.3.3. Competitive scenario
    • 5.6.3.4. India market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.6.4. Australia
    • 5.6.4.1. Key country dynamics
    • 5.6.4.2. Regulatory framework
    • 5.6.4.3. Competitive scenario
    • 5.6.4.4. Australia market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.6.5. South Korea
    • 5.6.5.1. Key country dynamics
    • 5.6.5.2. Regulatory framework
    • 5.6.5.3. Competitive scenario
    • 5.6.5.4. South Korea market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.6.6. Thailand
    • 5.6.6.1. Key country dynamics
    • 5.6.6.2. Regulatory framework
    • 5.6.6.3. Competitive scenario
    • 5.6.6.4. Thailand market estimates and forecasts, 2021 to 2033 (USD Million)
• 5.7. Latin America
  • 5.7.1. Brazil
    • 5.7.1.1. Key country dynamics
    • 5.7.1.2. Regulatory framework
    • 5.7.1.3. Competitive scenario
    • 5.7.1.4. Brazil market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.7.2. Argentina
    • 5.7.2.1. Key country dynamics
    • 5.7.2.2. Regulatory framework
    • 5.7.2.3. Competitive scenario
    • 5.7.2.4. Argentina market estimates and forecasts, 2021 to 2033 (USD Million)
• 5.8. MEA
  • 5.8.1. South Africa
    • 5.8.1.1. Key country dynamics
    • 5.8.1.2. Regulatory framework
    • 5.8.1.3. Competitive scenario
    • 5.8.1.4. South Africa market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.8.2. Saudi Arabia
    • 5.8.2.1. Key country dynamics
    • 5.8.2.2. Regulatory framework
    • 5.8.2.3. Competitive scenario
    • 5.8.2.4. Saudi Arabia market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.8.3. UAE
    • 5.8.3.1. Key country dynamics
    • 5.8.3.2. Regulatory framework
    • 5.8.3.3. Competitive scenario
    • 5.8.3.4. UAE market estimates and forecasts, 2021 to 2033 (USD Million)
  • 5.8.4. Kuwait
    • 5.8.4.1. Key country dynamics
    • 5.8.4.2. Regulatory framework
    • 5.8.4.3. Competitive scenario
    • 5.8.4.4. Kuwait market estimates and forecasts, 2021 to 2033 (USD Million)

Chapter 6. Competitive Landscape

• 6.1. Company/Competition Categorization
• 6.2. Strategy Mapping
• 6.3. Company Market Position Analysis, 2025
• 6.4. Company Profiles/Listing
  • 6.4.1. Oracle
    • 6.4.1.1. Company overview
    • 6.4.1.2. Financial performance
    • 6.4.1.3. Product benchmarking
    • 6.4.1.4. Strategic initiatives
  • 6.4.2. CodaMetrix
    • 6.4.2.1. Company overview
    • 6.4.2.2. Financial performance
    • 6.4.2.3. Product benchmarking
    • 6.4.2.4. Strategic initiatives
  • 6.4.3. IBM
    • 6.4.3.1. Company overview
    • 6.4.3.2. Financial performance
    • 6.4.3.3. Product benchmarking
    • 6.4.3.4. Strategic initiatives
  • 6.4.4. Fathom, Inc.
    • 6.4.4.1. Company overview
    • 6.4.4.2. Financial performance
    • 6.4.4.3. Product benchmarking
    • 6.4.4.4. Strategic initiatives
  • 6.4.5. Clinion
    • 6.4.5.1. Company overview
    • 6.4.5.2. Financial performance
    • 6.4.5.3. Product benchmarking
    • 6.4.5.4. Strategic initiatives
  • 6.4.6. BUDDI.AI
    • 6.4.6.1. Company overview
    • 6.4.6.2. Financial performance
    • 6.4.6.3. Product benchmarking
    • 6.4.6.4. Strategic initiatives
  • 6.4.7. aideo technologies, LLC
    • 6.4.7.1. Company overview
    • 6.4.7.2. Financial performance
    • 6.4.7.3. Product benchmarking
    • 6.4.7.4. Strategic initiatives
  • 6.4.8. Diagnoss
    • 6.4.8.1. Company overview
    • 6.4.8.2. Financial performance
    • 6.4.8.3. Product benchmarking
    • 6.4.8.4. Strategic initiatives
  • 6.4.9. Suki AI, Inc.
    • 6.4.9.1. Company overview
    • 6.4.9.2. Financial performance
    • 6.4.9.3. Product benchmarking
    • 6.4.9.4. Strategic initiatives
  • 6.4.10. Netsmart Technologies, Inc.
    • 6.4.10.1. Company overview
    • 6.4.10.2. Financial performance
    • 6.4.10.3. Product benchmarking
    • 6.4.10.4. Strategic initiatives
  • 6.4.11. Arintra
    • 6.4.11.1. Company overview
    • 6.4.11.2. Financial performance
    • 6.4.11.3. Product benchmarking
    • 6.4.11.4. Strategic initiatives