Product Code: GVR-4-68040-145-8
AI In Patient Engagement Market Growth & Trends:
The global AI in patient engagement market size is expected to reach USD 23.1 billion by 2030, registering a CAGR of 21.2% from 2024 to 2030, according to a new report by Grand View Research, Inc. The market is driven by the growing demand for AI-based personalized treatment plans and healthcare experiences and the emergence of digital platforms and necessity for omnichannel approach. In addition, the increasing role of artificial intelligence (AI) in enhancing pharmacy efficiency and managing supply chain complexities and business strategies by market players is also driving the market growth. For instance, in May 2024, EmpiRx Health introduced Clinically, a new AI-powered platform that incorporates established technologies. This platform enhances pharmacy claims processing and clinical evaluations and includes a unique population health engine, reinforcing EmpiRx Health's clinical-focused Pharmacy Benefit Management (PBM) approach.
Moreover, the growing prevalence of chronic diseases, such as diabetes and hypertension, necessitates continuous patient engagement & management, which AI can effectively facilitate. Furthermore, AI technologies such as machine learning and natural language processing (NLP) can significantly enhance patient engagement by providing personalized support & interventions. These technologies analyze patient data to offer tailored recommendations, reminders, & educational content, improving adherence and health outcomes. For instance, in March 2022, Uniphore entered into a strategic partnership with SpinSci Technologies, a provider of digital patient engagement solutions, to improve patient access and interaction with healthcare providers. This collaboration integrated Uniphore's conversational AI and automation technology into SpinSci Technologies Patient Access Care solutions, which are compatible with Electronic Health Records (EHR) systems. The integration aimed to enhance efficiency for contact center agents and streamline patient self-service workflows.
The integration of AI enables healthcare organizations to deliver tailored educational content based on individual patient preferences, health literacy levels, and language proficiency, thereby improving patient engagement & adherence to treatment plans. For instance, in February 2024, Ascend, a startup platform backed by the Accolade Group, announced its intention to deliver educational and healthcare services tailored to specific requirements utilizing AI. As a result of such initiatives, the patient education functionality segment is expected to witness substantial growth, driving overall market expansion in the coming years.
In addition, the market in North America is driven by the integration of AI, enabling healthcare organizations to deliver tailored educational content based on individual patient preferences, health literacy levels, and language proficiency, thereby improving patient engagement & adherence to treatment plans. For instance, in February 2024, Ascend, a startup platform backed by the Accolade Group, announced its intention to deliver educational and healthcare services tailored to specific requirements utilizing AI. As a result of such initiatives, the patient education functionality segment is expected to witness substantial growth, driving overall market expansion in the coming years.
AI In Patient Engagement Market Report Highlights:
- On the basis of delivery mode, the cloud-based segment dominated the market and held a revenue share of 72.37% in 2023. Cloud-based solutions provide scalable resources, enabling healthcare organizations to adjust capacity according to demand fluctuations
- On the basis of functionality, enhanced communication held the largest revenue share of 25.84% in 2023. The growing integration of AI-driven solutions in the healthcare sector is driving the need for enhanced communication capabilities
- On the basis of technology, Natural Language Processing (NLP) held the largest revenue share of 88.82% in 2023. The segment growth can be attributed to several benefits offered by NLP models such as improved patient engagement and education through the provision of tailored & comprehensible health information
- On the basis of therapeutic area, chronic disease management held the largest revenue share of 64.87% in 2023. The segment growth can be attributed to the increasing prevalence of chronic conditions such as diabetes, hypertension, and heart disease
- On the basis of end use, the healthcare providers segment held the largest revenue share of 38.31% in 2023. The increasing focus on patient-centric care, coupled with the growing need for effective use of resources and a rising demand for personalized healthcare experiences, is driving healthcare providers to adopt AI for patient engagement
- North America dominated the market with a share of 43.60% in 2023. Key factors contributing to this notable share include the presence of a well-established healthcare infrastructure equipped with advanced technology, increasing awareness of the advantages of integrating AI-enabled patient engagement solutions, and a growing preference for personalized healthcare experiences & treatment plans
- The market is fragmented owing to the presence of several players. This is expected to intensify the competition in the coming years. Key companies are increasingly adopting strategies such as new product development, collaborations, and mergers & acquisitions to strengthen their market position. In June 2024, MedAdvisor Solutions announced the launch of Omnichannel Engagement for Pharmacy powered by THRiV, its AI-enabled platform. This suite enables pharmacies to enhance their digital patient engagement strategies and existing initiatives, including providing paperless options increasingly preferred by patients
Table of Contents
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.1.1. Technology
- 1.1.2. Therapeutic Area
- 1.1.3. Functionality
- 1.1.4. Delivery Type
- 1.1.5. End Use
- 1.2. Research Methodology
- 1.3. Information Procurement
- 1.3.1. Purchased database.
