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The Artificial Intelligence in Genomics Market Size is valued at 757.26 Million in 2023 and is predicted to reach 18,618.72 Million by the year 2031 at a 49.4 % CAGR during the forecast period for 2024-2031.
The Global Artificial Intelligence in Genomics market is segmented on the basis of offering, application, technology type, functionality, and region. Based on the offering, the AI in the genomics market is divided into Software, Services. Based on the application, the AI in the genomics market is divided into Diagnostics, Drug Discovery & Development, Precision Medicine, Agriculture & animal Research, Other Applications. On the basis of technology, the market is segmented into Machine Learning and Other Technologies. Machine Learning is further segmented into Deep Learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning, Other Machine Learning Technologies.
The growing research and development activities for the development of advanced treatment to treat various diseases and the high application of machine learning and deep learning in drug development are expected to the market growth significantly in the coming years. By Functionality, the market is segmented into Genome Sequencing, Gene Editing, Clinical Workflows, and Predictive Genetic Testing & Preventive Medicine. By end-user, the market is segmented into Pharmaceutical & Biotech Companies, Healthcare Providers, Research Centers, Academic Institutes & Government Organizations, and Other End-Users. The growing adoption of AI in the large number of companies operating in drug development and research activities is expected to propel the growth AI in the genomics market significantly.
Based on the region, the market is segmented into Latin America, Asia Pacific, Middle East & Africa, North America, and Europe. In 2019, North America accounted for the largest share in AI in the genomics market, followed by Europe.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 757.26 Million |
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Revenue Forecast In 2031 |
USD 18,618.72 Million |
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Growth Rate CAGR |
CAGR of 49.4 % from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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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 Offering, By Functionality, By Technology, By Application, By End-User |
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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 ;The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia; South Korea; South East Asia |
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Competitive Landscape |
AI Therapeutics, Inc., Ares Genetics GmbH, BenevolentAI, BioSymetrics, Cambridge Cancer Genomics (UK), Clover Therapeutics, Congenica Ltd, Coral Genomics, CureMatch, Inc., Cyclica Inc., Data4Cure, Inc, Deep Genomics, Desktop Genetics Ltd., Diploid (Belgium), DNAnexus, Emedgene, Empiric Logic, Engine Biosciences Pte. Ltd., Fabric Genomics, Inc., FDNA Inc. (US), Freenome Holdings, Inc., Genoox, Ltd., IBM (US), LifebitAI, Microsoft (Project Hanover), MolecularMatch Inc. (US), NVIDIA Corporation (US), PrecisionLife Ltd, Predictive Oncology, SOPHiA GENETICS, Inc., Trace Genomics, Verge Genomics, WhiteLab Genomics, WuXi Nextcode Genomics |
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Customization Scope |
Free customization report with the procurement of the report, 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. |
Global Artificial Intelligence (AI) in Genomics Market by Offering
Global Artificial Intelligence (AI) in Genomics Market by Applications
Global Artificial Intelligence (AI) in Genomics Market by Technology
Global Artificial Intelligence (AI) in Genomics Market by Functionality
Global Artificial Intelligence (AI) in Genomics Market by End-Users
Global Artificial Intelligence in Genomics Market Based on Region
Europe Artificial Intelligence in Genomics Market
North America Artificial Intelligence in Genomics Market
Asia Pacific Artificial Intelligence in Genomics Market
Latin America Artificial Intelligence in Genomics Market
Middle East & Africa Artificial Intelligence in Genomics Market
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.
