by The global artificial intelligence (AI) in epidemiology market size is expected to increase USD 6,025.53 billion by 2033 from USD 548.99 billion in 2023 with a CAGR of 27.07% between 2024 and 2033.
Key Points
- North America dominated the artificial intelligence (AI) in epidemiology market in 2023.
- Europe is expected to grow at a notable rate in the market during the forecast period.
- By deployment, the cloud-based segment will dominate the market in 2023.
- By deployment, the web-based segment is expected to grow at the highest CAGR in the market during the forecast period.
- By application, the prediction & forecasting segment dominated the market in 2023.
- By application, the disease & syndromic surveillance segment is expected to grow at the highest CAGR in the market during the forecast period.
- By end-use, the pharmaceuticals and biotechnology companies segment dominated the market in 2023.
- By end-use, the research labs segment is expected to grow at a significant CAGR in the market during the forecast period.
Artificial Intelligence (AI) has emerged as a transformative technology in various sectors, and its application in epidemiology is rapidly gaining momentum. AI in epidemiology refers to the utilization of machine learning algorithms and data analytics techniques to analyze vast amounts of epidemiological data. This includes data related to disease outbreaks, public health trends, and healthcare disparities among populations. The integration of AI in epidemiology aims to enhance disease surveillance, improve predictive modeling for outbreaks, and optimize resource allocation in healthcare systems.
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Growth Factors
The growth of AI in epidemiology is fueled by several key factors. Firstly, the exponential increase in digital health data availability, including electronic health records (EHRs), genomic data, and wearable device data, provides a rich source of information for AI algorithms to analyze. Secondly, advancements in machine learning algorithms, such as deep learning and natural language processing, enable more accurate and efficient analysis of complex epidemiological datasets. Thirdly, the global COVID-19 pandemic has highlighted the critical need for advanced epidemiological tools to track and predict disease spread, further accelerating the adoption of AI in this field.
Regional Insights
The adoption of AI in epidemiology varies across regions due to factors such as healthcare infrastructure, regulatory frameworks, and investment in technology. In developed regions like North America and Europe, there is significant investment in AI-driven healthcare solutions, including epidemiology. These regions benefit from robust data infrastructure and a strong research ecosystem, facilitating the development and deployment of AI technologies. In contrast, developing regions in Asia-Pacific, Latin America, and Africa are increasingly exploring AI applications in epidemiology to address public health challenges and improve healthcare outcomes.
Artificial Intelligence (AI) in Epidemiology Market Scope
| Report Coverage | Details |
| Market Size in 2023 | USD 548.99 Million |
| Market Size in 2024 | USD 697.60 Million |
| Market Size by 2033 | USD 6,025.53 Million |
| Market Growth Rate | CAGR of 8.92% from 2024 to 2033 |
| Largest Market | North America |
| Base Year | 2023 |
| Forecast Period | 2024 to 2033 |
| Segments Covered | Deployment, Application Infection, End-use, and Regions |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Artificial Intelligence (AI) in Epidemiology Market Dynamics
Drivers
Several drivers propel the growth of AI in epidemiology. One major driver is the potential of AI to revolutionize disease surveillance and early detection. AI algorithms can analyze diverse data sources in real-time, enabling quicker identification of disease outbreaks and trends. Another driver is the demand for personalized medicine and targeted interventions, where AI-powered predictive models can help tailor healthcare strategies based on individual and population-level data. Additionally, cost-effectiveness and efficiency improvements in healthcare delivery through AI-driven automation and decision support systems drive adoption across healthcare systems globally.
Opportunities
The AI in epidemiology market presents numerous opportunities for innovation and collaboration. One significant opportunity lies in developing AI algorithms for predictive modeling of infectious diseases and chronic conditions, enhancing preparedness and response strategies. Collaborations between technology firms, healthcare providers, and research institutions can foster the development of AI-powered tools for epidemiological research and public health policy. Moreover, AI can facilitate real-time data integration and analysis, enabling proactive healthcare management and resource allocation.
Challenges
Despite its potential, AI in epidemiology faces several challenges. Data privacy concerns and regulatory compliance issues are critical barriers, particularly when dealing with sensitive health data. Ensuring the reliability and interpretability of AI algorithms in epidemiological predictions is another challenge, as complex algorithms may obscure underlying patterns or biases in data. Moreover, the integration of AI into existing healthcare workflows requires overcoming organizational resistance and ensuring adequate training and support for healthcare professionals. Lastly, the upfront costs and ongoing maintenance of AI infrastructure pose financial challenges, especially for healthcare systems in resource-constrained settings.
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Artificial Intelligence (AI) in Epidemiology Market Companies
- Cerner Corporation
- Cognizant
- eClinical Works Inc
- Alphabet Inc
- Intel Corporation
- Epic Systems Corporation
- Microsoft Corporation
- Meditech
- Komodo Health
- Siemens Healthineers
- Bayer Healthcare
- SAS Institute
- Cardiolyse
- Predixion Healthcare (Jvion LLC)
Recent Developments
- In September 2023, The Department of Biomedical Informatics (DBMI) at Harvard Medical School is creating an AI in Medicine Ph.D. track to prepare the next generation of leaders at the intersection of artificial intelligence and medicine. Applications were opened in September 2023 for a program started in the fall of 2024.
- In August 2023, Clarivate Plc, a global leader in connecting people and organizations to intelligence they can trust to transform their world, launched its new enhanced search platform leveraging generative artificial intelligence (GenAI). GenAI has the potential to yield efficiencies across the entire Life Sciences & Healthcare value chain.
- In June 2023, Dartmouth launched its Center for Precision Health and Artificial Intelligence (CPHAI), which is set to advance interdisciplinary research into how artificial intelligence (AI) and biomedical data can be used to improve precision medicine and health outcomes. CPHAI’s launch is supported by $2 million in initial funding from Dartmouth’s Geisel School of Medicine and the Dartmouth Cancer Center.
Segment Covered in the Report
By Deployment
- Web-based
- Cloud-based
By Application Infection
- Prediction and forecasting
- Disease and syndromic surveillance
By End-use
- Government and state Agencies
- Research labs
- Pharmaceutical and Biotechnology Companies
- Healthcare Providers
By Geography
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
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