by The global artificial intelligence in life sciences market is on the rise. According to research and consulting company, Precedence Research, the market size of artificial intelligence in life sciences worldwide will hit US$ 6.7 billion by 2030, up from US$ 1.56 billion in 2022. This means a cumulative average growth rate (CAGR) of 20% from 2022 to 2030. The report contains 150+ pages with detailed analysis.
The rising technological advances and rapid emergence of the novel technologies like artificial intelligence and its rising applications across various industries has led to the increased demand for the AI in the life sciences industry. The rising need for controlling costs and enhancing the operational efficiencies in the drug discovery and clinical trials is fostering the growth of the AI in life sciences market across the globe.
The rapidly emerging data based AI, technological advances in the deep learning, and growing need for achieving autonomy in robotics are expected to boost the demand for the AI technology in the life sciences industry. The inefficiency of the drug discovery process due to factors such as high costs of research and development, low success rate in clinical trials, and growing focus on rare diseases is fueling the adoption of the AI in life sciences to improve efficiency and reduce costs.
The machine learning technology can enhances the candidate recruitment functions, data, storage, and data analytics, which is anticipated to fuel the market growth during the forecast period.
Artificial Intelligence in Life Sciences Market Report Scope
| Report Coverage | Details |
| Market Size by 2030 | USD 6.7 Billion |
| Growth Rate from 2022 to 2030 | CAGR of 20% |
| Largest Market | North America |
| Fastest Growing Region | Europe |
| Base Year | 2021 |
| Forecast Period | 2022 to 2030 |
| Segments Covered | Offering, Deployment, Application, Geography |
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Artificial Intelligence in Life Sciences Market Report Highlights
- By offering, the software segment dominated the market, owing to the rising adoption of the software among the life science companies. This is attributed to the rising importance and need for data collection, processing, management, and analytics. The software can offer various benefits related to the data.
- By deployment, the cloud segment dominated the market. The rising penetration of internet and rising advances in the IT and telecommunications industry has led to the development of advanced cloud based servers that can improve the operations of the organization as per their requirements and can easily store, manage, and share data.
- Based on application, the drug discovery segment dominated the market owing to the rising adoption of Ai in the drug discovery process. The AI can efficiently control costs and improve the operational efficiency in the drug discovery activities.
Artificial Intelligence in Life Sciences Market Regional Snapshot
North America led the global AI in life sciences market. US was the major driver of the North America AI in life sciences market in 2021. The US is known to be the home of the several leading biotech and pharma companies that are the major investors in the research and development, drug discovery, and clinical trial activities. The increased demand for the AI technology among the research organizations and the pharmaceutical companies has led to the dominance of North America in the AI in life sciences market.
Approximately US$80 billion was invested on research and development by the pharmaceutical companies in 2018 across the globe, as per the data of Pharmaceutical Research and Manufacturers of America (PhRMA). US leads the globe in terms of new drug discovery and development and it holds the property rights of the majority of the drugs that has been recently developed.
Asia Pacific is the home to several top research organizations that are the major drivers of the AI in life sciences market in Asia Pacific. The presence of top research institutions and rising investments in the research studies of various diseases and its treatment has bolstered the demand for the AI hardware and software in Asia Pacific region. The growing government investments towards advancing the medical infrastructure and rising pharma FDIs in the region is expected to boost the growth of the market in the forthcoming years.
Artificial Intelligence in Life Sciences Market Dynamics
Driver: Growing need for clinical trials and drug discovery
Drug discovery and clinical trials are expensive affairs that involve huge recurring costs. The research, development, candidate recruitment, candidate retention, and various phases of clinical trials, each of them are very costly and the low success rate of these activities increases the costs for the company at a significant level. As per the Pharmaceutical Research and Manufacturers of America (PhRMA), the pharma companies spends around 19 % of their revenue, on an average, in the research. Therefore, the growing the growing need for controlling costs and improving outcomes is boosting the adoption of AI in life sciences field.
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Restraints: Huge capital investments
The artificial intelligence is an expensive and latest technology that has gained a rapid traction across the globe and across various industry verticals. The rising need for data analytics, deep learning, machine learning, and natural language processing are the major drivers of the AI technology. However, the high capital investments in the deployment of AI in the life sciences companies may hinder the market growth during the forecast period.
Opportunity: Lack of AI experts
AI is a new technology and there is a dearth of experts and skilled staffs that can efficiently handle the AI based software and hardware systems. This automatically increases the third party services provided by the AI in life sciences market players, which increases the revenues of the AI in life sciences market players. This factor is offering the market players to generate huge revenues on recurring basis.
Challenge: Data privacy and cybersecurity
With the growing adoption of the digital technologies, the risks of malware and cyberattacks has significantly increased across the globe. The growing number of cyberattacks and rising concerns regarding the data privacy is the major challenge for the market players.
Artificial Intelligence in Life Sciences Market Recent Developments
- In June 2020, The University of Kentucky andAtomwise, entered into a strategic collaboration for small molecule discovery, to discover potential therapies for COVID-19.
AI in Life Sciences Market Key Players:
- IBM Corporation
- Atomwise, Inc.
- Nuance Communications, Inc.
- NuMedii, Inc.
- AiCure LLC.
- APIXIO, Inc.
- Insilico Medicine, Inc.
- Enlitic, Inc.
