RCM(Revenue Cycle Management)용 AI 시장 규모, 점유율, 동향 분석 리포트 : 제품별, 유형별, 용도별, 딜리버리 모드별, 최종 용도별, 지역별, 매출과 동향 예측(2025-2030년)

Market Size & Trends:

The global AI in revenue cycle management market size was estimated at USD 20.63 billion in 2024 and is projected to grow at a CAGR of 24.16% from 2025 to 2030. Rising healthcare claim denials & complexity in payer rules, shift from transactional to value-based revenue cycle management (RCM), and growing focus on interoperability & ecosystem integration are factors contributing to market growth.

One of the most significant drivers of artificial intelligence in the revenue cycle management market is the increasing volume and complexity of healthcare claim denials. Claim denials are rising in volume and are increasingly difficult to appeal due to varying payer policies and frequent regulatory shifts.

AI-enabled solutions offer predictive denial management, real-time eligibility checks, and automated appeals processing, significantly improving denial resolution rates. Healthcare providers are thus investing in AI to reduce denials, predict them, and intervene earlier in the billing cycle. For instance, in December 2024, Care.fi launched RevNow, an AI-powered RCM platform for hospitals in India to manage insurance claims. This platform uses advanced analytics and automation to streamline the insurance claims process, including patient admission through to final discharge, pre-authorization to post-authorization, and claim adjudication to settlement.

"By harnessing AI and automation, we're enabling hospitals to overcome the traditional challenges of claims processing-delays, rejections, and inefficiencies-and transform them into streamlined, transparent workflows."

Sidak Singh, Co-founder, Care.fi.

Moreover, healthcare facilities are outsourcing RCM software solutions owing to the multiple advantages associated such as easy availability of trained and skilled professionals, enhanced efficiency, compliance, adherence to required regulations, and cost-effectiveness. A survey by Salucro Healthcare Solutions in January 2024, involving 176 healthcare professionals, found that 50% of respondents are generally satisfied with their organization's revenue cycle management, with 34% considering it somewhat efficient and 16% very efficient. However, hands-on revenue cycle leaders are less likely to view the system as efficient compared to executive leaders.

Furthermore, acute workforce shortages in medical billing and coding departments drive market growth further. AI helps offset staffing gaps by automating routine, manual RCM tasks such as charge entry, coding validation, claims status checks, and payment posting. For instance, in July 2024, Thoughtful AI launched human-capable AI agents' CAM, EVA, and PHIL to reduce human intervention in healthcare providers' RCM departments.

"Back office staffing and reimbursement are core reasons why the U.S. healthcare system is so expensive and inefficient," explained Zekoff. "In many industries, collections cost less than a penny on the dollar, but collections can cost 10 times that in healthcare. Imagine a healthcare provider making $100 million a year yet having to spend $10 million to collect that revenue. Those dollars should go to the patient experience, not inefficient collections processes."

Alex Zekoff, Thoughtful AI co-founder and CEO

AI solutions that can seamlessly integrate with existing RCM platforms, electronic health record (EHR), and payer systems are gaining traction. Interoperability is essential for enabling real-time claims processing and ensuring payment integrity workflows. Vendors are increasingly providing APIs and cloud-based platforms that improve data flow between clinical and financial systems. AI plays a crucial role in unifying various revenue cycle processes, ranging from prior authorizations to denial appeals, resulting in a more cohesive and real-time financial environment.

