Artificial Intelligence (AI) In Epidemiology Market Size, Share, Growth, Trends, and Global Industry Analysis: By Component (Software, Services, Hardware), By Deployment Type (Cloud-based, On-premises), By Application (Disease Surveillance, Outbreak Prediction & Detection, Contact Tracing, Risk Assessment, Health Trend Forecasting, Public Health Resource Allocation, Others), By End User (Government & Public Health Agencies, Hospitals & Clinics, Research Institutions, Pharmaceutical & Biotech Companies, Academic Institutions, Others) and Region Forecast 2020-2031

Artificial Intelligence (AI) In Epidemiology Market size was valued at US$ 650.0 million in 2024 and is expected to reach US$ 2,660.1 million by 2031, growing at a significant CAGR of 22.3% from 2025-2031. Moreover, the U.S. Artificial Intelligence (AI) In Epidemiology Market is projected to grow at a CAGR of 24% over the forecast period. The market refers to the sector focused on the application of AI technologies such as machine learning, deep learning, and natural language processing to the study and management of disease patterns, causes, and effects in populations. This market encompasses AI-powered tools used for disease surveillance, outbreak prediction, risk assessment, contact tracing, and epidemiological modelling. It integrates large-scale health data from clinical, genomic, and environmental sources to support real-time decision-making in public health research, policy formulation, and disease control strategies.

The market is gaining significant traction as global healthcare systems increasingly rely on data-driven tools to detect, monitor, and mitigate disease outbreaks. With the growing frequency of epidemics and pandemics, AI enables faster, and more accurate modelling of disease spread, early identification of at-risk populations, and targeted intervention strategies. Governments, research institutions, and health organizations are actively investing in AI platforms that enhance surveillance and prediction capabilities. The combination of big data analytics and AI is transforming epidemiology from a traditionally reactive field to a more proactive, preventive discipline, thereby expanding the scope and impact of public health intelligence.

Facts & Figures

• In fact, over 80% of global public health agencies in high-income countries have adopted or piloted AI tools for disease surveillance and outbreak response.
• AI models can predict infectious disease outbreaks up to 2–3 weeks in advance with accuracy rates exceeding 85%, depending on data quality and region.
• AI-powered contact tracing apps reduced transmission rates by 15–35% during the peak of COVID-19 in countries like South Korea, Singapore, and Germany.
• More than 60 countries globally have incorporated AI tools in national health data systems or epidemic response frameworks post-2020.
• A single AI-based outbreak detection platform can process over 10 million data points per day, including social media trends, mobility data, and clinical reports.
• AI integration in genomic surveillance has reduced pathogen sequencing time by up to 50%, enhancing real-time variant tracking and mutation analysis.

Key Developments:

• In June 2024, Oracle released its Clinical Digital Assistant in the U.S., a generative?AI–enabled tool integrated with electronic health records (EHR), designed to support ambulatory clinics by automating clinical workflows and documentation.

Artificial Intelligence (AI) In Epidemiology Market Segmentation:

Based on the component:

• Software
• Services
• Hardware

Among the components, Software is anticipated to lead the AI in Epidemiology market due to its central role in enabling data processing, predictive modelling, and real-time analytics. AI-powered software platforms are essential for interpreting complex epidemiological data, such as disease spread patterns, demographic risk factors, and genomic sequences. These tools help researchers and public health officials make faster, evidence-based decisions during outbreaks. With the rise in cloud-based platforms, software solutions are becoming more scalable and accessible, especially in developing regions. The increasing demand for customizable, AI-driven applications in surveillance and outbreak forecasting positions software as the dominant segment in the market.

Based on the deployment type:

• Cloud-based
• On-premises

Among the deployment types, Cloud-based solutions are anticipated to lead the AI in Epidemiology market. Cloud deployment offers greater flexibility, scalability, and cost-efficiency, allowing real-time access to large volumes of epidemiological data from multiple sources and locations. These solutions are particularly valuable during disease outbreaks, enabling faster collaboration between healthcare institutions, public health agencies, and research centres. With the increased adoption of mobile health platforms and remote monitoring systems, cloud-based AI tools support dynamic data integration and predictive analytics on a global scale. Their ability to rapidly deploy and update AI models makes them the preferred choice for modern epidemiological applications.

Based on the application:

• Disease Surveillance
• Outbreak Prediction & Detection
• Contact Tracing
• Risk Assessment
• Health Trend Forecasting
• Public Health Resource Allocation
• Others

Among the applications, Outbreak Prediction & Detection is expected to lead the AI in Epidemiology market, owing to its critical role in early response and containment of infectious diseases. AI algorithms can analyze vast datasets from multiple sources such as hospital records, travel data, climate conditions, and social media to identify abnormal patterns that may indicate the emergence or spread of an outbreak.

This application has gained momentum following the COVID-19 pandemic, where AI tools significantly contributed to tracking and anticipating virus surges. Governments and health organizations are increasingly investing in predictive systems to avoid delayed responses and resource strain. The rising frequency of pandemics, coupled with the demand for proactive health interventions, positions outbreak prediction as the most impactful and widely adopted use case in the market.

Based on the end user:

• Government & Public Health Agencies
• Hospitals & Clinics
• Research Institutions
• Pharmaceutical & Biotech Companies
• Academic Institutions
• Others

Among the end users, Government & Public Health Agencies are anticipated to lead the AI in Epidemiology market due to their central role in disease surveillance, outbreak management, and population health planning. These agencies rely heavily on AI tools to process large-scale public health data, predict disease spread, and allocate resources efficiently during health emergencies. National and international bodies, such as the CDC and WHO, have increasingly integrated AI into their surveillance systems to enhance decision-making and policy development. With growing global concerns about pandemic preparedness and biosecurity, government agencies are investing in advanced AI platforms, positioning them as the dominant market segment.