- 1.3.2. GVR's internal database
- 1.3.3. Secondary sources
- 1.3.4. Primary research
- 1.3.5. Details of primary research
- 1.4. Information or Data Analysis
- 1.4.1. Data analysis models
- 1.5. Market Formulation & Validation
- 1.6. Model Details
- 1.6.1. Commodity flow analysis (Model 1)
- 1.6.2. Approach 1: Commodity flow approach
- 1.6.3. Volume price analysis (Model 2)
- 1.6.4. Approach 2: Volume price analysis
- 1.7. List of Secondary Sources
- 1.8. List of Primary Sources
- 1.9. Objectives
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.2.1. Technology Outlook
- 2.2.2. Therapeutic Area Outlook
- 2.2.3. Functionality Outlook
- 2.2.4. Delivery Outlook
- 2.2.5. End Use Outlook
- 2.2.6. Regional outlook
- 2.3. Competitive Insights
Chapter 3. Artificial Intelligence (AI) in Patient Engagement 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
- 3.3. Artificial Intelligence (AI) in Patient Engagement Market Analysis Tools
- 3.3.1. Industry Analysis - Porter's
- 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
- 3.3.3. Impact of COVID-19
- 3.3.4. Case Study
Chapter 4. Artificial Intelligence (AI) in Patient Engagement Market Delivery Type Estimates & Trend Analysis
- 4.1. Delivery Type Market Share, 2023 & 2030
- 4.2. Segment Dashboard
- 4.3. Global Artificial Intelligence (AI) in Patient Engagement Market by Delivery Type Outlook
- 4.4. Cloud-based
- 4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 4.5. On-premise
- 4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 5. Artificial Intelligence (AI) in Patient Engagement Market Functionality Estimates & Trend Analysis
- 5.1. Functionality Market Share, 2023 & 2030
- 5.2. Segment Dashboard
- 5.3. Global Artificial Intelligence (AI) in Patient Engagement Market by Functionality Outlook
- 5.4. Enhanced Communication
- 5.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.5. Patient Education
- 5.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.6. Chabot & Virtual Health Assistants
- 5.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.7. Predictive Analytics
- 5.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.8. Administrative & Streamlined Operations
- 5.8.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 5.9. Others
- 5.9.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 6. Artificial Intelligence (AI) in Patient Engagement Market Technology Type Estimates & Trend Analysis
- 6.1. Technology Type Market Share, 2023 & 2030
- 6.2. Segment Dashboard
- 6.3. Global Artificial Intelligence (AI) in Patient Engagement Market by Technology Type Outlook
- 6.4. NLP
- 6.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.2. Smart Assistance
- 6.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.3. Optical Character Recognition (OCR)
- 6.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.4. Auto Coding
- 6.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.5. Text Analytics
- 6.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.6. Speech Analytics
- 6.4.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.4.7. Classification & Categorization
- 6.4.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.5. Others
- 6.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 6.5.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 7. Artificial Intelligence (AI) in Patient Engagement Market Therapeutic Area Estimates & Trend Analysis
- 7.1. Therapeutic Area Market Share, 2023 & 2030
- 7.2. Segment Dashboard
- 7.3. Global Artificial Intelligence (AI) in Patient Engagement Market by Therapeutic Area Outlook
- 7.4. Health & Wellness
- 7.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 7.5. Chronic Disease Management
- 7.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 7.6. Others
- 7.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 8. Artificial Intelligence (AI) in Patient Engagement Market End Use Estimates & Trend Analysis
- 8.1. End Use Market Share, 2023 & 2030
- 8.2. Segment Dashboard
- 8.3. Global Artificial Intelligence (AI) in Patient Engagement Market by End Use Outlook
- 8.4. Healthcare Provider
- 8.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 8.5. Healthcare Payers
- 8.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 8.6. Others
- 8.6.1. Pharmaceutical Companies
- 8.6.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
- 8.6.2. Pharmacy
- 8.6.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 9. Artificial Intelligence (AI) in Patient Engagement Market Regional Estimates & Trend Analysis, By Component, By Technology Type
- 9.1. Regional Market Share Analysis, 2023 & 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. U.S.