Global AI In Revenue Cycle Management Market Report Segmentation

This report forecasts revenue growth at the global, regional & country level and provides an analysis of the latest trends and opportunities in each of the sub-segments from 2018 to 2030. For this report, Grand View Research has segmented the global AI in revenue cycle management market report based on product, type, application, delivery mode, end use, and region:

• Product Outlook (Revenue, USD Million, 2018 - 2030)
• Software
• Services
• Type Outlook (Revenue, USD Million, 2018 - 2030)
• Integrated
• Standalone
• Application Outlook (Revenue, USD Million, 2018 - 2030)
• Medical Coding and Charge Capture
• Claims Management
• Payment Posting & Remittance
• Financial Analytics & KPI Monitoring
• Others
• Delivery Mode Outlook (Revenue, USD Million, 2018 - 2030)
• Web-based
• Cloud-based
• On-premise
• End Use Outlook (Revenue, USD Million, 2018 - 2030)
• Physician Back Offices
• Hospitals
• Diagnostic Laboratories
• Other
• Regional Outlook (Revenue, USD Million, 2018 - 2030)
• North America
  • U.S.
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Denmark
  • Sweden
  • Norway
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • South Korea
  • Thailand
• Latin America
  • Brazil
  • Argentina
• Middle East and Africa (MEA)
  • South Africa
  • Saudi Arabia
  • UAE
  • Kuwait

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Segment Definitions
  • 1.2.1. Type
  • 1.2.2. Product
  • 1.2.3. Application
  • 1.2.4. Delivery Mode
  • 1.2.5. End Use
• 1.3. Estimates and Forecast Timeline
• 1.4. Research Methodology
• 1.5. Information Procurement
  • 1.5.1. Purchased Database
  • 1.5.2. GVR's Internal Database
  • 1.5.3. Secondary Sources
  • 1.5.4. Primary Research
• 1.6. Information Analysis
  • 1.6.1. Data Analysis Models
• 1.7. Market Formulation & Data Visualization
• 1.8. Model Details
• 1.9. List of Secondary Sources
• 1.10. Objectives

Chapter 2. Executive Summary

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

Chapter 3. Market Variables, Trends, & Scope

• 3.1. Market Segmentation and Scope
• 3.2. Market Lineage Outlook
  • 3.2.1. Parent Market Outlook
  • 3.2.2. Related/Ancillary Market Outlook
• 3.3. Market Trends and Outlook
  • 3.3.1. Market Driver Analysis
  • 3.3.2. Market Restraint Analysis
  • 3.3.3. Market Opportunity Analysis
  • 3.3.4. Market Challenges Analysis
• 3.4. Business Environment Analysis
  • 3.4.1. PESTLE Analysis
  • 3.4.2. Porter's Five Forces Analysis
• 3.5. Case Studies

Chapter 4. AI in Revenue Cycle Management Market: Product Estimates & Trend Analysis

• 4.1. Segment Dashboard
• 4.2. Global AI in Revenue Cycle Management Market Product Movement Analysis
• 4.3. Global AI in Revenue Cycle Management Market Size & Trend Analysis, by Product, 2018 to 2030 (USD Million)
• 4.4. Software
  • 4.4.1. Software market, 2018 - 2030 (USD Million)
• 4.5. Services
  • 4.5.1. Services market, 2018 - 2030 (USD Million)

Chapter 5. AI in Revenue Cycle Management Market: Type Estimates & Trend Analysis

• 5.1. Segment Dashboard
• 5.2. Global AI in Revenue Cycle Management Market Type Movement Analysis
• 5.3. Global AI in Revenue Cycle Management Market Size & Trend Analysis, by Type, 2018 to 2030 (USD Million)
• 5.4. Integrated
  • 5.4.1. Integrated market, 2018 - 2030 (USD Million)
• 5.5. Standalone
  • 5.5.1. Standalone market, 2018 - 2030 (USD Million)

Chapter 6. AI in Revenue Cycle Management Market: Application Estimates & Trend Analysis

• 6.1. Segment Dashboard
• 6.2. Global AI in Revenue Cycle Management Market Application Movement Analysis
• 6.3. Global AI in Revenue Cycle Management Market Size & Trend Analysis, by Application, 2018 to 2030 (USD Million)
• 6.4. Medical Coding and Charge Capture
  • 6.4.1. Medical coding and charge capture market, 2018 - 2030 (USD Million)
• 6.5. Claims Management
  • 6.5.1. Claims management market, 2018 - 2030 (USD Million)
• 6.6. Payment Posting & Remittance
  • 6.6.1. Payment posting & remittance market, 2018 - 2030 (USD Million)
• 6.7. Financial Analytics & KPI Monitoring
  • 6.7.1. Financial analytics & KPI monitoring market, 2018 - 2030 (USD Million)
• 6.8. Others
  • 6.8.1. Others market, 2018 - 2030 (USD Million)

