
North America AI In Revenue Cycle Management Market Size, Share & Industry Analysis Report By Type (Integrated and Standalone), By Delivery Mode (Cloud-based, Web-based, and On-premise), By End Use (Physician Back Offices, Hospitals, Diagnostic Laboratori
Description
The North America AI In Revenue Cycle Management Market would witness market growth of 23.3% CAGR during the forecast period (2025-2032).
The US market dominated the North America AI In Revenue Cycle Management Market by Country in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of $39,704.5 Million by 2032. The Canada market is experiencing a CAGR of 26% during (2025 - 2032). Additionally, The Mexico market would exhibit a CAGR of 24.9% during (2025 - 2032).
Artificial Intelligence (AI) has rapidly emerged as a transformative force across various sectors of the global economy, with the healthcare industry experiencing particularly profound change. Among the critical domains within healthcare, Revenue Cycle Management (RCM) stands out as an area where AI’s potential to drive efficiency, accuracy, and financial sustainability is increasingly evident. The integration of AI into RCM is reshaping how healthcare providers, payers, and associated stakeholders manage the complex web of administrative and financial processes required to track patient care episodes, from registration and appointment scheduling to final payment of a balance.
Revenue Cycle Management encompasses the comprehensive process of capturing, managing, and collecting patient service revenue, a cycle that begins at the time a patient schedules an appointment and concludes when the healthcare provider receives full payment for services rendered. Traditionally, RCM has been fraught with challenges, including manual data entry errors, fragmented workflows, claim denials, coding inaccuracies, delayed payments, and regulatory compliance complexities.
The United States is the world’s leading market for artificial intelligence in revenue cycle management, owing to its vast and complex healthcare ecosystem. The U.S. healthcare sector encompasses thousands of hospitals, clinics, payers, and physician groups, all operating under a multi-payer insurance model with a heavy administrative load. Rising healthcare costs, frequent coding updates, and mounting regulatory pressures have made the adoption of AI-powered RCM solutions a top priority for providers seeking to improve both profitability and patient care.
Canada’s publicly funded healthcare system is increasingly turning to artificial intelligence in revenue cycle management to address operational inefficiencies and meet rising expectations for service delivery. The country’s universal health coverage model, while eliminating the complexities of multi-payer billing, still faces challenges related to resource allocation, administrative burdens, and the integration of disparate provincial healthcare systems.
Mexico’s healthcare system is marked by a mix of public and private providers, with significant variation in quality, efficiency, and financial management across the sector. In recent years, the adoption of artificial intelligence in revenue cycle management has begun to accelerate as hospitals, insurers, and clinics recognize the benefits of automation in reducing administrative burdens and improving revenue collection.
Based on Type, the market is segmented into Integrated and Standalone. Based on Delivery Mode, the market is segmented into Cloud-based, Web-based, and On-premise. Based on End Use, the market is segmented into Physician Back Offices, Hospitals, Diagnostic Laboratories, and Other End Use. Based on Application, the market is segmented into Claims Management, Medical Coding & Charge Capture, Financial Analytics & KPI Monitoring, Payment Posting & Remittance, and Other Application. Based on Product, the market is segmented into Software and Services. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
List of Key Companies Profiled
By Type
The US market dominated the North America AI In Revenue Cycle Management Market by Country in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of $39,704.5 Million by 2032. The Canada market is experiencing a CAGR of 26% during (2025 - 2032). Additionally, The Mexico market would exhibit a CAGR of 24.9% during (2025 - 2032).
Artificial Intelligence (AI) has rapidly emerged as a transformative force across various sectors of the global economy, with the healthcare industry experiencing particularly profound change. Among the critical domains within healthcare, Revenue Cycle Management (RCM) stands out as an area where AI’s potential to drive efficiency, accuracy, and financial sustainability is increasingly evident. The integration of AI into RCM is reshaping how healthcare providers, payers, and associated stakeholders manage the complex web of administrative and financial processes required to track patient care episodes, from registration and appointment scheduling to final payment of a balance.