- 9.5.1.1. Key country dynamics
- 9.5.1.2. Regulatory framework/ reimbursement structure
- 9.5.1.3. Competitive scenario
- 9.5.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
- 9.5.2. Canada
- 9.5.2.1. Key country dynamics
- 9.5.2.2. Regulatory framework/ reimbursement structure
- 9.5.2.3. Competitive scenario
- 9.5.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
- 9.5.3. Mexico
- 9.5.3.1. Key country dynamics
- 9.5.3.2. Regulatory framework/ reimbursement structure
- 9.5.3.3. Competitive scenario
- 9.5.3.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6. Europe
- 9.6.1. UK
- 9.6.1.1. Key country dynamics
- 9.6.1.2. Regulatory framework/ reimbursement structure
- 9.6.1.3. Competitive scenario
- 9.6.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.2. Germany
- 9.6.2.1. Key country dynamics
- 9.6.2.2. Regulatory framework/ reimbursement structure
- 9.6.2.3. Competitive scenario
- 9.6.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.3. France
- 9.6.3.1. Key country dynamics
- 9.6.3.2. Regulatory framework/ reimbursement structure
- 9.6.3.3. Competitive scenario
- 9.6.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.4. Italy
- 9.6.4.1. Key country dynamics
- 9.6.4.2. Regulatory framework/ reimbursement structure
- 9.6.4.3. Competitive scenario
- 9.6.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.5. Spain
- 9.6.5.1. Key country dynamics
- 9.6.5.2. Regulatory framework/ reimbursement structure
- 9.6.5.3. Competitive scenario
- 9.6.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.6. Norway
- 9.6.6.1. Key country dynamics
- 9.6.6.2. Regulatory framework/ reimbursement structure
- 9.6.6.3. Competitive scenario
- 9.6.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.7. Sweden
- 9.6.7.1. Key country dynamics
- 9.6.7.2. Regulatory framework/ reimbursement structure
- 9.6.7.3. Competitive scenario
- 9.6.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
- 9.6.8. Denmark
- 9.6.8.1. Key country dynamics
- 9.6.8.2. Regulatory framework/ reimbursement structure
- 9.6.8.3. Competitive scenario
- 9.6.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
- 9.7. Asia Pacific
- 9.7.1. Japan
- 9.7.1.1. Key country dynamics
- 9.7.1.2. Regulatory framework/ reimbursement structure
- 9.7.1.3. Competitive scenario
- 9.7.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
- 9.7.2. China
- 9.7.2.1. Key country dynamics
- 9.7.2.2. Regulatory framework/ reimbursement structure
- 9.7.2.3. Competitive scenario
- 9.7.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
- 9.7.3. India
- 9.7.3.1. Key country dynamics
- 9.7.3.2. Regulatory framework/ reimbursement structure
- 9.7.3.3. Competitive scenario
- 9.7.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
- 9.7.4. Australia
- 9.7.4.1. Key country dynamics
- 9.7.4.2. Regulatory framework/ reimbursement structure
- 9.7.4.3. Competitive scenario
- 9.7.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
- 9.7.5. South Korea
- 9.7.5.1. Key country dynamics
- 9.7.5.2. Regulatory framework/ reimbursement structure
- 9.7.5.3. Competitive scenario
- 9.7.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
- 9.7.6. Singapore
- 9.7.6.1. Key country dynamics
- 9.7.6.2. Regulatory framework/ reimbursement structure
- 9.7.6.3. Competitive scenario
- 9.7.6.4. Singapore market estimates and forecasts 2018 to 2030 (USD Million)
- 9.8. Latin America
- 9.8.1. Brazil
- 9.8.1.1. Key country dynamics
- 9.8.1.2. Regulatory framework/ reimbursement structure
- 9.8.1.3. Competitive scenario
- 9.8.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
- 9.8.2. Argentina
- 9.8.2.1. Key country dynamics
- 9.8.2.2. Regulatory framework/ reimbursement structure
- 9.8.2.3. Competitive scenario
- 9.8.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
- 9.9. MEA
- 9.9.1. South Africa
- 9.9.1.1. Key country dynamics
- 9.9.1.2. Regulatory framework/ reimbursement structure
- 9.9.1.3. Competitive scenario
- 9.9.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
- 9.9.2. Saudi Arabia
- 9.9.2.1. Key country dynamics
- 9.9.2.2. Regulatory framework/ reimbursement structure
- 9.9.2.3. Competitive scenario
- 9.9.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
- 9.9.3. UAE
- 9.9.3.1. Key country dynamics
- 9.9.3.2. Regulatory framework/ reimbursement structure
- 9.9.3.3. Competitive scenario
- 9.9.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
- 9.9.4. Kuwait
- 9.9.4.1. Key country dynamics
- 9.9.4.2. Regulatory framework/ reimbursement structure
- 9.9.4.3. Competitive scenario
- 9.9.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)
Chapter 10. Competitive Landscape
- 10.1. Recent Developments & Impact Analysis, By Key Market Participants
- 10.2. Company/Competition Categorization
- 10.3. Innovators
- 10.4. Vendor Landscape
- 10.4.1. Key company market position analysis, 2023
- 10.4.2. Medadvisor Solutions
- 10.4.2.1. Company overview
- 10.4.2.2. Financial performance
- 10.4.2.3. Product benchmarking
- 10.4.2.4. Strategic initiatives
- 10.4.3. Innovaccer Inc.
