Artificial Intelligence in Genomics Market Report Scope & Overview:

The Artificial Intelligence in Genomics Market Size was valued at USD 726.9 million in 2023 and is expected to reach USD 15007.1 million by 2031, and grow at a CAGR of 46.0% over the forecast period 2024-2031.

The market is driven by the need to control drug development and discovery costs and time, increase public and private investment in AI genomics, adoption of artificial intelligence solutions for precision medicine, increased partnerships and collaboration between players as well as growing investments in AI Genomics. Also, the market growth is supported by factors like improving computing capacity, decreasing hardware costs, increasing adoption of artificial intelligence in precision medicine and huge volumes of data from bioinformatics and genotyping.

Artificial Intelligence in Genomics Market Revenue Analysis

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  • In precision medicine, AI has become more and more widespread.

  • To increase the number of genomic data sets

  • The cost of developing and discovering drugs needs to be reduced by speeding up processes and time lines

The discovery of new drugs is an expensive and protracted process, which means that alternative methods are needed to discover them. It is common to conduct drug discovery and development through in vivo or pharmacologic methods, which are expensive and time consuming. In addition, a new medicine takes an average of 10 years to reach the market and costs USD 2.6 billion.


  • The lack of skilled AI workers and unclear guidance on the regulation of medical technology

AI is a complex system, and companies need workers with certain skills in order to develop, manage or implement an AI system. For example, people working on AI systems should know about image recognition, deep learning, cognitive computing, ML and machine intelligence. Integrating AI technologies into existing systems is a difficult task, requiring significant data processing, in order to replicate human brain behavior. A small error can lead to system failure or have a negative effect on the desired outcome.


  • Focus on developing human-aware AI systems

The development of artificial intelligence technologies was to enable them to become human aware, or able to think like humans. But for the developers of AI machines, it is still a challenge to create interactive and scaleable machines. In addition, new research problems of interpretation and presentation have arisen as a result of the increasing interference of humans with AI techniques, e.g. in interactions between automated components and smart control of crowdsourcing parts. The challenge of interpreting human input, such as knowledge and specific directives, is part of the problem AI machines face.


  • There's a shortage of curated genomic data

Data is a vital source for training and developing an intelligent system which can be fully exploited. Datasets were previously largely composed and entered by hand. However, large volumes of unstructured data, in the form of text, voice, or image, are emerging as a result of the growing digital footprint and the adoption of technologies such as the Internet of Things in healthcare and life sciences.

Impact of Russia-Ukraine War

The Ukrainian health system faces a number of challenges. Due to security concerns, limited mobility, fragmented supply chains and mass migration, access to healthcare is seriously hampered. Between February 24 and June 15, a total of 295 attacks targeting healthcare, including assaults on health facilities, transportation, personnel, patients, supplies, and warehouses, resulted in 60 injuries and 77 deaths. According to the World Health Organization WHO Surveillance System for Attacks on Health Care, these attacks rob people of urgently needed medical attention, threaten health care providers and jeopardise healthcare systems.

Since February 24, over 161 confirmed assaults on healthcare facilities in Ukraine have been limiting the available services. Access to reproductive, maternal, antenatal, and mental health care in Ukraine has likewise been significantly hindered by security apprehensions, limited mobility, disrupted supply chains, and widespread displacement. All wartime patients fall into several categories. The initial group comprises military personnel experiencing battlefield injuries and adverse environmental effects, while the second group encompasses civilians residing in occupied territories or areas near combat zones. Access to healthcare and medical supplies for these individuals is either restricted or insufficient.

Impact of Economic Slowdown

The current economic slowdown in the health sector will be aggravated by recession's consequences. The COVID-19 pandemic exposed weaknesses in health systems worldwide, with numerous systems grappling with infrastructure and technology-related hurdles, while also endeavoring to tackle enduring workforce-related issues that impede system resilience. As the downturn approaches, healthcare systems have to cope with a risk environment shaped by persistent long-term trends such as climate change and ageing populations, which are exacerbated by pandemics like funding gaps and supply chain weaknesses.

