Generative Artificial Intelligence (Gen AI) in Healthcare Market Size to Reach USD 34.61 Bn by 2034

Vantage Market Research releases its latest comprehensive report on the ‘Generative Artificial Intelligence (AI) in Healthcare Market ’ with a forecast period of 2025-2034. In 2023, the global Generative Artificial Intelligence (AI) in healthcare market  size was USD 1.4 Billion, and is calculated at USD 1.8 billion in 2024. The market is calculated to reach USD 34.61 billion in 2034, and register a revenue CAGR of 34.4% over the forecast period (2025-2034).

Market Overview:

Growth of the Generative Artificial Intelligence (AI) in healthcare market is expected to register a rapid Compound Annual Growth rate of 34.4% between 2025 and 2034. This is a substantial incline from USD 1.4 billion in 2023, which has also been a year of significant advancements in artificial intelligence and related technologies, and steady acceptance of these technologies across various industries and sectors, and especially generative AI in healthcare. Integration of generative artificial intelligence or GenAI in healthcare has increased steadily in 2024, with rising volume of healthcare and patient data, need for accurate image analysis and diagnostics, increasing focus on new drug discovery, disease diagnosis, personalized medicine, preventive healthcare, steady traction medical chatbots, virtual health assistants, tailored treatment plan medical simulations, disease diagnosis, screening, and customer services among others. 

Integration of Natural Language Processing (NLP), deep learning, predictive analytics, generative adversarial networks, and transformer neural networks have been gaining traction in the global generative AI in healthcare market, and this trend is expected to gain momentum over the forecast period. Also, generative AI continues to gain rapid traction and is being increasingly integrated into operations across hospitals and clinics, pharmaceutical companies, medical device manufacturers, and research institutions. 

Automated segmenting of organs and anomalies in medical images, accuracy of diagnosis, quick responses and results, rising usefulness in pathology for analyzing patterns in medical images to predict or identify pathological conditions, and support in early disease detection and intervention are some of the primary advantages of generative AI in healthcare. Also, predicting side effects, repurposing drugs, designing new drug candidates, drug discovery, precision medicine, personalized treatment planning, and remote patient monitoring also serve to enhance healthcare delivery and patient outcomes. Other advantages including reduced costs of operations and administration compared to human workforce in healthcare delivery, speed, reduced errors, and automation of repetitive tasks, optimizing workflows are driving deployment and integration in the healthcare sector. 

Rising prevalence of chronic diseases and inclining focus across the healthcare sector to encourage early detection and integrate advanced technologies to assist in disease diagnosis and patient care, monitoring, and management are also factors supporting need for more advanced technologies in the healthcare sector. Rising appeal and preference for telehealth, remote patient monitoring, access to round-the-clock medical consultation and interaction, emergency services, chatbots, and virtual health assistants is driven significantly to ease and availability of supporting equipment, devices, and technologies and software. These are also some of the key factors expected to continue to drive growth of the generative AI in healthcare market over the forecast period.

Development of cutting-edge treatments and solutions based on generative AI has also been revolutionizing diagnostics and treatment, as well as aiding healthcare personnel and facilities in enhancing patient care, management, and monitoring. Advancements in technologies and AI-powered algorithms and models has also been driving innovation and development of cutting-edge technologies and solutions. Capability to analyze medical images and extract and provide data-driven insights to enhance patient care and streamline operational processes and use in behavioral health monitoring has been transforming medical diagnostics, and enhancing care and treatment. 

Technological advancements are enabling healthcare personnel to achieve improved diagnostic accuracy, create optimized treatment strategies, and also to efficiently allocate and utilize healthcare resources. This integration also serves to reduced human error and spending, automate repetitive tasks, manage administrative tasks, remove need for manual entry of patient data, enhance scheduling and documentation to health record search, and streamline workflows. Automating repetitive tasks can also free resources for other crucial tasks and operational needs, and reduces manual workforce for certain operations or tasks. This is also evident with regard to patient and customer support in the healthcare sector, and generative AI can manage tasks such as providing 24/7 patient response services, and also supports NLP-powered conversational EHR solutions to enable collection of relevant patient information by asking specific questions in natural language. 