- 10.4.3.1. Company overview
- 10.4.3.2. Financial performance
- 10.4.3.3. Product benchmarking
- 10.4.3.4. Strategic initiatives
- 10.4.4. EnlivenHealth (Omnicell)
- 10.4.4.1. Company overview
- 10.4.4.2. Financial performance
- 10.4.4.3. Product benchmarking
- 10.4.4.4. Strategic initiatives
- 10.4.5. EmpiRx Health
- 10.4.5.1. Company overview
- 10.4.5.2. Financial performance
- 10.4.5.3. Product benchmarking
- 10.4.5.4. Strategic initiatives
- 10.4.6. IBM.
- 10.4.6.1. Company overview
- 10.4.6.2. Financial performance
- 10.4.6.3. Product benchmarking
- 10.4.6.4. Strategic initiatives
- 10.4.7. Huma
- 10.4.7.1. Company overview
- 10.4.7.2. Financial performance
- 10.4.7.3. Product benchmarking
- 10.4.7.4. Strategic initiatives
- 10.4.8. mPulse Mobile
- 10.4.8.1. Company overview
- 10.4.8.2. Financial performance
- 10.4.8.3. Product benchmarking
- 10.4.8.4. Strategic initiatives
- 10.4.9. AllazoHealth
- 10.4.9.1. Company overview
- 10.4.9.2. Financial performance
- 10.4.9.3. Product benchmarking
- 10.4.9.4. Strategic initiatives
- 10.4.10. P360
- 10.4.10.1. Company overview
- 10.4.10.2. Financial performance
- 10.4.10.3. Product benchmarking
- 10.4.10.4. Strategic initiatives
- 10.4.11. Brand Engagement Network, Inc.
- 10.4.11.1. Company overview
- 10.4.11.2. Financial performance
- 10.4.11.3. Product benchmarking
- 10.4.11.4. Strategic initiatives
- 10.4.12. Oracle
- 10.4.12.1. Company overview
- 10.4.12.2. Financial performance
- 10.4.12.3. Product benchmarking
- 10.4.12.4. Strategic initiatives
- 10.4.13. Nuance Communications Inc. (Microsoft)
- 10.4.13.1. Company overview
- 10.4.13.2. Financial performance
- 10.4.13.3. Product benchmarking
- 10.4.13.4. Strategic initiatives
- 10.4.14. Health Catalyst
- 10.4.14.1. Company overview
- 10.4.14.2. Financial performance
- 10.4.14.3. Product benchmarking
- 10.4.14.4. Strategic initiatives
- 10.4.15. Ada Health GmbH
- 10.4.15.1. Company overview
- 10.4.15.2. Financial performance
- 10.4.15.3. Product benchmarking
- 10.4.15.4. Strategic initiatives
- 10.4.16. Aiva Inc.
- 10.4.16.1. Company overview
- 10.4.16.2. Financial performance
- 10.4.16.3. Product benchmarking
- 10.4.16.4. Strategic initiatives
- 10.4.17. Claritas Rx
- 10.4.17.1. Company overview
- 10.4.17.2. Financial performance
- 10.4.17.3. Product benchmarking
- 10.4.17.4. Strategic initiatives
- 10.4.18. AiCure
- 10.4.18.1. Company overview
- 10.4.18.2. Financial performance
- 10.4.18.3. Product benchmarking
- 10.4.18.4. Strategic initiatives
- 10.4.19. UST Global Inc.
- 10.4.19.1. Company overview
- 10.4.19.2. Financial performance
- 10.4.19.3. Product benchmarking
- 10.4.19.4. Strategic initiatives
- 10.4.20. ZS
- 10.4.20.1. Company overview
- 10.4.20.2. Financial performance
- 10.4.20.3. Product benchmarking
- 10.4.20.4. Strategic initiatives
- 10.4.21. IQVIA, Inc.
- 10.4.21.1. Company overview
- 10.4.21.2. Financial performance
- 10.4.21.3. Product benchmarking
- 10.4.21.4. Strategic initiatives