Summary

Generative AI In Healthcare Market Growth & Trends

The global generative AI in healthcare market size is expected to reach USD 14.77 billion by 2030, according to a new report by Grand View Research, Inc. The market is anticipated to grow at a compound annual growth rate (CAGR) of 36.7% from 2023 to 2030. Generative models in healthcare are advancing diagnostic accuracy by generating high-resolution medical images. These AI-powered models excel at producing intricate imaging, aiding in the detection and diagnosis of critical diseases like cancer, lesions, and abnormalities. The enhanced image quality enables healthcare professionals to identify subtle anomalies more effectively. Moreover, the efficiency and speed of generative models expedite the diagnostic process, enabling prompt intervention and improved patient outcomes.

Generative AI is utilized in drug discovery to create new drug compounds or optimize the existing ones, accelerating the drug development timeline. Additionally, it assists in predicting drug properties and potential side effects, offering valuable insights for informed decision-making in the pharmaceutical industry. For instance, DeepChem, an open-source platform created by Stanford University researchers, employs generative models and machine learning to drive advancements in computational chemistry for drug discovery. DeepChem offers a range of tools and models to optimize and analyze molecular compounds, catering to diverse applications in healthcare and pharmaceutical industries.

Generative AI is a transformative force in healthcare, enabling a profound shift towards personalized medicine. By leveraging an individual's genetic data and health history, generative AI algorithms can craft tailor-made treatment plans and medications. This innovative approach ensures that medical interventions are precisely aligned with a person's unique genetic makeup and health circumstances, maximizing treatment efficacy and minimizing adverse effects. The potential of generative AI to customize healthcare interventions marks a pivotal advancement in medicine, promising a future where treatments are optimized and personalized for everyone, ultimately improving overall healthcare outcomes.

Generative AI's foothold in the healthcare market of North America has strengthened significantly, showcasing a notable surge in growth. Advances in artificial intelligence and machine learning, particularly generative models, have propelled their applications within healthcare. From generating medical images for accurate diagnostics to aiding drug discovery processes, and personalizing treatment plans based on individual genetic profiles, the potential of generative AI is being actively explored and adopted. Collaborations between research institutions, healthcare organizations, and technology firms, along with substantial venture capital funding and supportive regulatory frameworks, further fuel the integration of generative AI into various healthcare domains. The demand for personalized medicine and a drive towards innovation are key factors contributing to the remarkable growth of generative AI in the healthcare sector throughout North America.

Generative AI In Healthcare Market Report Highlights

• Based on function, the medical imaging analysis segment dominated with a revenue share of 28.9% in 2022. Generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), have shown significant promise in generating high-fidelity medical images

• Based on end-use, the clinical research segment dominated the market with a revenue share of 29.3% in 2022. Generative AI has demonstrated substantial potential in assisting and expediting various aspects of clinical research like drug discovery, optimization of clinical trial designs, predictive analytics, and optimizing research processes

• The pharmaceutical industry continued to embrace generative AI for drug discovery and development. AI-driven generative models accelerated the process of identifying potential drug candidates and optimizing existing ones, reducing the time and cost associated with bringing new medications to market

• Generative AI is revolutionizing healthcare training with realistic virtual simulations. It helps create lifelike patient avatars and interactive surgical scenarios, enhancing the skills of healthcare professionals in a risk-free environment