Innovation and collaboration in the field of AI driven genomics may also be stimulated by economic slowdown. Researchers and industry professionals can take advantage of joint opportunities for pooling resources and expertise, as the focus is increasingly on cost effectiveness and efficiency. In that to support the development of accessable and low-cost AI tools for genetic analysis, which will benefit a wider scientific community, openness initiatives and partnerships with academia, industry and governments could be encouraged.

Market Segmentation

By Component

  • Hardware
  • Software
  • Services

In 2023, software accounted for more than 40.2% of the market share and is projected to grow rapidly at a compound annual growth rate of 46.8% over the forecast period. The segments are anticipated to be driven by the rapid adoption of AI based software solutions for genomics among healthcare institutions, R&D centres and patients as well as new product launches from market participants.


By Technology

  • Machine Learning

    • Deep Learning

    • Supervised Learning

    • Unsupervised Learning

    • Others

  • Computer Vision

In 2023, The machine learning segment had the largest market share of around 63.2% and is expected to grow at a faster compound annual growth rate over the forecast period. Machine learning, which allows scientists to make discoveries and improve their understanding of the genetic basis for health and disease, is becoming an important tool in research on genomics. Automated tasks such as the annotation of genomic data or identifying potential drug targets can be performed by machine learning algorithms without requiring a great deal of manual effort.

By Functionality

  • Genome Sequencing

  • Gene Editing

  • Others

In 2023, the segment of genome sequencing accounted for a revenue share of 44.3% and is expected to maintain its dominance over the forecast period. The sequencing of the genome to find genetic patterns has been accelerated by the use of artificial intelligence in the field of genomics. In order to speed up the process, genome sequencing companies are working with companies based on artificial intelligence. For example, PacBio, a provider of genome sequencing technology, and Google have been working together since January 2022. Under the terms of the collaboration, PacBio was expected to use Google's algorithm development, genomic analysis, and machine learning tools to enhance its existing HiFI sequencing operations and to provide new information from its sequencing data.

By Application

  • Drug Discovery & Development

  • Precision Medicine

  • Diagnostics

  • Others

In 2023, the drug discovery & development segment dominated the market with a revenue share of over 30.2%. This is due to a growing demand for novel medicines for the treatment of infectious and chronic diseases, as well as an increasing number of partnerships between pharmaceutical and biotechnology companies and market players providing AI solutions in the field of genomics.


By End-Use

  • Pharmaceutical and Biotech Companies

  • Healthcare Providers

  • Research Centers

  • Others

In 2023, the pharmaceutical and biotech companies accounted for around 35.2% of the market's revenue due to artificial intelligence and machine learning are widely applied for applications such as data management, automatic disease prediction and prevention of illness or identification of biomarkers within the biotechnology and pharmaceutical industry. In order to help pharmaceutical companies avoid investments in drugs that are unlikely to perform well in clinical trials, AI algorithms can be applied to predict drug toxicity.


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Regional Analysis

In 2023, North America accounted for around 29.4% of the global market for artificial intelligence in genomics in terms of revenue due to the presence of many market players such as Danone; Abbott; Nestlé; Targeted Medical Pharma, Inc.; and Mead Johnson & Company, LLC, North America is home to some of the world's largest and most well-funded research institutions and biotechnology companies, and these organizations are investing heavily in the development of AI powered solutions for genomics. This is driving the development of new software and tools to analyse genomic data in North America, contributing to a growing market for artificial intelligence in genomics.

The fastest compound annual growth rate is expected to be in Asia Pacific during the forecast period. The combination of rapid increases in healthcare costs, increased emphasis on precision medicine, advances in genomics technologies and an aging population is driving the demand for artificial intelligence in Genomics across the region. National initiatives in the field of genomics have been launched by some Asia countries, which are setting up their own population genetic database based on DNA sample from healthy people.



North America

  • US

  • Canada

  • Mexico


  • Eastern Europe

    • Poland

    • Romania

    • Hungary

    • Turkey

    • Rest of Eastern Europe

  • Western Europe

    • Germany

    • France

    • UK

    • Italy

    • Spain

    • Netherlands

    • Switzerland

    • Austria

    • Rest of Western Europe

Asia Pacific

  • China

  • India

  • Japan

  • South Korea

  • Vietnam

  • Singapore

  • Australia

  • Rest of Asia Pacific

Middle East & Africa

  • Middle East

    • UAE

    • Egypt

    • Saudi Arabia

    • Qatar

    • Rest of the Middle East

  • Africa

    • Nigeria

    • South Africa

    • Rest of Africa

Latin America

  • Brazil

  • Argentina

  • Colombia

  • Rest of Latin America


The Major Players are IBM, Cambridge Cancer Genomics, NVIDIA Corporation, Thermo Fisher Scientific, MolecularMatch Inc., Deep Genomics, Microsoft, Freenome Holdings, Inc., BenevolentAI, Fabric Genomics Inc. and Other Players.

