According to the research report, the global artificial intelligence in healthcare market size is expected to touch USD 187.95 Billion by 2030, from USD 15.1 Billion in 2022, growing with a significant CAGR of 37% from 2022 to 2030.
The artificial intelligence in healthcare 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 artificial intelligence in healthcare 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 artificial intelligence in healthcare 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 artificial intelligence in
healthcare 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).
Sample
Link @ https://www.precedenceresearch.com/sample/1616
Report Coverage | Details |
Market Size by 2030 | USD 187.95 Billion |
Growth Rate from 2022 to 2030 | CAGR of 37% |
North America Market Share in 2021 | 58.1% |
Software Solutions Segment Market Share in 2021 | 39.5% |
Base Year | 2021 |
Forecast Period | 2022 to 2030 |
Segments Covered | Component, Application, Technology, End USer, Geography |
This study covers a detailed segmentation
of the global artificial intelligence in healthcare market, along with key
information and a competition outlook. The report mentions company profiles of
players that are currently dominating the global artificial intelligence in
healthcare market, wherein various developments, expansions, and winning
strategies practiced and implemented by leading players have been presented in
detail.
Key Players
- Intel
- Koninklijke Philips
- Microsoft
- IBM
- Siemens Healthineers
- Nvidia
- General Electric Company
- Medtronic
- Micron Technology
- Amazon Web Services
- Johnson & Johnson
- General Vision
- CloudmedX
- Oncora Medical
- Enlitic
- Lunit
Market Segmentation
- Software
- Hardware
- Services
By Application
- Virtual Assistants
- Diagnosis
- Robot Assisted Surgery
- Clinical Trials
- Wearables
- Administrative Workflow Assistants
- Cybersecurity
- Dosage Error Reduction
- Fraud Detection
- Connected Machines
By Technology
- Machine Learning
- Natural Language Processing
- Context-aware Computing
- Computer Vision
By End User
- Hospital & Healthcare Providers
- Patients
- Pharmaceuticals & Biotechnology Companies
- Healthcare Payers
By Geography
- North America
- U.S.
- Canada
- Europe
- U.K.
- Germany
- France
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Malaysia
- Philippines
- Latin America
- Brazil
- Rest of Latin America
- Middle East & Africa (MEA)
- GCC
- North Africa
- South Africa
- Rest of the Middle East & Africa
Research Methodology
The research methodology adopted by
analysts for compiling the global artificial intelligence in healthcare 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 artificial intelligence in healthcare market.
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
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 Artificial Intelligence (AI) in Healthcare Market
5.1. COVID-19 Landscape: Artificial Intelligence (AI) in Healthcare 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 Artificial Intelligence (AI) in Healthcare Market, By Component
8.1. Artificial Intelligence (AI) in Healthcare Market, by Component Type, 2022-2030
8.1.1. Software
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Hardware
8.1.2.1. Market Revenue and Forecast (2017-2030)
8.1.3. Services
8.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Artificial Intelligence (AI) in Healthcare Market, By Application
9.1. Artificial Intelligence (AI) in Healthcare Market, by Application, 2022-2030
9.1.1. Virtual Assistants
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Diagnosis
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Robot Assisted Surgery
9.1.3.1. Market Revenue and Forecast (2017-2030)
9.1.4. Clinical Trials
9.1.4.1. Market Revenue and Forecast (2017-2030)
9.1.5. Wearables
9.1.5.1. Market Revenue and Forecast (2017-2030)
9.1.6. Administrative Workflow Assistants
9.1.6.1. Market Revenue and Forecast (2017-2030)
9.1.7. Cybersecurity
9.1.7.1. Market Revenue and Forecast (2017-2030)
9.1.8. Dosage Error Reduction
9.1.8.1. Market Revenue and Forecast (2017-2030)
9.1.9. Fraud Detection
9.1.9.1. Market Revenue and Forecast (2017-2030)
9.1.10. Connected Machines
9.1.10.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Artificial Intelligence (AI) in Healthcare Market, By Technology Type
10.1. Artificial Intelligence (AI) in Healthcare Market, by Technology Type, 2022-2030
10.1.1. Machine Learning
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Natural Language Processing
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. Context-aware Computing
10.1.3.1. Market Revenue and Forecast (2017-2030)
10.1.4. Computer Vision
10.1.4.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Artificial Intelligence (AI) in Healthcare Market, By End User Type
11.1. Artificial Intelligence (AI) in Healthcare Market, by End User Type, 2022-2030
11.1.1. Hospital & Healthcare Providers
11.1.1.1. Market Revenue and Forecast (2017-2030)
11.1.2. Patients
11.1.2.1. Market Revenue and Forecast (2017-2030)
11.1.3. Pharmaceuticals & Biotechnology Companies
11.1.3.1. Market Revenue and Forecast (2017-2030)
11.1.4. Healthcare Payers
Chapter 12. Global Artificial Intelligence (AI) in Healthcare Market, Regional Estimates and Trend Forecast
12.1. North America
12.1.1. Market Revenue and Forecast, by Component (2017-2030)
12.1.2. Market Revenue and Forecast, by Application (2017-2030)
12.1.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.1.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.1.5. U.S.
