Generative AI In Healthcare Market Size, Share & Trends Analysis Report By Component (Software, Service), By Function (Virtual Nursing Assistants, Robot-Assisted AI Surgery), By End-use, By Application, By Region, And Segment Forecasts, 2023 - 2030

Generative AI In Healthcare Market Trends

The global generative AI in healthcare market size was estimated at USD 1.28 billion in 2022 and is projected to grow at a compound annual growth rate (CAGR) of 36.7% from 2023 to 2030. Artificial intelligence (AI) is rapidly reshaping the healthcare landscape, empowering healthcare professionals with comprehensive insights to optimize patient care. Its analytical prowess, capable of processing immense amounts of data and identifying patterns, proves invaluable in medical decision-making. Generative AI is a subset of AI, which stands out for its potential to create new data and solutions, offering promise for innovative approaches to diagnostics, drug discovery, and personalized medicine. Its ability to generate medical images, design drug molecules, and tailor treatments based on individual health data makes it a powerful tool in advancing healthcare outcomes.

In the realm of biopharmaceuticals, generative AI is causing a substantial reduction in the time taken to develop new drugs and therapies. For instance, major players in the pharmaceutical industry, such as Novartis and Amgen, are harnessing the potential of large language models trained on sequences and amino acids. These models are being utilized to generate innovative protein structures and forecast intricate molecular interactions. This approach accelerates drug development and holds immense promise in creating more effective and tailored treatments. The integration of generative AI marks a pivotal shift towards a more efficient and innovative future in biopharmaceutical research and development.

The expanding accessibility of diverse and extensive healthcare datasets is fundamentally shaping the training of generative AI models. With a wealth of comprehensive data at their disposal, generative AI models can better understand intricate patterns and nuances in healthcare information. This heightened understanding translates to the production of more accurate and valuable outputs, fostering the seamless integration of generative AI within the healthcare domain. The abundance of quality healthcare data is thus propelling the growth and effectiveness of generative AI applications in various healthcare use cases.

Component Insights

The solution segment dominated the market with a revenue share of 60.2% in 2022. Machine learning models are used in code generation to create code automatically. Generative AI is a burgeoning field with various promising applications in healthcare, including medical imaging enhancement, drug discovery, predictive modeling, and more. The potential dominance of a particular solution segment would likely arise from its proven efficacy, cost-effectiveness, regulatory compliance, and seamless integration into existing healthcare infrastructures. Factors such as superior outcomes in diagnostics, accelerated drug development, and precise patient care would contribute to the domination of a specific generative AI solution in the healthcare market.

The service segment of generative AI in the healthcare market has asserted dominance by offering comprehensive and tailored solutions to healthcare providers. These services encompass the implementation, customization, and maintenance of generative AI systems, addressing specific healthcare challenges. Providers benefit from expert guidance in integrating generative AI into their workflows, ensuring regulatory compliance, and maximizing its potential. The dominance of the service segment is driven by its ability to bridge the gap between AI technology and healthcare applications, delivering practical, value-driven solutions that enhance diagnostics, drug discovery, patient care, and operational efficiency, ultimately transforming the healthcare landscape.

Function Insights

The medical imaging analysis segment dominated the market with a revenue share of 28.9% in 2022. The dominance of generative AI in this segment is notable due to its ability to significantly enhance diagnostic accuracy and efficiency. Generative AI models, particularly Generative Adversarial Networks (GANs), can generate high-fidelity medical images, augmenting limited datasets and aiding in training robust image recognition algorithms. This innovation results in improved interpretation of medical images, aiding healthcare professionals in making more accurate diagnoses and treatment plans. The dominance stems from the substantial value addition in medical imaging, leading to a revolutionized approach in healthcare through enhanced diagnostic capabilities and ultimately better patient care.

The robot-assisted AI surgery segment is expected to grow with the fastest CAGR of 38.21% from 2023 to 2030. Robot-assisted AI surgery represents advancements in the field of healthcare. It combines robotics and artificial intelligence to enhance surgical procedures. In this innovative approach, robots equipped with AI algorithms work alongside surgeons to improve precision, control, and overall outcomes during surgeries. These robots are often equipped with computer vision systems and advanced machine learning algorithms, allowing them to analyze real-time data, provide surgeons with augmented information, and assist in performing delicate tasks with greater accuracy. Robot-assisted AI surgery has the potential to reduce human error, minimize invasiveness, shorten recovery times, and improve patient outcomes across various surgical specialties, from minimally invasive procedures to more complex interventions.

Application Insights

The clinical segment dominated the market, with a revenue share of 62.1% in 2022. This segment has emerged as a dominant force in the healthcare market through the integration of generative AI in specialized areas like cardiovascular care, dermatology, infectious disease, and oncology. Generative AI's application in cardiovascular health involves advanced analysis of cardiac data, aiding in precise diagnostics and personalized treatment planning. In dermatology, it facilitates accurate diagnosis and treatment recommendations by analyzing skin conditions. For infectious diseases, generative AI assists in pathogen identification and supports rapid responses to outbreaks. In oncology, it is crucial in genomic analysis and personalized therapy recommendations, showcasing the significant impact of generative AI in enhancing clinical decision-making.