Cambridge Cancer Genomics-Company Financial Analysis

Company Landscape Analysis

Recent Developments:

  • In December 2022, Intel Labs and Perelman School of Medicine at the University of Pennsylvania have completed a joint research study using distributed machine learning ML AI approaches to help diagnose brain tumours in international hospitals and research laboratories.

  • In September 20222, NVIDIA teams up with MIT and Harvard's Broad Institute to accelerate genome analysis and develop advanced language models for targeted therapies. Leveraging NVIDIA's AI expertise and Broad Institute's open platforms, goals include integrating Clara Parabricks into Terra, building large-scale language models, and improving deep learning for GATK.

Artificial Intelligence in Genomics Market Report Scope:

Report Attributes Details
Market Size in 2023  US$ 726.9 Million
Market Size by 2031  US$ 15007.1 Million
CAGR  CAGR of 46% From 2024 to 2031
Base Year  2023
Forecast Perio  2024-2031
Historical Data  2020-2022
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Component (Hardware, Software, Services)
• By Technology (Machine Learning, Computer Vision)
• By Functionality (Genome Sequencing, Gene Editing, Others)
• By Application (Drug Discovery & Development, Precision Medicine, Diagnostics, Others)
• By End Use (Pharmaceutical and Biotech Companies, Healthcare Providers, Research Centers, Others)
Regional Analysis/Coverage North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America)
Company Profiles IBM, Cambridge Cancer Genomics, NVIDIA Corporation, Thermo Fisher Scientific, MolecularMatch Inc., Deep Genomics, Microsoft, Freenome Holdings, Inc., BenevolentAI, Fabric Genomics Inc.
DRIVERS • Controlling the time and expense of medication development and discovery is essential.
• Increasing the amount of money spent on AI in genomics
• AI is being more widely used in precision medicine.
RESTRAINTS • Medical software regulations are vague, and there is a shortage of competent AI workers.

Frequently Asked Questions

Ans: The Artificial Intelligence in Genomics market size was valued at US$ 726.9 Mn in 2023

Genome Sequencing, Gene Editing, Clinical Workflows, and Predictive Genetic Testing & Preventive Medicine are the sub segments of Artificial Intelligence in Genomics market.

Key drivers of the Artificial Intelligence in Genomics Market is Increasing the amount of money spent on AI in genomics, and AI is being more widely used in precision medicine

The use of artificial intelligence (AI) in genomics focuses on the development of computer systems that can perform tasks such as genome mapping. Furthermore, AI aids in the faster study of genetic material's structure, evolution, and function than is achievable with human interaction.

Ans: The Artificial Intelligence in Genomics Market is to grow at a CAGR of 46% during the forecast period 2024-2031


1. Introduction

1.1 Market Definition

1.2 Scope

1.3 Research Assumptions

2. Industry Flowchart

3. Research Methodology

4. Market Dynamics

4.1 Drivers

4.2 Restraints

4.3 Opportunities

4.4 Challenges

5. Impact Analysis

5.1 Impact of Russia-Ukraine Crisis

5.2 Impact of Economic Slowdown on Major Countries

5.2.1 Introduction

5.2.2 United States

5.2.3 Canada

5.2.4 Germany

5.2.5 France

5.2.6 UK

5.2.7 China

5.2.8 Japan

5.2.9 South Korea

5.2.10 India

6. Value Chain Analysis

7. Porter’s 5 Forces Model

8.  Pest Analysis

9. Artificial Intelligence in Genomics Market, By Component

9.1 Introduction

    1. Trend Analysis
    2. Hardware
    3. Software
    4. Services

10. Artificial Intelligence in Genomics Market, by Technology

    1.  Introduction
    2.  Trend Analysis
    1.  Machine Learning
      1. Deep Learning
      2. Supervised Learning
      3. Unsupervised Learning
      4. Others
    2.  Computer Vision