Chapter 7. AI in Revenue Cycle Management Market: Delivery Mode Estimates & Trend Analysis

• 7.1. Segment Dashboard
• 7.2. Global AI in Revenue Cycle Management Market Delivery Mode Movement Analysis
• 7.3. Global AI in Revenue Cycle Management Market Size & Trend Analysis, by Delivery Mode, 2018 to 2030 (USD Million)
• 7.4. On-premise
  • 7.4.1. On-premise market, 2018 - 2030 (USD Million)
• 7.5. Web-based
  • 7.5.1. Web-based market, 2018 - 2030 (USD Million)
• 7.6. Cloud-based
  • 7.6.1. Cloud-based market, 2018 - 2030 (USD Million)

Chapter 8. AI in Revenue Cycle Management Market: End Use Estimates & Trend Analysis

• 8.1. Segment Dashboard
• 8.2. Global AI in Revenue Cycle Management Market End Use Movement Analysis
• 8.3. Global AI in Revenue Cycle Management Market Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
• 8.4. Physician Back Offices
  • 8.4.1. Physician back offices market, 2018 - 2030 (USD Million)
• 8.5. Hospitals
  • 8.5.1. Hospitals market, 2018 - 2030 (USD Million)
• 8.6. Diagnostic Laboratories
  • 8.6.1. Diagnostic laboratories market, 2018 - 2030 (USD Million)
• 8.7. Others
  • 8.7.1. Others market, 2018 - 2030 (USD Million)

