Artificial Intelligence (AI) In Predictive Healthcare Analytics Market Size, Share, Opportunities, And Trends By Deployment Mode (Cloud-Based, On-Premise), By Application (Patient Risk Stratification, Disease Diagnosis And Prognosis, Population Health Management, Fraud Detection, Supply, Chain Management, Others), By End-User (Hospitals And Clinics, Healthcare Payers, Pharmaceutical And Biotechnology Companies, Research Institutes And Academic Centers, Others), And By Geography - Forecasts From 2024 To 2029

Artificial intelligence (AI) in the predictive healthcare analytics market is expected to grow at a CAGR of 41.56%, reaching a market size of US$29.360 billion in 2029 and US$5.165 billion in 2024.

The implementation of Artificial Intelligence (AI) in predictive healthcare analytics is an interesting and growing topic in hospitals and healthcare facilities. In preventive care solutions, predictive analytics, integration of healthcare analytics, and AI utilize the patient's health information, predict health risks to the population in the future, and propose interventions.

Further, artificial intelligence predictive modeling, also known as predictive modeling, is the most extensively utilized form of AI. AI evaluates the integrated data of millions of genetic, phenotypic, and lifestyle electronic health records (EHR) to predict impending disease attacks, possible readmission, and a patient’s response to an intervention. This predictive capacity benefits the healthcare system by enabling the service providers to act and design the processes even before any illness appears, which is a cost-effective way of improving the services. The market for AI in predictive healthcare analytics is quite optimistic. It envisions the transformation of healthcare delivery through strategic resolution-making, enhancing prevention, and even the positive development of individualized care treatment.

What are the artificial intelligence (AI) in the predictive healthcare analytics market growth drivers?

• Advancements in AI technologies are increasing the Artificial Intelligence (AI) In predictive healthcare analytics market growth.

Progress in the application of AI has been one of the major reasons for AI in the predictive healthcare analytics market growth. This development encompasses many things, most notably machine learning, natural language processing, and computer vision, among others. This progression enables the AI processes to conduct severe and extensive analysis of enormous and complex volumes of medical-related information such as patient history, genome sequencing, and even imagery diagnostics.

It empowers healthcare system stakeholders to predict disease outcomes, analyze risk factors, and customize treatment methodologies, thus changing the decision-making processes in healthcare. The growing precision and performance of AI-based prediction models have led to an increased use of these models by health providers and researchers. There is a possibility of alterations in healthcare analytics, enhancement of the patient's well-being as advocated by the trends, and a commendable shift to preventive and information-based treatments due to the growth in AI technologies.

• Growing emphasis on personalized and precision medicine enhances the AI in predictive healthcare analytics market growth

The rising trend of personalized and precision medicine is a key driver for the growing adoption of AI in predictive healthcare analytics. Healthcare providers are beginning to appreciate individual genetic and behavioral variables that influence health outcomes. With advancements in data and predictive analytics, it is now possible to incorporate genomics and medical records and even tailor a patient’s lifestyle to generate predictive models. This paradigm shift from a one-size-fits-all way of prescribing medicine to personally prescribed medicine is enabling more targeted medicines, more effective prevention of diseases, and improved healthcare outcomes. In such an environment, predictive analytics assumes special significance for adjusting treatment protocols for various diagnoses and providing individualized care.

• Demand for efficient patient risk stratification and disease prediction boosts AI in the predictive healthcare analytics market

The need for precision in estimating patient risk factors and predicting illnesses plays a pivotal role in AI in the predictive healthcare analytics market. Healthcare professionals are in search of ways to detect high-risk patients and predict the progression of diseases early to provide appropriate interventions and prevent adverse effects. AI and data analytics are used in predictive healthcare analytics to analyze large patient datasets, detecting patterns and risk factors related to certain diseases. By accurately forecasting the course of diseases and their outcomes, health practitioners can modify treatment methodologies, control resources better, and enhance the quality of patient care. The ability to mitigate health threats enhances patient safety and reduces the cost of care, explaining AI in the predictive analytics market growth in the healthcare industry.

Artificial intelligence (AI) in predictive healthcare analytics market restraints:

• High costs and increased cases of data breaches are anticipated to impede market growth

Even with all its prospective benefits in healthcare, AI remains underutilized in this segment. The intricacy that healthcare providers face is to blame for this. Mistakes can cause variances between a patient’s treatment medications and the assessment. Other problems related to the artificial intelligence application in health care include the unavailability of quality health records, job performance metrics that are clinically irrelevant, methodological issues in the studies, data collection challenges, and ethics and societal issues. Data privacy concerns are yet another impediment to the increasing popularity of AI in the healthcare industry. Several countries have enacted laws meant to protect their citizens' health information. Violating this policy may attract fines or prosecution, among other penalties.

Additionally, issues like the unethical collection of private information raise concerns about the security of patient data. As a result, growing worries about patient safety and unethical patient data collection are impeding the market's overall expansion.

What are the key geographical trends shaping the artificial intelligence (AI) in the predictive healthcare analytics market?

• North America is witnessing exponential growth during the forecast period

North America was anticipated to retain its market leadership in AI in the predictive healthcare analytics market. This is due to the extensive use and growth of healthcare analytics and predictive modeling AI technology within the United States healthcare system. North America's continued dominance is also ascribed to its well-established healthcare facilities, high investment in AI projects, and presence of prominent health technology corporations.

Moreover, enhanced patient-centered healthcare and precision medicine in the region also increases the use of AI-based predictive analytics to leverage patient outcomes, maximize resource utilization, and elevate healthcare services. The developments in artificial intelligence technology in predictive healthcare are one of the factors that will guarantee that North America will continue to lead in the AI in predictive healthcare analytics market.

