Global Generative Ai In Healthcare Market
Tamaño del mercado en miles de millones de dólares
Tasa de crecimiento anual compuesta (CAGR) :
% 
 Período de pronóstico |
2024 –2031 |
 Tamaño del mercado (año base) |
USD 1.80 Billion |
 Tamaño del mercado (año de pronóstico) |
USD 17.20 Billion |
 Tasa de crecimiento anual compuesta (CAGR) |
% |
| Jugadoras de los principales mercados |
Global Generative AI in Healthcare Market, By Application (Personalized Treatment, Patient Assistance, Patient Monitoring and Predictive Analytics, Medical Image Analysis and Diagnostics, Drug Discovery and Development), End-user (Hospitals, Specialty Clinics, Ambulatory Surgical Centers (ASCs), Research and Academic Institutes, Others) – Industry Trends and Forecast to 2031.
Generative AI in Healthcare Market Analysis and Size
The market has been attracted to generative AI due to its capacity to create reliable and innovative data, thereby improving diagnostics, replicating patient responses, and providing synthetic datasets for testing and training purposes. As reported in the article 2024 Life Sciences and Health Care Generative AI Outlook Survey, the healthcare industry is investing heavily in exposing the transformative possibilities of generative AI, with approximately 75% of major healthcare companies currently experimenting or planning to scale generative AI. Thus, the increasing traction for generative AI is opening up new opportunities in the healthcare sector.
Data Bridge Market Research analyses that the global generative AI in healthcare market which was USD 1.8 billion in 2023, expecting to reach up to USD 17.20 billion by 2031, and is expected to undergo a CAGR of 32.60% during the forecast period. This indicates that the market value. “Personalized Treatment” dominates the application segment of the global generative AI in healthcare market due to surging demand for AI in healthcare stemmed from the transformative impact in healthcare industry revolutionizing medical practices. In addition to the insights on market scenarios such as market value, growth rate, segmentation, geographical coverage, and major players, the market reports curated by the Data Bridge Market Research also include depth expert analysis, patient epidemiology, pipeline analysis, pricing analysis, and regulatory framework.
Report Scope and Market Segmentation
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Report Metric |
Details |
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Forecast Period |
2024 to 2031 |
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Base Year |
2023 |
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Historic Years |
2022 (Customizable to 2016-2021) |
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Quantitative Units |
Revenue in USD Billion, Volumes in Units, Pricing in USD |
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Segments Covered |
Application (Personalized Treatment, Patient Assistance, Patient Monitoring and Predictive Analytics, Medical Image Analysis and Diagnostics, Drug Discovery and Development), End-user (Hospitals, Specialty Clinics, Ambulatory Surgical Centers (ASCs), Research and Academic Institutes, Others) |
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Countries Covered |
U.S., Canada, Mexico, U.K., Germany, France, Spain, Italy, Netherlands, Switzerland, Russia, Belgium, Turkey, Rest of Europe, China, South Korea, Japan, India, Australia, Singapore, Malaysia, Indonesia, Thailand, Philippines, Rest of Asia-Pacific, South Africa, Rest of Middle East and Africa, Brazil, and Rest of South America |
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Market Players Covered |
Epic Systems Corporation (U.S.), DiagnaMed Holdings Corp. (U.S.), Syntegra (U.S.), Merative (U.S.), Google LLC (U.S.), Oracle (U.S.), Microsoft (U.S.), NVIDIA Corporation (U.S.), Insilico Medicine (U.S.), Abridge AI, Inc. (U.S.), ELEKS (Estonia), Persistent Systems (India) |
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Market Opportunities |
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Market Definition
Generative AI in healthcare refers to the application of artificial intelligence (AI) techniques that involve the generation of new and original data. Also, in the healthcare sector, generative AI is used for tasks such as generating synthetic medical images, creating virtual patient data for training healthcare algorithms, simulating disease progression, and even designing novel molecules for drug discovery.