Revenue Cycle Management encompasses the comprehensive process of capturing, managing, and collecting patient service revenue, a cycle that begins at the time a patient schedules an appointment and concludes when the healthcare provider receives full payment for services rendered. Traditionally, RCM has been fraught with challenges, including manual data entry errors, fragmented workflows, claim denials, coding inaccuracies, delayed payments, and regulatory compliance complexities.
The United States is the world’s leading market for artificial intelligence in revenue cycle management, owing to its vast and complex healthcare ecosystem. The U.S. healthcare sector encompasses thousands of hospitals, clinics, payers, and physician groups, all operating under a multi-payer insurance model with a heavy administrative load. Rising healthcare costs, frequent coding updates, and mounting regulatory pressures have made the adoption of AI-powered RCM solutions a top priority for providers seeking to improve both profitability and patient care.
Canada’s publicly funded healthcare system is increasingly turning to artificial intelligence in revenue cycle management to address operational inefficiencies and meet rising expectations for service delivery. The country’s universal health coverage model, while eliminating the complexities of multi-payer billing, still faces challenges related to resource allocation, administrative burdens, and the integration of disparate provincial healthcare systems.
Mexico’s healthcare system is marked by a mix of public and private providers, with significant variation in quality, efficiency, and financial management across the sector. In recent years, the adoption of artificial intelligence in revenue cycle management has begun to accelerate as hospitals, insurers, and clinics recognize the benefits of automation in reducing administrative burdens and improving revenue collection.
Based on Type, the market is segmented into Integrated and Standalone. Based on Delivery Mode, the market is segmented into Cloud-based, Web-based, and On-premise. Based on End Use, the market is segmented into Physician Back Offices, Hospitals, Diagnostic Laboratories, and Other End Use. Based on Application, the market is segmented into Claims Management, Medical Coding & Charge Capture, Financial Analytics & KPI Monitoring, Payment Posting & Remittance, and Other Application. Based on Product, the market is segmented into Software and Services. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
List of Key Companies Profiled
- R1 RCM, Inc. (TowerBrook Capital Partners L.P.)
- Athenahealth, Inc. (Bain Capital, LP.)
- McKesson Corporation
- Oracle Corporation
- Veradigm, Inc.
- eClinicalWorks LLC
- CareCloud, Inc.
- Infinx, Inc.
- UnitedHealth Group, Inc. (Optum, Inc.)
- Experian Information Solutions, Inc. (Experian plc)
By Type
- Integrated
- Standalone
- Cloud-based
- Web-based
- On-premise
- Physician Back Offices
- Hospitals
- Diagnostic Laboratories
- Other End Use
- Claims Management
- Medical Coding & Charge Capture
- Financial Analytics & KPI Monitoring
- Payment Posting & Remittance
- Other Application
- Software
- Services
- US
- Canada
- Mexico
- Rest of North America
Table of Contents
185 Pages
- Chapter 1. Market Scope & Methodology
- 1.1 Market Definition
- 1.2 Objectives
- 1.3 Market Scope
- 1.4 Segmentation
- 1.4.1 North America AI In Revenue Cycle Management Market, by Type
- 1.4.2 North America AI In Revenue Cycle Management Market, by Delivery Mode
