According to the research report, the global generative AI in medicine market size is expected to touch USD 21,586.75 Million by 2032, from USD 501.06 million in 2022, growing with a significant CAGR of 45.69% from 2023 to 2032.
Key Takeaways:
- By region, North America dominated the market with the largest market share of 44% in 2022.
- Asia Pacific expected to expand at the fastest CAGR during the forecast period.
- By deployment, the cloud segment dominated the market with the largest market share in 2022. While the on-premises segment is expected to show a steady growth in market share during the forecast period.
- By application, the medical imaging segment held the largest market share in 2022, the segment will continue to maintain its dominance during the forecast period.
- By end-user, the hospitals and clinics segment dominated the market with the highest market share in 2022. While the diagnostics center segment is the most emerging segment of the market.
The generative AI in medicine report offers a comprehensive study of the current state expected at the major drivers, market strategies, and key vendors’ growth. The report presents energetic visions to conclude and study the market size, market hopes, and competitive surroundings. The research also focuses on the important achievements of the market, research & development, and regional growth of the leading competitors operating in the market. The current trends of the global generative AI in medicine in conjunction with the geographical landscape of this vertical have also been included in this report.
The report offers intricate dynamics about different aspects of the global generative AI in medicine market, which aids companies operating in the market in making strategic development decisions. The study also elaborates on significant changes that are highly anticipated to configure growth of the global generative AI in medicine during the forecast period. It also includes a key indicator assessment that highlights growth prospects of this market and estimates statistics related to growth of the market in terms of value (US$ Mn) and volume (tons).
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This study covers a detailed segmentation of the global generative AI in medicine market, along with key information and a competition outlook. The report mentions company profiles of players that are currently dominating the global generative AI in medicine market, wherein various developments, expansions, and winning strategies practiced and implemented by leading players have been presented in detail.
Key Players
- Nuance Communications, Inc.
- IBM Corporation
- Microsoft
- NVIDIA Corporation
- Intel Corporation
- DeepMind Technologies Limited
Market Segmentation
By Deployment
- Cloud-based
- On-premises
By Application
- Medical Imaging
- Drug Discovery
- Medical Diagnosis
- Patient Data Analysis
- Other
By End-User
- Hospitals & Clinics
- Clinical Research
- Healthcare Organizations
- Diagnostic Centers
- Other
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East and Africa
Research Methodology
The research methodology adopted by analysts for compiling the global generative AI in medicine report is based on detailed primary as well as secondary research. With the help of in-depth insights of the market-affiliated information that is obtained and legitimated by market-admissible resources, analysts have offered riveting observations and authentic forecasts for the global market.
During the primary research phase, analysts interviewed market stakeholders, investors, brand managers, vice presidents, and sales and marketing managers. Based on data obtained through interviews of genuine resources, analysts have emphasized the changing scenario of the global market.
For secondary research, analysts scrutinized numerous annual report publications, white papers, market association publications, and company websites to obtain the necessary understanding of the global generative AI in medicine market.
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Generative AI in Medicine Market
5.1. COVID-19 Landscape: Generative AI in Medicine Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Generative AI in Medicine Market, By Deployment
8.1. Generative AI in Medicine Market, by Deployment, 2023-2032
8.1.1 Cloud-based
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. On-premises
8.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Generative AI in Medicine Market, By Application
9.1. Generative AI in Medicine Market, by Application, 2023-2032
9.1.1. Medical Imaging
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Drug Discovery
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Medical Diagnosis
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Patient Data Analysis
9.1.4.1. Market Revenue and Forecast (2020-2032)
9.1.5. Other
9.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Generative AI in Medicine Market, By End-User
10.1. Generative AI in Medicine Market, by End-User, 2023-2032
10.1.1. Hospitals & Clinics
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Clinical Research
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Healthcare Organizations
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Diagnostic Centers
10.1.4.1. Market Revenue and Forecast (2020-2032)
10.1.5. Other
10.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Generative AI in Medicine Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.1.2. Market Revenue and Forecast, by Application (2020-2032)
11.1.3. Market Revenue and Forecast, by End-User (2020-2032)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.1.4.2. Market Revenue and Forecast, by Application (2020-2032)
11.1.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.1.5.2. Market Revenue and Forecast, by Application (2020-2032)
11.1.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.2. Market Revenue and Forecast, by Application (2020-2032)
11.2.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.4.2. Market Revenue and Forecast, by Application (2020-2032)
11.2.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.5.2. Market Revenue and Forecast, by Application (2020-2032)
11.2.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.6.2. Market Revenue and Forecast, by Application (2020-2032)
11.2.6.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.7.2. Market Revenue and Forecast, by Application (2020-2032)
11.2.7.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.2. Market Revenue and Forecast, by Application (2020-2032)
11.3.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.4.2. Market Revenue and Forecast, by Application (2020-2032)
11.3.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.5.2. Market Revenue and Forecast, by Application (2020-2032)
11.3.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.6.2. Market Revenue and Forecast, by Application (2020-2032)
11.3.6.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.7.2. Market Revenue and Forecast, by Application (2020-2032)
11.3.7.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.2. Market Revenue and Forecast, by Application (2020-2032)
11.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.4.2. Market Revenue and Forecast, by Application (2020-2032)
11.4.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.5.2. Market Revenue and Forecast, by Application (2020-2032)
11.4.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.6.2. Market Revenue and Forecast, by Application (2020-2032)
11.4.6.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.7.2. Market Revenue and Forecast, by Application (2020-2032)
11.4.7.3. Market Revenue and Forecast, by End-User (2020-2032)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.5.2. Market Revenue and Forecast, by Application (2020-2032)
11.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.5.4.2. Market Revenue and Forecast, by Application (2020-2032)
11.5.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.5.5.2. Market Revenue and Forecast, by Application (2020-2032)
11.5.5.3. Market Revenue and Forecast, by End-User (2020-2032)
Chapter 12. Company Profiles
12.1. Nuance Communications, Inc.
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. IBM Corporation
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Microsoft
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. NVIDIA Corporation
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. Intel Corporation
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. DeepMind Technologies Limited
12.6.1. Company Overview
12.6.2. Product Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
14.2. Glossary of Terms
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