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Table of Contents

Table of Contents

Chapter 1. Methodology and Scope
1.1. Market Segmentation and Scope
1.2. Research Methodology
1.2.1. Information Procurement
1.3. Information or Data Analysis
1.4. Methodology
1.5. Research Scope and Assumptions
1.6. Market Formulation & Validation
1.7. List of Data Sources
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.3. Competitive Insights
Chapter 3. Generative AI in Healthcare Market Variables, Trends, & Scope
3.1. Market Lineage Outlook
3.2. Market Dynamics
3.2.1. Market Driver Analysis
3.2.2. Market Restraint Analysis
3.2.3. Industry Challenge
3.3. Generative AI in Healthcare Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Bargaining power of the suppliers
3.3.1.2. Bargaining power of the buyers
3.3.1.3. Threats of substitution
3.3.1.4. Threats from new entrants
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political Landscape
3.3.2.2. Economic Landscape
3.3.2.3. Social Landscape
3.3.2.4. Technology Landscape
3.3.2.5. Environmental Landscape
3.3.2.6. Legal Landscape
3.4. Use Cases Analysis
Chapter 4. Generative AI in Healthcare Market: Component Estimates & Trend Analysis
4.1. Segment Dashboard
4.2. Generative AI in Healthcare Market: Component Movement Analysis, USD Million, 2022 & 2030
4.3. Solutions
4.3.1. Solutions Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
4.4. Services
4.4.1. Services Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 5. Generative AI in Healthcare Market: Function Estimates & Trend Analysis
5.1. Segment Dashboard
5.2. Generative AI in Healthcare Market: Function Movement Analysis, USD Million, 2022 & 2030
5.3. Virtual Nursing Assistants
5.3.1. Virtual Nursing Assistants Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
5.4. Robot-Assisted AI Surgery
5.4.1. Robot-Assisted AI Surgery Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
5.5. Administrative Process Optimization
5.5.1. Administrative Process Optimization Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
5.6. Medical Imaging Analysis
5.6.1. Medical Imaging Analysis Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 6. Generative AI in Healthcare Market: End-use Estimates & Trend Analysis
6.1. Segment Dashboard
6.2. Generative AI in Healthcare Market: End-use Movement Analysis, USD Million, 2022 & 2030
6.3. Clinical Research
6.3.1. Clinical Research Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
6.4. Medical Centers
6.4.1. Medical Centers Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
6.5. Diagnostic Centers
6.5.1. Diagnostic Centers Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
6.6. Others
6.6.1. Others Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 7. Generative AI in Healthcare Market: Application Estimates & Trend Analysis
7.1. Segment Dashboard
7.2. Generative AI in Healthcare Market: Application Movement Analysis, USD Million, 2022 & 2030
7.3. Clinical
7.3.1. Clinical Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4. System
7.4.1. System Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 8. Generative AI in Healthcare Market: Regional Estimates & Trend Analysis
8.1. Generative AI in Healthcare Market Share, By Region, 2022 & 2030, USD Million
8.2. North America
8.2.1. North America Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.2.2. U.S.
8.2.2.1. U.S. Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.2.3. Canada
8.2.3.1. Canada Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.3. Europe
8.3.1. Europe Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.3.2. U.K.
8.3.2.1. U.K. Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.3.3. Germany
8.3.3.1. Germany Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.3.4. France
8.3.4.1. France Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.4. Asia Pacific
8.4.1. Asia Pacific Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.4.2. China
8.4.2.1. China Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.4.3. Japan
8.4.3.1. Japan Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.4.4. India
8.4.4.1. India Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.4.5. South Korea
8.4.5.1. South Korea Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.4.6. Australia
8.4.6.1. Australia Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.5. Latin America
8.5.1. Latin America Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.5.2. Brazil
8.5.2.1. Brazil Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.5.3. Mexico
8.5.3.1. Mexico Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.6. Middle East and Africa
8.6.1. Middle East and Africa Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.6.1.1. (USD MILLION)
8.6.2. KSA
8.6.2.1. KSA Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.6.3. UAE
8.6.3.1. UAE Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030 (USD Million)
8.6.4. South Africa
8.6.4.1. South Africa Generative AI in Healthcare Market Estimates and Forecasts, 2017 - 2030
Chapter 9. Competitive Landscape
9.1. Company Categorization
9.2. Company Market Positioning
9.3. Participant’s Overview
9.4. Financial Performance
9.5. Product Benchmarking
9.6. Company Heat Map Analysis
9.7. Strategy Mapping
9.8. Company Profiles/Listing
9.8.1. Google LLC
9.8.2. IBM Watson
9.8.3. Johnson & Johnson
9.8.4. Microsoft Corporation
9.8.5. Neuralink Corporation
9.8.6. NioyaTech
9.8.7. OpenAI
9.8.8. Oracle
9.8.9. Saxon
9.8.10. Syntegra
9.8.11. Tencent Holdings Ltd