- 1.4.3 North America AI In Revenue Cycle Management Market, by End Use
- 1.4.4 North America AI In Revenue Cycle Management Market, by Application
- 1.4.5 North America AI In Revenue Cycle Management Market, by Product
- 1.4.6 North America AI In Revenue Cycle Management Market, by Country
- 1.5 Methodology for the research
- Chapter 2. Market at a Glance
- 2.1 Key Highlights
- Chapter 3. Market Overview
- 3.1 Introduction
- 3.1.1 Overview
- 3.1.1.1 Market Composition and Scenario
- 3.2 Key Factors Impacting the Market
- 3.2.1 Market Drivers
- 3.2.2 Market Restraints
- 3.2.3 Market Opportunities:
- 3.2.4 Market Challenges
- Chapter 4. Competition Analysis - Global
- 4.1 KBV Cardinal Matrix
- 4.2 Recent Industry Wide Strategic Developments
- 4.2.1 Partnerships, Collaborations and Agreements
- 4.2.2 Product Launches and Product Expansions
- 4.2.3 Acquisition and Mergers
- 4.3 Top Winning Strategies
- 4.3.1 Key Leading Strategies: Percentage Distribution (2021-2025)
- 4.3.2 Key Strategic Move: (Product Launches and Product Expansions : 2023, Feb – 2025, Apr) Leading Players
- 4.4 Porter Five Forces Analysis
- Chapter 5. Value Chain Analysis of AI In Revenue Cycle Management Market
- 5.1 Research & Development (R&D) and Innovation:
- 5.2 Data Aggregation & Preprocessing:
- 5.3 Product Development & Platform Engineering:
- 5.4 Marketing & Sales Enablement:
- 5.5 Implementation & Integration Services:
- 5.6 Operations & Support:
- 5.7 Outcomes Monitoring & Optimization:
- 5.8 Ecosystem Partnerships & Compliance:
- Chapter 6. Key Customer Criteria - AI In Revenue Cycle Management Market
- 6.1 Accuracy of AI Solutions
- 6.2 Integration Capability
- 6.3 Data Security & Compliance
- 6.4 Return on Investment (ROI) & Cost Efficiency
- 6.5 Ease of Use & Training Requirements
- 6.6 Scalability & Flexibility
- 6.7 Vendor Support & Reputation
- 6.8 Advanced Analytics & Reporting
- 6.9 Speed of Implementation
- 6.10. Customization and Localization
- Chapter 7. North America AI In Revenue Cycle Management Market by Type
- 7.1 North America Integrated Market by Region
- 7.2 North America Standalone Market by Region
- Chapter 8. North America AI In Revenue Cycle Management Market by Delivery Mode
- 8.1 North America Cloud-based Market by Country
- 8.2 North America Web-based Market by Country
- 8.3 North America On-premise Market by Country
- Chapter 9. North America AI In Revenue Cycle Management Market by End Use
- 9.1 North America Physician Back Offices Market by Country
- 9.2 North America Hospitals Market by Country
- 9.3 North America Diagnostic Laboratories Market by Country
- 9.4 North America Other End Use Market by Country
- Chapter 10. North America AI In Revenue Cycle Management Market by Application
- 10.1 North America Claims Management Market by Country
- 10.2 North America Medical Coding & Charge Capture Market by Country
- 10.3 North America Financial Analytics & KPI Monitoring Market by Country
- 10.4 North America Payment Posting & Remittance Market by Country
- 10.5 North America Other Application Market by Country
- Chapter 11. North America AI In Revenue Cycle Management Market by Product
- 11.1 North America Software Market by Country
- 11.2 North America Services Market by Country
- Chapter 12. North America AI In Revenue Cycle Management Market by Country
- 12.1 US AI In Revenue Cycle Management Market
- 12.1.1 US AI In Revenue Cycle Management Market by Type
- 12.1.2 US AI In Revenue Cycle Management Market by Delivery Mode
- 12.1.3 US AI In Revenue Cycle Management Market by End Use