12.1.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.1.5.2. Market Revenue and Forecast, by Application (2017-2030)
12.1.5.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.1.5.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.1.6. Rest of North America
12.1.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.1.6.2. Market Revenue and Forecast, by Application (2017-2030)
12.1.6.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.1.6.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.2. Europe
12.2.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.2. Market Revenue and Forecast, by Application (2017-2030)
12.2.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.2.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.2.5. UK
12.2.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.5.2. Market Revenue and Forecast, by Application (2017-2030)
12.2.5.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.2.5.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.2.6. Germany
12.2.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.6.2. Market Revenue and Forecast, by Application (2017-2030)
12.2.6.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.2.6.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.2.7. France
12.2.7.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.7.2. Market Revenue and Forecast, by Application (2017-2030)
12.2.7.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.2.7.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.2.8. Rest of Europe
12.2.8.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.8.2. Market Revenue and Forecast, by Application (2017-2030)
12.2.8.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.2.8.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.3. APAC
12.3.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.2. Market Revenue and Forecast, by Application (2017-2030)
12.3.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.3.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.3.5. India
12.3.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.5.2. Market Revenue and Forecast, by Application (2017-2030)
12.3.5.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.3.5.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.3.6. China
12.3.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.6.2. Market Revenue and Forecast, by Application (2017-2030)
12.3.6.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.3.6.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.3.7. Japan
12.3.7.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.7.2. Market Revenue and Forecast, by Application (2017-2030)
12.3.7.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.3.7.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.3.8. Rest of APAC
12.3.8.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.8.2. Market Revenue and Forecast, by Application (2017-2030)
12.3.8.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.3.8.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.4. MEA
12.4.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.2. Market Revenue and Forecast, by Application (2017-2030)
12.4.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.4.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.4.5. GCC
12.4.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.5.2. Market Revenue and Forecast, by Application (2017-2030)
12.4.5.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.4.5.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.4.6. North Africa
12.4.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.6.2. Market Revenue and Forecast, by Application (2017-2030)
12.4.6.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.4.6.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.4.7. South Africa
12.4.7.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.7.2. Market Revenue and Forecast, by Application (2017-2030)
12.4.7.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.4.7.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.4.8. Rest of MEA
12.4.8.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.8.2. Market Revenue and Forecast, by Application (2017-2030)
12.4.8.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.4.8.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.5. Latin America
12.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.5.2. Market Revenue and Forecast, by Application (2017-2030)
12.5.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.5.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.5.5. Brazil
12.5.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.5.5.2. Market Revenue and Forecast, by Application (2017-2030)
12.5.5.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.5.5.4. Market Revenue and Forecast, by End User Type (2017-2030)
12.5.6. Rest of LATAM
12.5.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.5.6.2. Market Revenue and Forecast, by Application (2017-2030)
12.5.6.3. Market Revenue and Forecast, by Technology Type (2017-2030)
12.5.6.4. Market Revenue and Forecast, by End User Type (2017-2030)
Chapter 13. Company Profiles
13.1. Intel
13.1.1. Company Overview
13.1.2. Product Offerings
13.1.3. Financial Performance
13.1.4. Recent Initiatives
13.2. Koninklijke Philips
13.2.1. Company Overview
13.2.2. Product Offerings
13.2.3. Financial Performance
13.2.4. Recent Initiatives
13.3. Microsoft
13.3.1. Company Overview
13.3.2. Product Offerings
13.3.3. Financial Performance
13.3.4. Recent Initiatives
13.4. IBM
13.4.1. Company Overview
13.4.2. Product Offerings
13.4.3. Financial Performance
13.4.4. Recent Initiatives
13.5. Siemens Healthineers
13.5.1. Company Overview
13.5.2. Product Offerings
13.5.3. Financial Performance
13.5.4. Recent Initiatives
13.6. Nvidia
13.6.1. Company Overview
13.6.2. Product Offerings
13.6.3. Financial Performance
13.6.4. Recent Initiatives
13.7. Google
13.7.1. Company Overview
13.7.2. Product Offerings
13.7.3. Financial Performance
13.7.4. Recent Initiatives
13.8. General Electric Company
13.8.1. Company Overview
13.8.2. Product Offerings
13.8.3. Financial Performance
13.8.4. Recent Initiatives
13.9. Medtronic
13.9.1. Company Overview
13.9.2. Product Offerings
13.9.3. Financial Performance
13.9.4. Recent Initiatives
13.10. Micron Technology
13.10.1. Company Overview
13.10.2. Product Offerings
13.10.3. Financial Performance
13.10.4. Recent Initiatives
13.11. Amazon Web Services
13.11.1. Company Overview
13.11.2. Product Offerings
13.11.3. Financial Performance
13.11.4. Recent Initiatives
Chapter 14. Research Methodology
14.1. Primary Research
14.2. Secondary Research
14.3. Assumptions
Chapter 15. Appendix
15.1. About Us
15.2. Glossary of Terms
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