The Artificial Intelligence (AI) in Predictive Healthcare Analytics market is forecast to grow at a CAGR of 42.7%, reaching USD 62.1 billion in 2031 from USD 10.5 billion in 2026.
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.
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. 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 imaging 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.
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 ethical 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.
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 increase 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.
November 2025: VUNO Medical AI Company Reports Profit Driven by Predictive DeepCARS® Solution. South Korean medical AI company VUNO Inc. announced it achieved its first quarterly operating and net profit since its founding in 2014, driven by the commercial success of its flagship predictive solution, VUNO Med®–DeepCARS®. This AI-powered device predicts the risk of in-hospital cardiac arrest up to 24 hours in advance. The product, which holds FDA Breakthrough Device Designation (BDD), is currently deployed across over 50,000 hospital beds in South Korea and is actively pursuing CE-MDR certification in Europe and FDA clearance in the U.S., demonstrating the growing commercial viability of predictive AI in critical care.
November 2025: American Heart Association Releases New Guidance for Responsible AI Use in Clinical Care. The American Heart Association (AHA) released a new science advisory urging health systems to adopt clear and simple rules for deploying AI tools in patient care. The advisory, published in Circulation, introduced a pragmatic, risk-based framework for evaluating and monitoring AI in cardiovascular and stroke care. It emphasizes the need for local validation and bias assessment to ensure AI tools deliver measurable clinical benefits while preventing known and unknown patient harms, establishing new clinical standards for the responsible integration of predictive analytics.
August 2025: FDA Finalizes Guidance on AI Device Software Modifications. The U.S. Food and Drug Administration (FDA) issued its final guidance on "Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions." This guidance formalizes a pathway for companies to iteratively improve and modify their AI-enabled medical devices, including predictive analytics tools, without submitting a new marketing application for every single change, thereby accelerating the development and deployment of safe and effective AI in healthcare.
IBM Corporation
Microsoft Corporation
Google LLC (Alphabet Inc.)
SAS Institute Inc.
Oracle Corporation
| Report Metric | Details |
|---|---|
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 – 2031 |
| Companies |
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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