- 12.1.4 US AI In Revenue Cycle Management Market by Application
- 12.1.5 US AI In Revenue Cycle Management Market by Product
- 12.2 Canada AI In Revenue Cycle Management Market
- 12.2.1 Canada AI In Revenue Cycle Management Market by Type
- 12.2.2 Canada AI In Revenue Cycle Management Market by Delivery Mode
- 12.2.3 Canada AI In Revenue Cycle Management Market by End Use
- 12.2.4 Canada AI In Revenue Cycle Management Market by Application
- 12.2.5 Canada AI In Revenue Cycle Management Market by Product
- 12.3 Mexico AI In Revenue Cycle Management Market
- 12.3.1 Mexico AI In Revenue Cycle Management Market by Type
- 12.3.2 Mexico AI In Revenue Cycle Management Market by Delivery Mode
- 12.3.3 Mexico AI In Revenue Cycle Management Market by End Use
- 12.3.4 Mexico AI In Revenue Cycle Management Market by Application
- 12.3.5 Mexico AI In Revenue Cycle Management Market by Product
- 12.4 Rest of North America AI In Revenue Cycle Management Market
- 12.4.1 Rest of North America AI In Revenue Cycle Management Market by Type
- 12.4.2 Rest of North America AI In Revenue Cycle Management Market by Delivery Mode
- 12.4.3 Rest of North America AI In Revenue Cycle Management Market by End Use
- 12.4.4 Rest of North America AI In Revenue Cycle Management Market by Application
- 12.4.5 Rest of North America AI In Revenue Cycle Management Market by Product
- Chapter 13. Company Profiles
- 13.1 R1 RCM, Inc. (TowerBrook Capital Partners L.P.)
- 13.1.1 Company Overview
- 13.1.2 Recent strategies and developments:
- 13.1.2.1 Partnerships, Collaborations, and Agreements:
- 13.1.2.2 Acquisition and Mergers:
- 13.2 Athenahealth, Inc. (Bain Capital, LP.)
- 13.2.1 Company overview
- 13.2.2 Recent strategies and developments:
- 13.2.2.1 Product Launches and Product Expansions:
- 13.3 McKesson Corporation
- 13.3.1 Company Overview
- 13.3.2 Financial Analysis
- 13.3.3 Segmental Analysis
- 13.3.4 Research & Development Expense
- 13.3.5 SWOT Analysis
- 13.4 Oracle Corporation
- 13.4.1 Company Overview
- 13.4.2 Financial Analysis
- 13.4.3 Segmental and Regional Analysis
- 13.4.4 Research & Development Expense
- 13.4.5 SWOT Analysis
- 13.5 Veradigm, Inc.
- 13.5.1 Company Overview
- 13.5.2 Recent strategies and developments:
- 13.5.2.1 Acquisition and Mergers:
- 13.5.3 SWOT Analysis
- 13.6 eClinicalWorks LLC
- 13.6.1 Company Overview
- 13.6.2 Recent strategies and developments:
- 13.6.2.1 Product Launches and Product Expansions:
- 13.7 CareCloud, Inc.
- 13.7.1 Company Overview
- 13.7.2 Financial Analysis
- 13.7.3 Segmental and Regional Analysis
- 13.7.4 Research & Development Expenses
- 13.7.5 Recent strategies and developments:
- 13.7.5.1 Partnerships, Collaborations, and Agreements:
- 13.7.5.2 Product Launches and Product Expansions:
- 13.8 Infinx, Inc.
- 13.8.1 Company Overview
- 13.8.2 Recent strategies and developments:
- 13.8.2.1 Product Launches and Product Expansions:
- 13.8.2.2 Acquisition and Mergers:
- 13.9 UnitedHealth Group, Inc. (Optum, Inc.)
- 13.9.1 Company Overview
- 13.9.2 Financial Analysis
- 13.9.3 Segmental Analysis
- 13.10. Experian Information Solutions, Inc. (Experian plc)
- 13.10.1 Company Overview
- 13.10.2 Financial Analysis
- 13.10.3 Regional Analysis
- 13.10.4 Recent strategies and developments:
- 13.10.4.1 Product Launches and Product Expansions:
- 13.10.5 SWOT Analysis
Pricing
Currency Rates
Questions or Comments?
Our team has the ability to search within reports to verify it suits your needs. We can also help maximize your budget by finding sections of reports you can purchase.