Global Generative AI in Healthcare Market Dynamics
Drivers
- Advancements in AI and Machine Learning Technologies
Continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies have significantly enhanced the capabilities of generative AI algorithms. These advancements enable healthcare providers to leverage generative AI for tasks such as drug discovery, medical imaging analysis, personalized medicine, and predictive analytics.
- Increasing Demand for Personalized Healthcare Solutions
There is a growing demand for personalized healthcare solutions tailored to individual patients' needs. Generative AI algorithms can analyze large datasets, including genomic data, patient records, and clinical trials, to develop personalized treatment plans and therapies. This personalized approach to healthcare can lead to better patient outcomes and improved efficiency in healthcare delivery.
- Rising Need for Drug Discovery and Development
The pharmaceutical industry faces challenges in drug discovery and development, including lengthy development timelines, high costs, and low success rates. Generative AI technologies offer the potential to accelerate the drug discovery process by predicting molecular structures, identifying potential drug candidates, and optimizing drug design. As a result, pharmaceutical companies are increasingly adopting generative AI solutions to streamline drug discovery and development processes.
- Growing Investment for Healthcare Facilities
Surging focus towards improving the condition of healthcare facilities and improving the overall healthcare infrastructure another important factor fostering the growth of the market. Rising number of partnerships and strategic collaborations between the public and private players pertaining to funding and application of new and improved technology is further creating lucrative market opportunities.
Opportunities
- Growing Adoption of Medical Imaging Analysis
Medical imaging plays a crucial role in disease diagnosis, treatment planning, and monitoring patient outcomes. Generative AI algorithms can analyze medical imaging data, such as MRI scans, CT scans, and X-rays, to assist healthcare professionals in detecting abnormalities, predicting disease progression, and improving diagnostic accuracy. The growing adoption of generative AI for medical imaging analysis is driving market growth and revolutionizing the field of radiology and diagnostic imaging.
- Healthcare Operational Efficiency and Cost Reduction
Generative AI applications offer opportunities to streamline healthcare operations, automate repetitive tasks, and optimize resource allocation across healthcare facilities. For instance, generative AI-driven predictive analytics can forecast patient admissions, optimize staffing levels, and improve inventory management, leading to reduced operational costs, enhanced workflow efficiency, and better resource utilization.
Restraints
- Data Privacy and Security Concerns
Generative AI algorithms require access to large volumes of sensitive patient data, including medical records, genomic information, and diagnostic images. However, concerns about data privacy, security breaches, and regulatory compliance present significant barriers to widespread adoption. Healthcare organizations must navigate complex regulations such as HIPAA in the U.S. and GDPR in the European Union to ensure the ethical and secure use of patient data, which may limit data sharing and collaboration across institutions.
- Lack of Interoperability and Standardization
The healthcare industry encompasses a diverse ecosystem of electronic health record (EHR) systems, medical devices, and data formats, leading to challenges in interoperability and data standardization. Inconsistent data formats and siloed information systems hinder the seamless integration of generative AI solutions into existing healthcare workflows. Without standardized data formats and interoperable systems, healthcare providers may struggle to access and exchange data efficiently, limiting the scalability and impact of generative AI applications.
Challenges
- Ethical and Regulatory Considerations
The deployment of generative AI in healthcare raises complex ethical and regulatory considerations related to accountability, transparency, bias, and fairness. Healthcare providers must grapple with issues such as algorithmic bias, informed consent, and the interpretability of AI-driven decisions to ensure patient safety and trust. Moreover, regulatory bodies face challenges in adapting existing frameworks to govern the use of AI in healthcare, leading to uncertainty regarding liability, oversight, and compliance requirements.
- Limited Clinical Validation and Evidence Base
While generative AI algorithms hold promise for revolutionizing healthcare delivery and research, many applications lack robust clinical validation and evidence demonstrating their efficacy, accuracy, and safety in real-world settings. Healthcare providers and regulatory agencies require rigorous validation studies and clinical trials to assess the reliability and clinical utility of generative AI solutions before widespread adoption. Without sufficient evidence supporting their effectiveness and reliability, generative AI technologies may encounter skepticism from healthcare stakeholders and reluctance to integrate them into clinical practice.