11. Artificial Intelligence in Genomics Market, by Functionality

    1.  Introduction
    2.  Trend Analysis
    1.  Genome Sequencing
    2.  Gene Editing
    3.  Others

12. Artificial Intelligence in Genomics Market, by Application

12.1 Introduction

12.2 Trend Analysis

12.3 Drug Discovery & Development

12.4 Precision Medicine

12.5 Diagnostics

12.6 Others 

13. Artificial Intelligence in Genomics Market, by End-use

13.1 Introduction

13.2 Trend Analysis

13.3 Pharmaceutical and Biotech Companies

13.4 Healthcare Providers

13.5 Research Centers

13.6 Others 

14. Regional Analysis

14.1 Introduction

14.2 North America

14.2.1 USA

14.2.2 Canada

14.2.3 Mexico

14.3 Europe

14.3.1 Eastern Europe Poland Romania Hungary Turkey Rest of Eastern Europe

14.3.2 Western Europe Germany France UK Italy Spain Netherlands Switzerland Austria Rest of Western Europe

14.4 Asia-Pacific

14.4.1 China

14.4.2 India

14.4.3 Japan

14.4.4 South Korea

14.4.5 Vietnam

14.4.6 Singapore

14.4.7 Australia

14.4.8 Rest of Asia Pacific

14.5 The Middle East & Africa

14.5.1 Middle East UAE Egypt Saudi Arabia Qatar Rest of the Middle East

14.5.2 Africa Nigeria South Africa Rest of Africa

14.6 Latin America

14.6.1 Brazil

14.6.2 Argentina

14.6.3 Colombia

14.6.4 Rest of Latin America

15. Company Profiles

15.1 IBM

15.1.1 Company Overview

15.1.2 Financial

15.1.3 Products/ Services Offered

15.1.4 SWOT Analysis

15.1.5 The SNS View

15.2 Cambridge Cancer Genomics

15.2.1 Company Overview

15.2.2 Financial

15.2.3 Products/ Services Offered

15.2.4 SWOT Analysis

15.2.5 The SNS View

15.3 NVIDIA Corporation

15.3.1 Company Overview

15.3.2 Financial

15.3.3 Products/ Services Offered

15.3.4 SWOT Analysis

15.3.5 The SNS View

15.4 Thermo Fisher Scientific

15.4.1 Company Overview

15.4.2 Financial

15.4.3 Products/ Services Offered

15.4.4 SWOT Analysis

15.4.5 The SNS View

15.5 Molecular Match Inc.

15.5.1 Company Overview

15.5.2 Financial

15.5.3 Products/ Services Offered

15.5.4 SWOT Analysis

15.5.5 The SNS View

15.6 Deep Genomics

15.6.1 Company Overview

15.6.2 Financial

15.6.3 Products/ Services Offered

15.6.4 SWOT Analysis

15.6.5 The SNS View

15.7 Microsoft

15.7.1 Company Overview

15.7.2 Financial

15.7.3 Products/ Services Offered

15.7.4 SWOT Analysis

15.7.5 The SNS View

15.8 Freenome Holdings Inc.

15.8.1 Company Overview

15.8.2 Financial

15.8.3 Products/ Services Offered

15.8.4 SWOT Analysis

15.8.5 The SNS View

15.9 Benevolent AI

15.9.1 Company Overview

15.9.2 Financial

15.9.3 Products/ Services Offered

15.9.4 SWOT Analysis

15.9.5 The SNS View

15.10 Fabric Genomics Inc.

15.10.1 Company Overview

15.10.2 Financial

15.10.3 Products/ Services Offered

15.10.4 SWOT Analysis

15.10.5 The SNS View

16. Competitive Landscape

16.1 Competitive Benchmarking

16.2 Market Share Analysis

16.3 Recent Developments

16.3.1 Industry News

16.3.2 Company News

16.3.3 Mergers & Acquisitions

17. Use Case and Best Practices

18. Conclusion

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Step 1: Secondary Research:

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Secondary Research

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Primary Research

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Data Bank Validation

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