Chapter 9. Regional Business Analysis

• 9.1. Regional Market Share Analysis, 2024 & 2030
• 9.2. Regional Market Dashboard
• 9.3. Global Regional Market Snapshot
• 9.4. Market Size, & Forecasts Trend Analysis, 2018 to 2030:
• 9.5. North America
  • 9.5.1. North America AI in Revenue Cycle Management Market, 2018 - 2030 (USD Million)
  • 9.5.2. U.S.
    • 9.5.2.1. Key Country Dynamics
    • 9.5.2.2. Competitive Scenario
    • 9.5.2.3. Regulatory Framework
    • 9.5.2.4. U.S. revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.5.3. Canada
    • 9.5.3.1. Key Country Dynamics
    • 9.5.3.2. Competitive Scenario
    • 9.5.3.3. Regulatory Framework
    • 9.5.3.4. Canada revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.5.4. Mexico
    • 9.5.4.1. Key Country Dynamics
    • 9.5.4.2. Competitive Scenario
    • 9.5.4.3. Regulatory Framework
    • 9.5.4.4. Mexico revenue cycle management market, 2018 - 2030 (USD Million)
• 9.6. Europe
  • 9.6.1. Europe AI in Revenue Cycle Management Market, 2018 - 2030 (USD Million)
  • 9.6.2. Germany
    • 9.6.2.1. Key Country Dynamics
    • 9.6.2.2. Competitive Scenario
    • 9.6.2.3. Regulatory Framework
    • 9.6.2.4. Germany revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.3. UK
    • 9.6.3.1. Key Country Dynamics
    • 9.6.3.2. Competitive Scenario
    • 9.6.3.3. Regulatory Framework
    • 9.6.3.4. UK revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.4. France
    • 9.6.4.1. Key Country Dynamics
    • 9.6.4.2. Competitive Scenario
    • 9.6.4.3. Regulatory Framework
    • 9.6.4.4. France revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.5. Italy
    • 9.6.5.1. Key Country Dynamics
    • 9.6.5.2. Competitive Scenario
    • 9.6.5.3. Regulatory Framework
    • 9.6.5.4. Italy revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.6. Spain
    • 9.6.6.1. Key Country Dynamics
    • 9.6.6.2. Competitive Scenario
    • 9.6.6.3. Regulatory Framework
    • 9.6.6.4. Spain revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.7. Denmark
    • 9.6.7.1. Key Country Dynamics
    • 9.6.7.2. Competitive Scenario
    • 9.6.7.3. Regulatory Framework
    • 9.6.7.4. Denmark revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.8. Sweden
    • 9.6.8.1. Key Country Dynamics
    • 9.6.8.2. Competitive Scenario
    • 9.6.8.3. Regulatory Framework
    • 9.6.8.4. Sweden revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.6.9. Norway
    • 9.6.9.1. Key Country Dynamics
    • 9.6.9.2. Competitive Scenario
    • 9.6.9.3. Regulatory Framework
    • 9.6.9.4. Norway revenue cycle management market, 2018 - 2030 (USD Million)
• 9.7. Asia Pacific
  • 9.7.1. Asia Pacific AI in Revenue Cycle Management Market, 2018 - 2030 (USD Million)
  • 9.7.2. Japan
    • 9.7.2.1. Key Country Dynamics
    • 9.7.2.2. Competitive Scenario
    • 9.7.2.3. Regulatory Framework
    • 9.7.2.4. Japan revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.7.3. China
    • 9.7.3.1. Key Country Dynamics
    • 9.7.3.2. Competitive Scenario
    • 9.7.3.3. Regulatory Framework
    • 9.7.3.4. China revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.7.4. India
    • 9.7.4.1. Key Country Dynamics
    • 9.7.4.2. Competitive Scenario
    • 9.7.4.3. Regulatory Framework
    • 9.7.4.4. India revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.7.5. South Korea
    • 9.7.5.1. Key Country Dynamics
    • 9.7.5.2. Competitive Scenario
    • 9.7.5.3. Regulatory Framework
    • 9.7.5.4. South Korea revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.7.6. Australia
    • 9.7.6.1. Key Country Dynamics
    • 9.7.6.2. Competitive Scenario
    • 9.7.6.3. Regulatory Framework
    • 9.7.6.4. Australia revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.7.7. Thailand
    • 9.7.7.1. Key Country Dynamics
    • 9.7.7.2. Competitive Scenario
    • 9.7.7.3. Regulatory Framework
    • 9.7.7.4. Thailand revenue cycle management market, 2018 - 2030 (USD Million)
• 9.8. Latin America
  • 9.8.1. Latin America AI in Revenue Cycle Management Market, 2018 - 2030 (USD Million)
  • 9.8.2. Brazil
    • 9.8.2.1. Key Country Dynamics
    • 9.8.2.2. Competitive Scenario
    • 9.8.2.3. Regulatory Framework
    • 9.8.2.4. Brazil revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.8.3. Argentina
    • 9.8.3.1. Key Country Dynamics
    • 9.8.3.2. Competitive Scenario
    • 9.8.3.3. Regulatory Framework
    • 9.8.3.4. Argentina revenue cycle management market, 2018 - 2030 (USD Million)
• 9.9. MEA
  • 9.9.1. MEA AI in Revenue Cycle Management Market, 2018 - 2030 (USD Million)
  • 9.9.2. South Africa
    • 9.9.2.1. Key Country Dynamics
    • 9.9.2.2. Competitive Scenario
    • 9.9.2.3. Regulatory Framework
    • 9.9.2.4. South Africa revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.9.3. Saudi Arabia
    • 9.9.3.1. Key Country Dynamics
    • 9.9.3.2. Competitive Scenario
    • 9.9.3.3. Regulatory Framework
    • 9.9.3.4. Saudi Arabia revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.9.4. UAE
    • 9.9.4.1. Key Country Dynamics
    • 9.9.4.2. Competitive Scenario
    • 9.9.4.3. Regulatory Framework
    • 9.9.4.4. UAE revenue cycle management market, 2018 - 2030 (USD Million)
  • 9.9.5. Kuwait
    • 9.9.5.1. Key Country Dynamics
    • 9.9.5.2. Competitive Scenario
    • 9.9.5.3. Regulatory Framework
    • 9.9.5.4. Kuwait revenue cycle management market, 2018 - 2030 (USD Million)