This global generative AI in healthcare market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the global generative AI in healthcare market contact Data Bridge Market Research for an analyst brief, our team will help you take an informed market decision to achieve market growth.
Recent Developments
- In December 2023, Merck introduced Aiddison, a pioneering software-as-a-service for drug discovery. This platform integrated a virtual design and manufacturability through Synthia retrosynthesis software application programing interface (API) integration. The launch aimed to expedite drug development with the ability to speed up to about 70% process compared to traditional process
- In August 2023, Cognizant expanded collaboration with Google Cloud, utilizing generative AI to enhance administrative processes, aiming for cost optimization and improved user experiences. This collaborative partnership aimed to strengthen the healthcare solutions, improved business efficiencies, and enhanced user experiences
Global Generative AI in Healthcare Market Scope
The global generative AI in healthcare market is segmented on the basis of application and end user. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.
Application
- Personalized Treatment
- Patient Assistance
- Patient Monitoring and Predictive Analytics
- Medical Image Analysis and Diagnostics
- Drug Discovery and Development
End user
- Hospitals
- Specialty Clinics
- Ambulatory Surgical Centers (ASCs)
- Research and Academic Institutes
- Others
Global Generative AI in Healthcare Market Regional Analysis/Insights
The global generative AI in healthcare market is analyzed and market size insights and trends are provided by country, application, and end user as referenced above.
The countries covered in the global generative AI in healthcare market report are U.S., Canada, Mexico, U.K., Germany, France, Spain, Italy, Netherlands, Switzerland, Russia, Belgium, Turkey, Rest of Europe, China, Japan, India, Australia, South Korea, Singapore, Thailand, Malaysia, Indonesia, Philippines, rest of Asia-Pacific, Brazil, rest of South America in South America, South Africa, and rest of Middle East and Africa in Middle East and Africa.
North America region dominates the global generative AI in healthcare market due to the rise adoption of AI in healthcare, the presence of major market players and increased technological advancement in the region.
Asia-Pacific region is projected to observe significant amount of growth in the global generative AI in healthcare market due to the rapid necessity for telemedicine and healthcare support. Moreover, the modernization and development in telecommunication is further anticipated to propel the growth of the global generative AI in healthcare market in the region in the coming years.
The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points such as down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.
Healthcare Infrastructure Growth Installed base and New Technology Penetration
The global generative AI in healthcare market also provides you with detailed market analysis for every country growth in healthcare expenditure for capital equipment, installed base of different kind of products for global generative AI in healthcare market, impact of technology using life line curves and changes in healthcare regulatory scenarios and their impact on the global generative AI in healthcare market.
Competitive Landscape and Global Generative AI in Healthcare Market Share Analysis
The global generative AI in healthcare market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to global generative AI in healthcare market.
Some of the major players operating in the global generative AI in healthcare market are:
- Epic Systems Corporation (U.S.)
- DiagnaMed Holdings Corp. (U.S.)
- Syntegra (U.S.)
- Merative (U.S.)
- Google LLC (U.S.)
- Oracle (U.S.)
- Microsoft (U.S.)
- NVIDIA Corporation (U.S.)
- Insilico Medicine (U.S.)
- Abridge AI, Inc. (U.S.)
- ELEKS (Estonia)
- Persistent Systems (India)
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Metodología de investigación
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La metodología de investigación clave utilizada por el equipo de investigación de DBMR es la triangulación de datos, que implica la extracción de datos, el análisis del impacto de las variables de datos en el mercado y la validación primaria (experto en la industria). Los modelos de datos incluyen cuadrícula de posicionamiento de proveedores, análisis de línea de tiempo de mercado, descripción general y guía del mercado, cuadrícula de posicionamiento de la empresa, análisis de patentes, análisis de precios, análisis de participación de mercado de la empresa, estándares de medición, análisis global versus regional y de participación de proveedores. Para obtener más información sobre la metodología de investigación, envíe una consulta para hablar con nuestros expertos de la industria.
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