Integration of GenAI and advanced medical analytics and Electronic Health Records (EHRs), and adoption of cloud computing can offer enhanced performance and accessibility to data and medical insights for healthcare organizations across a wider network. Generative AI is enhancing capabilities of EHRs and enabling interoperability of patient records, clinical decision support, and co-pilot experiences for clinicians. Also, EHR Interoperability enables better workflows and reduced ambiguity, and allows proper data transfer among EHR systems and healthcare organizations, thereby improving delivery of healthcare.

Some Key Takeaways:

• North America is expected to continue to account for largest revenue share over the forecast period, driven by the US with continuous technological advancements, innovations, high rate of adoption of generative AI-powered solutions, presence of modern and sophisticated healthcare infrastructure.
• Europe generative AI in healthcare market is expected to register robust revenue growth, with Germany and the UK accounting for majority revenue share contribution.
• Asia Pacific generative AI in healthcare market is expected to register a steady and rapid growth rate over the forecast period, with major contribution from China and Japan.
• Among the technology segments, the deep learning segment is expected to account for largest revenue share over the forecast period.
• Among the component segments, the solutions segment are expected to dominate in terms of revenue share over the forecast period.
• Among the modality segments, the text generation segment is expected to account for largest revenue share over the forecast period.
• Among the application segments, the chatbots segment is expected to account for largest revenue share over the forecast period.
• Among the end-use segments over the forecast period, the hospitals and clinics segment is expected to account for largest revenue share.
• The competitive landscape in the global Generative-Artificial Intelligence (GenAI) in healthcare market is intense with existing companies and new entrants engaged in developing and introducing solutions and tools with more advanced features and capabilities.  

Company List:

• IBM Watson
• Google LLC (Alphabet Inc.)
• Microsoft Corporation
• NVIDIA Corporation
• Johnson & Johnson
• Siemens Healthineers AG
• General Electric Company (GE Healthcare)
• Philips Healthcare
• Medtronic PLC
• Epic Systems Corporation
• Tempus Labs Inc.
• PathAI
• Aidoc Medical Ltd.
• Arterys Inc.
• CureMetrix

Recent Developments:

• October 11, 2024: Microsoft announced it is unveiling a number of artificial intelligence enhancements in Microsoft Cloud for healthcare innovations. This includes new healthcare AI models in Azure AI Studio, new healthcare data capabilities in Microsoft Fabric, and developer tools in Copilot Studio. According to the company, the tools are capable of combining data from EHRs to generate comprehensive insights and support use cases and clinical imaging, Medicare & Medicaid Services claims, social determinants of health and others. A key new feature is conversational data integration and generative AI voice-enabled tool, Nuance’s DAX Copilot, which has been available for a year, but has gained traction in recent months. 
• June 13, 2024: Cognizant, in partnership with Google Cloud, launched healthcare-specific generative AI solutions to target high-cost workflows, enhancing efficiency, accuracy, and overall healthcare delivery. The new solutions include Vertex AI platform and Gemini models, and these new generative AI solutions and tools are capable of redesigning healthcare administrative processes and improving experiences, and will streamline administrative processes and accelerate speed of operations while significantly improving quality of care and services delivered to members.

Generative Artificial Intelligence (Gen AI) in Healthcare Market Segmentation:

By Technology:

• Natural Language Processing (NLP)
• Deep Learning
• Predictive Analytics
• Generative Adversarial Networks
• Transformer Neural Networks

By Component:

• Solutions
• Services

By Modality:

• Text
• Image
• Video 

By Application:

• Diagnostic Imaging
• Drug Discovery
• Precision Medicine
• Personalized Treatment Planning
• Virtual Health Assistants
• Chatbots
• Remote Patient Monitoring

By End-Use:

• Hospitals and Clinics
• Pharmaceutical Companies
• Medical Device Manufacturers
• Research Institutions

Regional Segmentation: 

North America

• United States
• Canada
• Mexico

Europe

• Germany
• United Kingdom
• France
• Italy
• Spain
• Rest of Europe

Asia Pacific

• China
• Japan
• India
• Rest of Asia Pacific

Latin America

• Brazil
• Argentina
• Rest of Latin America 

Middle East & Africa

• Saudi Arabia
• South Africa
• United Arab Emirates
• Israel
• Rest of MEA