Recent developments in the artificial intelligence (AI) in the predictive healthcare analytics market

• In June 2023, Health Catalyst, Inc., a provider of data and analytics technology solutions and services for healthcare institutions, extended its collaboration with the Ohio Health Information Partnership (The Partnership), which runs CliniSync, a Health Information Exchange focused on enabling patient record sharing in Ohio.
• In October 2023, Innovations MUUTAA Inc., an emerging creator of AI deep learning solutions for healthcare supply chains focused on patient-driven demand, partnered with Mila-Quebec AI Institute, the world’s largest academic Deep Learning (DL) research center.

Artificial Intelligence (AI) In Predictive Healthcare Analytics Market Scope:

Report Metric	Details
AI in Predictive Healthcare Analytics Market Size in 2024	US$5.165 billion
AI in Predictive Healthcare Analytics Market Size in 2029	US$29.360 billion
Growth Rate	CAGR of 41.56%
Study Period	2019 to 2029
Historical Data	2019 to 2022
Base Year	2024
Forecast Period	2024 – 2029
Forecast Unit (Value)	USD Billion
Segmentation	Deployment Mode Application End-User Geography
Geographical Segmentation	North America, South America, Europe, Middle East and Africa, Asia Pacific
List of Major Companies in AI in Predictive Healthcare Analytics Market	Ibm Corporation Microsoft Corporation Google Llc (Alphabet Inc.) Sas Institute Inc. Oracle Corporation
Customization Scope	Free report customization with purchase

 

The Artificial Intelligence (AI) In predictive healthcare analytics market is segmented and analyzed as follows:

• By Deployment Mode
  • Cloud-Based
  • On-Premise      
• By Application
  • Patient Risk Stratification
  • Disease Diagnosis And Prognosis
  • Population Health Management
  • Fraud Detection
  • Supply Chain Management
  • Others    
• By End-User
  • Hospitals And Clinics
  • Healthcare Payers
  • Pharmaceutical And Biotechnology Companies
  • Research Institutes And Academic Centers
  • Others                
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain    
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • Japan
    • China
    • India
    • South Korea
    • Indonesia
    • Taiwan
    • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. CXO Perspective

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. ARTIFICIAL INTELLIGENCE (AI) IN PREDICTIVE HEALTHCARE ANALYTICS MARKET BY DEPLOYMENT MODE

5.1. Introduction

5.2. Cloud-Based

5.3. On-Premise 

6. ARTIFICIAL INTELLIGENCE (AI) IN PREDICTIVE HEALTHCARE ANALYTICS MARKET BY APPLICATION

6.1. Introduction

6.2. Patient Risk Stratification

6.3. Disease Diagnosis And Prognosis

6.4. Population Health Management

6.5. Fraud Detection

6.6. Supply Chain Management

6.7. Others 

7. ARTIFICIAL INTELLIGENCE (AI) IN PREDICTIVE HEALTHCARE ANALYTICS MARKET BY END-USER

7.1. Introduction

7.2. Hospitals And Clinics

7.3. Healthcare Payers

7.4. Pharmaceutical And Biotechnology Companies

7.5. Research Institutes And Academic Centers

7.6. Others 

8. ARTIFICIAL INTELLIGENCE (AI) IN PREDICTIVE HEALTHCARE ANALYTICS MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By Deployment Mode

8.2.2. By Application

8.2.3. BY End-User

8.2.4. By Country

8.2.4.1. United States

8.2.4.2. Canada

8.2.4.3. Mexico

8.3. South America

8.3.1. By Deployment Mode

8.3.2. By Application

8.3.3. BY End-User

8.3.4. By Country

8.3.4.1. Brazil

8.3.4.2. Argentina

8.3.4.3. Others

8.4. Europe

8.4.1. By Deployment Mode

8.4.2. By Application

8.4.3. BY End-User

8.4.4. By Country

8.4.4.1. United Kingdom

8.4.4.2. Germany

8.4.4.3. France

8.4.4.4. Italy

8.4.4.5. Spain

8.4.4.6. Others

8.5. Middle East and Africa

8.5.1. By Deployment Mode

8.5.2. By Application

8.5.3. BY End-User

8.5.4. By Country

8.5.4.1. Saudi Arabia

8.5.4.2. UAE

8.5.4.3. Others

8.6. Asia Pacific

8.6.1. By Deployment Mode

8.6.2. By Application

8.6.3. BY End-User

8.6.4. By Country

8.6.4.1. Japan

8.6.4.2. China

8.6.4.3. India

8.6.4.4. South Korea

8.6.4.5. Indonesia

8.6.4.6. Taiwan

8.6.4.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisitions, Agreements, and Collaborations

9.4. Competitive Dashboard

10. COMPANY PROFILES

10.1. Ibm Corporation

10.2. Microsoft Corporation

10.3. Google Llc (Alphabet Inc.)

10.4. Sas Institute Inc.

10.5. Oracle Corporation

10.6. Cerner Corporation

10.7. Allscripts Healthcare Solutions, Inc.

10.8. Medeanalytics, Inc.

10.9. Ayasdi, Inc.

10.10. Health Catalyst, Inc.   

Ibm Corporation

Microsoft Corporation

Google Llc (Alphabet Inc.)

Sas Institute Inc.

Oracle Corporation

Cerner Corporation

Allscripts Healthcare Solutions, Inc.

Medeanalytics, Inc.

Ayasdi, Inc.

Health Catalyst, Inc.