Generative AI is rapidly advancing within the system segment of the healthcare market, notably in disease diagnosis, telemedicine, electronic health records, and drug interaction management. It's significantly improving disease diagnosis by analyzing extensive medical data to aid in accurate and timely diagnoses. In telemedicine, generative AI models enhance virtual consultations by providing real-time analysis of patient symptoms. Integration of generative AI into electronic health records optimizes data management and quick access to vital patient information. Additionally, generative AI is enhancing drug interaction management by predicting potential adverse effects and aiding in better medication decision support, ultimately elevating patient care.

End-use Insights

The clinical research segment dominated the market, with a revenue share of 29.3% in 2022. The dominance of generative AI in the clinical research segment of the healthcare market is marked by its transformative impact on trial design, drug development, and data analysis. Generative AI models can simulate clinical trial scenarios, optimize trial protocols, and predict potential outcomes, significantly streamlining the research process. Through AI-generated insights, researchers can make data-driven decisions, identify patient populations more effectively, and predict drug responses. This results in faster and more cost-efficient trials, ultimately expediting the development and approval of novel drugs and therapies.

Medical centers, with their substantial resources and expertise, have been early adopters, leveraging generative AI for medical imaging enhancements, diagnostic support, personalized treatment plans, and drug discovery. The seamless integration of generative AI into medical workflows within these centers has led to improved patient care, enhanced efficiency in diagnostics and treatments, and facilitated research and development. Generative AI algorithms can assist in generating high-fidelity medical images, aiding in early and precise diagnoses. This integration significantly enhances diagnostic speed and accuracy, optimizing patient care and outcomes. The proactive approach of diagnostic centers in implementing and leveraging generative AI highlights their crucial role in advancing medical diagnostics and setting a trend for technological integration within the healthcare domain.

Regional Insights

North America dominated the market with a revenue share of 40.2% in 2022. This region boasts a robust technological landscape and a well-established healthcare infrastructure, making it conducive to adopting and implementing advanced AI solutions. Moreover, significant investments in research and development, combined with strong support from governments and private sectors, have accelerated the growth of generative AI applications in healthcare. The region also houses numerous leading research institutions and tech companies focused on AI, fostering an environment of innovation and collaboration. So, the pressing need for advancements in healthcare efficiency, precision medicine, and patient outcomes has led to a heightened interest in generative AI, propelling its growth and prominence within the healthcare domain in North America.

The Asia Pacific region is expected to grow with the fastest CAGR of 37.6% from 2023 to 2030. In countries such as China, India, Japan, and Singapore, rapid digital transformation and a growing tech ecosystem are paving the way for the seamless adoption and integration of advanced AI technologies within the healthcare sector. This dynamic environment is fostering an increased emphasis on precision medicine, fuelled by the region's vast and diverse population, consequently spurring a demand for tailored healthcare solutions. Furthermore, the Asia Pacific region benefits from the presence of world-class research institutions and strong collaborations between academia and industry, expediting the development and deployment of generative AI applications that hold immense potential for revolutionizing healthcare outcomes.

Key Companies & Market Share Insights

The generative AI in healthcare market is characterized by strong competition, with a few major worldwide competitors owning a significant market share. The major focus is on developing new products and collaborating among the key players. For instance, in May 2023, DiagnaMed Holdings Corp., a biotechnology company in Canada unveiled FormGPT.io, a generative AI data analysis solution tailored for the healthcare sector. This launch represents the company's first commercial product in its effort to release a suite of customizable applications utilizing the power of GPT-4. These applications are designed to improve patient outcomes and streamline operations in real-world healthcare settings. These applications are designed to improve patient outcomes and streamline operations in real-world healthcare settings. Some prominent players in the generative AI in healthcare market include:

• Google LLC

• IBM Watson

• Johnson & Johnson

• Microsoft Corporation

• Neuralink Corporation

• NioyaTech

• OpenAI

• Oracle

• Saxon

• Syntegra

• Tencent Holdings Ltd

Generative AI In Healthcare Market Report Scope

Global Generative AI In Healthcare Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the industry trends in each of the sub-segments from 2017 to 2030. For this study, Grand View Research has segmented the generative AI in healthcare market report based on component, function, end-use, application, and region:

• Component Outlook (Revenue, USD Million, 2017 - 2030)

  • Solutions

  • Service

• Function Outlook (Revenue, USD Million, 2017 - 2030)

  • Virtual Nursing Assistants

  • Robot-Assisted AI Surgery

  • Administrative Process Optimization

  • Medical Imaging Analysis

• End-use Outlook (Revenue, USD Million, 2017 - 2030)

  • Clinical Research

  • Medical Centers

  • Diagnostic Centers

  • Others

• Application Outlook (Revenue, USD Million, 2017 - 2030)

  • Clinical

  • System

• Regional Outlook (Revenue, USD Million, 2017 - 2030)

  • North America

    • U.S.

    • Canada

  • Europe

    • UK

    • Germany

    • France

  • Asia Pacific

    • China

    • Japan

    • India

    • South Korea

    • Australia

  • Latin America

    • Brazil

    • Mexico

  • Middle East and Africa

    • KSA

    • UAE

    • South Africa