- Sensely, Inc.
- Zebra Medical Vision
Artificial Intelligence in Life Sciences Market Segmentations
By Offering
- Software
- Hardware
- Services
By Deployment
- On Premise
- Cloud
By Application
- Medical Diagnosis
- Drug Discovery
- Precision and Personalized Medicine
- Biotechnology
- Clinical Trials
- Patient Monitoring
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
A unique research methodology has been utilized to conduct comprehensive research on the growth of the global artificial intelligence in life sciences market and arrive at conclusions on the future growth prospects of the market. This research methodology is a combination of primary and secondary research, which helps analysts warrant the accuracy and reliability of the draw conclusions.
Secondary sources referred to by analysts during the production of the global market report include statistics from company annual reports, SEC filings, company websites, World Bank database, investor presentations, regulatory databases, government publications, and industry white papers. Analysts have also interviewed senior managers, product portfolio managers, CEOs, VPs, and market intelligence managers, who contributed to the production of our study on the market as a primary source.
These primary and secondary sources provided exclusive information during interviews, which serves as validation from mattress topper industry leaders. Access to an extensive internal repository and external proprietary databases allows this report to address specific details and questions about the global artificial intelligence in life sciences market with accuracy. The study also uses the top-down approach to assess the numbers for each segment and the bottom-up approach to counter-validate them. This has helped to estimate the future prospects of the global market more reliable and accurately.
Why should you invest in this report?
If you are aiming to enter the global artificial intelligence in life sciences market, this report is a comprehensive guide that provides crystal clear insights into this niche market. All the major application areas for artificial intelligence in life sciences are covered in this report and information is given on the important regions of the world where this market is likely to boom during the forecast period of 2022-2030 so that you can plan your strategies to enter this market accordingly.
Besides, through this report, you can have a complete grasp of the level of competition you will be facing in this hugely competitive market and if you are an established player in this market already, this report will help you gauge the strategies that your competitors have adopted to stay as market leaders in this market. For new entrants to this market, the voluminous data provided in this report is invaluable.
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 in Life Sciences Market
5.1. COVID-19 Landscape: Artificial Intelligence in Life Sciences 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 in Life Sciences Market, By Offering
8.1. Artificial Intelligence in Life Sciences Market, by Offering, 2022-2030
8.1.1Software
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 in Life Sciences Market, By Deployment
9.1. Artificial Intelligence in Life Sciences Market, by Deployment, 2022-2030
9.1.1. On Premise
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Cloud
9.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Artificial Intelligence in Life Sciences Market, By Application
10.1. Artificial Intelligence in Life Sciences Market, by Application, 2022-2030
10.1.1. Medical Diagnosis
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Drug Discovery
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. Precision and Personalized Medicine
10.1.3.1. Market Revenue and Forecast (2017-2030)
10.1.4. Biotechnology
10.1.4.1. Market Revenue and Forecast (2017-2030)
10.1.5. Clinical Trials
10.1.5.1. Market Revenue and Forecast (2017-2030)
10.1.6. Patient Monitoring
10.1.6.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Artificial Intelligence in Life Sciences Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Offering (2017-2030)
11.1.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.1.3. Market Revenue and Forecast, by Application (2017-2030)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.1.4.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.1.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.1.5.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.1.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.2.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.4.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.2.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.5.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.2.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.6.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.2.6.3. Market Revenue and Forecast, by Application (2017-2030)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Offering (2017-2030)
11.2.7.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.2.7.3. Market Revenue and Forecast, by Application (2017-2030)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.3.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.4.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.3.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.5.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.3.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.6.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.3.6.3. Market Revenue and Forecast, by Application (2017-2030)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Offering (2017-2030)
11.3.7.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.3.7.3. Market Revenue and Forecast, by Application (2017-2030)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.4.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.4.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.5.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.4.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.6.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.4.6.3. Market Revenue and Forecast, by Application (2017-2030)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Offering (2017-2030)
11.4.7.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.4.7.3. Market Revenue and Forecast, by Application (2017-2030)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.5.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.5.3. Market Revenue and Forecast, by Application (2017-2030)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Offering (2017-2030)
11.5.4.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.5.4.3. Market Revenue and Forecast, by Application (2017-2030)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Offering (2017-2030)
11.5.5.2. Market Revenue and Forecast, by Deployment (2017-2030)
11.5.5.3. Market Revenue and Forecast, by Application (2017-2030)
Chapter 12. Company Profiles
12.1.IBM Corporation
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. Atomwise, Inc.
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Nuance Communications, Inc.
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. NuMedii, Inc.
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. AiCure LLC.
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. APIXIO, Inc.
12.6.1. Company Overview
12.6.2. Product Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
12.7. Insilico Medicine, Inc.
12.7.1. Company Overview
12.7.2. Product Offerings
12.7.3. Financial Performance
12.7.4. Recent Initiatives
12.8. Enlitic, Inc.
12.8.1. Company Overview
12.8.2. Product Offerings
12.8.3. Financial Performance
12.8.4. Recent Initiatives
12.9. Sensely, Inc.
12.9.1. Company Overview
12.9.2. Product Offerings
12.9.3. Financial Performance
12.9.4. Recent Initiatives
12.10. Zebra Medical Vision
12.10.1. Company Overview
12.10.2. Product Offerings
12.10.3. Financial Performance
12.10.4. 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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