Global AI In Life Science Analytics Market Size is valued at USD 1.7 Bn in 2024 and is predicted to reach USD 4.6 Bn by the year 2034 at a 10.4% CAGR during the forecast period for 2025-2034.
Artificial Intelligence (AI) in life science analytics harnesses machine learning (ML), deep learning, as well as data analytics to revolutionize research and development in biotechnology, pharmaceuticals, and healthcare. Artificial intelligence (AI) applied to life science analytics has enormous potential to revolutionize research, improve healthcare outcomes, and streamline operations in the healthcare and life sciences industries. The use of AI is anticipated to transform data analysis and utilization in these crucial fields further as technology keeps progressing.
Healthcare results and operational efficiency are both improved with the use of artificial intelligence (AI) in life science analytics. Furthermore, the field of drug research and development is ripe with potential for the growing market for artificial intelligence in life science analytics.
However, the market growth is hampered by the high investment criteria for the safety and health of this market and the product's inability to prevent fog in environments with dramatic temperature fluctuations or high AI in life science analytics because launching effective AI products requires massive investments of capital. The industry is neither easily nor immediately monetizable. Research and development teams and engineers specializing in machine learning are often necessary for these goods, and they can be rather costly.
In addition to the upfront software and cloud support expenses, life science businesses must also cover the continuing costs of training the AI system in response to changes in business processes. The difficulty in estimating return on investment (ROI), particularly at the outset of a project, is another major hurdle. However, The COVID-19 pandemic had a beneficial impact on businesses in the health and life sciences sector. The industry was forced to accelerate innovation in response to the pandemic, manage the interruption to clinical trials and supply chains, and deal with the crisis by using artificial intelligence (AI) for life science analytics at a significant upswing.
The Global AI in life science analytics market is segmented based on component, application, deployment, and end-use. As per the components, the market is categorized into hardware, software, and services. According to deployment, the market comprises on-premise and cloud. By application, the market is segmented into research and development, sales and marketing support, supply chain analytics, and others. By end use, the market is segmented into medical devices, pharmaceuticals, and biotechnology.
The research and development of AI in the life science analytics market is expected to hold a major global market share in 2023. Research and development rely on AI to help accelerate the discovery of potential new medications, analyze genomic data, and support different steps in the drug development pipeline. It makes research decision-making, data analysis, and experimentation more efficient.
The hardware dominates because specialist hardware components like AI memory and processors are in high demand. AI algorithms are used for more complicated operations,
The North American AI in life science analytics market is estimated to register the maximum market revenue share in the near future. This can be attributed to the fact that sophisticated network of roads, hospitals, and other medical facilities, as well as a booming biotech industry. The area is known for its innovative spirit, high concentration on research and development, and partnerships between IT firms and healthcare organizations. In addition, Asia Pacific is predicted to grow rapidly in the AI in life science analytics market because of the growing funding for cutting-edge research and development in this area. The expansion of healthcare facilities in the area is another factor that will boost the market's growth.
The key players in the AI in life science analytics market have shifted their focus toward technological advancement and higher demand for them. They are initiating significant strategies such as mergers and joint ventures of major and domestic players to expand their selection of products and raise their global market footprint. Some of the major key players in the AI in life science analytics market are Indegene, Lexalytics, Databricks, SAS Institute Inc., Sisense, IQVIA, IBM, Sorcero, Atomwise, NuMedii, AiCure LLC, Nuance Communications, APIXIO, Inc, Insilico Medicine, and Other Market Players.
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Report Attribute |
Specifications |
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Market Size Value In 2024 |
USD 1.7 Bn |
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Revenue Forecast In 2034 |
USD 4.6 Bn |
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Growth Rate CAGR |
CAGR of 10.4% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Bn,and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Component, Application, Deployment, And End-Use |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
Indegene, Lexalytics, Databricks, SAS Institute Inc., Sisense, IQVIA, IBM, Sorcero, Atomwise, NuMedii, AiCure LLC, Nuance Communications, APIXIO, Inc, Insilico Medicine, and Other Market Players |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI In Life Science Analytics Market Snapshot
Chapter 4. Global AI In Life Science Analytics Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Component Estimates & Trend Analysis
5.1. by Component & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Component:
5.2.1. Software
5.2.2. Hardware
5.2.3. Services
Chapter 6. Market Segmentation 2: by Deployment Estimates & Trend Analysis
6.1. by Deployment & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Deployment:
6.2.1. On-premise
6.2.2. Cloud
Chapter 7. Market Segmentation 3: by Application Estimates & Trend Analysis
7.1. by Application & Market Share, 2024 & 2034
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Application:
7.2.1. Research and Development
7.2.2. Sales and Marketing support
7.2.3. Supply chain analytics
7.2.4. Others
Chapter 8. Market Segmentation 4: by End-User Estimates & Trend Analysis
8.1. by End-User & Market Share, 2024 & 2034
8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by End-User:
8.2.1. Medical Devices
8.2.2. Pharmaceutical
8.2.3. Biotechnology
8.2.4. Others
Chapter 9. AI In Life Science Analytics Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
9.1.2. North America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment ,2021-2034
9.1.3. North America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
9.1.4. North America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
9.1.5. North America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
9.2. Europe
9.2.1. Europe AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component ,2021-2034
9.2.2. Europe AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2021-2034
9.2.3. Europe AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
9.2.4. Europe AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
9.2.5. Europe AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
9.3. Asia Pacific
9.3.1. Asia Pacific AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
9.3.2. Asia Pacific AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2021-2034
9.3.3. Asia-Pacific AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
9.3.4. Asia Pacific AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
9.3.5. Asia Pacific AI In Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
9.4. Latin America
9.4.1. Latin America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
9.4.2. Latin America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2021-2034
9.4.3. Latin America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
9.4.4. Latin America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
9.4.5. Latin America AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
9.5. Middle East & Africa
9.5.1. Middle East & Africa AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
9.5.2. Middle East & Africa AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment ,2021-2034
9.5.3. Middle East & Africa AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
9.5.4. Middle East & Africa AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
9.5.5. Middle East & Africa AI in Life Science Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. Indegene
10.2.2. Lexalytics
10.2.3. Databricks
10.2.4. SAS Institute Inc.
10.2.5. Sisense
10.2.6. IQVIA
10.2.7. IBM
10.2.8. Sorcero
10.2.9. Atomwise
10.2.10. NuMedii
10.2.11. AiCure LLC
10.2.12. Nuance Communications
10.2.13. APIXIO, Inc
10.2.14. Insilico Medicine
10.2.15. Other Market Players
AI In Life Science Analytics Market By Component-
AI In Life Science Analytics Market By Deployment-
AI In Life Science Analytics Market By Application-
AI In Life Science Analytics Market By End-user-
AI In Life Science Analytics Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