Chapter 10. Competitive Landscape

• 10.1. Participant's Overview
• 10.2. Financial Performance
• 10.3. Company Market Position Analysis
• 10.4. Strategy Mapping
• 10.5. Company Profiles/Listing
  • 10.5.1. athenahealth, Inc.
    • 10.5.1.1. Overview
    • 10.5.1.2. Financial Performance
    • 10.5.1.3. Product Benchmarking
    • 10.5.1.4. Strategic Initiatives
  • 10.5.2. Experian Information Solutions, Inc.
    • 10.5.2.1. Overview
    • 10.5.2.2. Financial Performance
    • 10.5.2.3. Product Benchmarking
    • 10.5.2.4. Strategic Initiatives
  • 10.5.3. R1 RCM, Inc.
    • 10.5.3.1. Overview
    • 10.5.3.2. Financial Performance
    • 10.5.3.3. Product Benchmarking
    • 10.5.3.4. Strategic Initiatives
  • 10.5.4. McKesson Corporation
    • 10.5.4.1. Overview
    • 10.5.4.2. Financial Performance
    • 10.5.4.3. Product Benchmarking
    • 10.5.4.4. Strategic Initiatives
  • 10.5.5. Oracle (Cerner Corporation)
    • 10.5.5.1. Overview
    • 10.5.5.2. Financial Performance
    • 10.5.5.3. Product Benchmarking
    • 10.5.5.4. Strategic Initiatives
  • 10.5.6. CareCloud Corporation
    • 10.5.6.1. Overview
    • 10.5.6.2. Financial Performance
    • 10.5.6.3. Product Benchmarking
    • 10.5.6.4. Strategic Initiatives
  • 10.5.7. eClinicalWorks
    • 10.5.7.1. Overview
    • 10.5.7.2. Financial Performance
    • 10.5.7.3. Product Benchmarking
    • 10.5.7.4. Strategic Initiatives
  • 10.5.8. Infinx
    • 10.5.8.1. Overview
    • 10.5.8.2. Financial Performance
    • 10.5.8.3. Product Benchmarking
    • 10.5.8.4. Strategic Initiatives
  • 10.5.9. Care.fi
    • 10.5.9.1. Overview
    • 10.5.9.2. Financial Performance
    • 10.5.9.3. Product Benchmarking
    • 10.5.9.4. Strategic Initiatives
  • 10.5.10. VisiQuate
    • 10.5.10.1. Overview
    • 10.5.10.2. Financial Performance
    • 10.5.10.3. Product Benchmarking
    • 10.5.10.4. Strategic Initiatives
  • 10.5.11. IntelligentDX
    • 10.5.11.1. Overview
    • 10.5.11.2. Financial Performance
    • 10.5.11.3. Product Benchmarking
    • 10.5.11.4. Strategic Initiatives
  • 10.5.12. Thoughtful AI
    • 10.5.12.1. Overview
    • 10.5.12.2. Financial Performance
    • 10.5.12.3. Product Benchmarking
    • 10.5.12.4. Strategic Initiatives
  • 10.5.13. Adonis
    • 10.5.13.1. Overview
    • 10.5.13.2. Financial Performance
    • 10.5.13.3. Product Benchmarking
    • 10.5.13.4. Strategic Initiatives
  • 10.5.14. Zentist
    • 10.5.14.1. Overview
    • 10.5.14.2. Financial Performance
    • 10.5.14.3. Product Benchmarking
    • 10.5.14.4. Strategic Initiatives
  • 10.5.15. Maverick Medical AI Ltd.
    • 10.5.15.1. Overview
    • 10.5.15.2. Financial Performance
    • 10.5.15.3. Product Benchmarking
    • 10.5.15.4. Strategic Initiatives