Global AI in Genomics Market 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), Region and Companies – Industry Segment Outlook, Market Assessment, Competition Scenario, Trends and Forecast 2024-2033

Report Overview

The Global AI in Genomics Market size is expected to be worth around USD 35267.3 Million by 2033 from USD 733.4 Million in 2023, growing at a CAGR of 47.3% during the forecast period from 2024 to 2033.

Genomics is concerned with the study of genetic makeup of living beings. The use of Ai has revolutionised the field of genomics by introducing efficiency in research. AI has multitude of applications in the genomics sector, which has assisted in accelerating the growth of the AI in genomics market. Additionally, the use of AI has enabled development of a variety of new applications that have further boosted the market growth.

• According to the National Human Genome Research Institute, the data generated by genomics research over the next 10 years is predicted to exceed 2 to 40 billion exabytes.
• According to a research published on the PNAS, approximately 17.3% of adult individuals (1 in 6 people) had genetic findings, and when combined with deep phenotyping data, the proportion with genotype and phenotype associations increased to 11.5%, which translates to 1 in 9 people.   

Key Takeaways

• Based on component, the software segment emerged as dominant in 2023, with a market share of 47.2%.
• Among technology segments, machine leaning commanded the market in 2023, by retaining the largest market share.
• As far as functionality is concerned, the genome sequencing segment secured a market share of 46.1%.
• By application, the drug delivery and development segment contributed the most to the market with a market share of 34.4%.
• Pharmaceutical and biotech companies remained primary end-users in the market in 2023.
• Regionally, North America generated most revenue for the market by claiming a market share of 31.7% in 2023.

By Component Analysis

In 2022, the AI in genomics market was segmented by components into hardware, software, and services. Among these, the software segment emerged as the market leader, capturing approximately 40% of the market share. Furthermore, it is anticipated to experience the most rapid compound annual growth rate (CAGR) of 47.2% throughout the forecast period.

This growth trajectory is primarily attributed to the swift adoption of AI-powered software solutions for genomics across healthcare institutions, research and development centers, and among patients. Additionally, the launch of new products by key market players is expected to further propel growth within the software segment.

By Technology Analysis

The AI in genomics market is segmented by technology into machine learning and computer vision. As of 2022, the machine learning segment dominated the market, capturing approximately 65.3% of the market share. Moreover, it is projected to maintain its lead by registering the fastest compound annual growth rate (CAGR) over the forecast period.

Machine learning has emerged as a pivotal tool in genomics research, empowering scientists to unravel discoveries and enhance comprehension of the genetic underpinnings of health and disease. Machine learning algorithms streamline tasks that traditionally demand substantial manual labor, such as genomic data annotation or the pinpointing of potential drug targets.

By Functionality Analysis

Segmented by functionality, the AI in genomics market includes genome sequencing, gene editing, and other functionalities. As of 2022, the genome sequencing segment held the largest market share, accounting for 46.1% of revenue. This segment is projected to maintain its dominance throughout the forecast period. The integration of AI in genomics has notably accelerated the genome sequencing process, facilitating the identification of genetic patterns and enhancing our understanding of genetic information.

By Application Analysis

The AI in genomics market is segmented by application into drug discovery & development, precision medicine, diagnostics, and other applications. As of 2022, the drug discovery & development segment emerged as the market leader, capturing a revenue share exceeding 34.4%. This dominance is attributed to rising demands for innovative medications targeting infectious and chronic diseases, coupled with the burgeoning collaborations between pharmaceutical, biotechnology companies, and providers of AI-driven genomics solutions.

By End-Use Analysis

The pharmaceutical and biotech companies segment held the largest market share of approximately 37.5% in 2022 based on end-use. In this industry, artificial intelligence (AI) and machine learning find extensive applications such as clinical data management, automated illness prediction and prevention, and biomarker identification. AI algorithms play a crucial role in predicting the toxicity of prospective drugs, aiding pharmaceutical firms in steering clear of investments in drugs that may fail during clinical trials.

Key Market Segments

Component

• Hardware
• Software
• Services

Technology

• Machine Learning
  • Deep Learning
  • Supervised Learning
  • Unsupervised Learning
  • Others
• Computer Vision

Functionality

• Genome Sequencing
• Gene Editing
• Others

Application

• Drug Discovery & Development
• Precision Medicine
• Diagnostics
• Others

End-use

• Pharmaceutical and Biotech Companies
• Healthcare Providers
• Research Centers
• Others

Drivers

Demand for effective handling tools of large data causing a gradual surge in market growth

According to the National Library of Medicine, a nuclear genome contains over 3.2 billion nucleotide pairs. this translates to extreme amounts of data to be generated, analyzed and processed. AI technologies are capable of in handling huge datasets with ease, which enables researchers to infer with greater accuracy and efficiency.

AI-powered cost-effective solutions drive the growth of the market

AI technologies enable researchers and clinicians to analyze genomic data more efficiently and cost-effectively than traditional methods. Automated data processing pipelines and predictive models streamline genomic analyses, reducing the time and resources required for research and clinical applications.

Increasing demand for clinical diagnostics boosts market growth

Clinical diagnostic workflows are now being integrated with AI-powered processes to assist in disease diagnosis, prognosis, and treatment selection. By leveraging genomic data and patient outcomes, AI algorithms can assist clinicians in making more informed decisions and improving patient care.

Restraints

Lack of skilled workforce

Effective use of AI requires expertise in both AI and genomics. Developers necessitate high-quality labeled data and skilled human trainers to train machine learning tools. Extracting and labeling unstructured data demands a substantial, proficient workforce and time investment. Additionally, patient information is highly sensitive and subject to strict privacy regulations. Legislation like HIPAA (enforced in the US since 1996) and the HITECH Act (enforced in the US since 2003) mandates entities handling sensitive health data to implement measures ensuring privacy and security.

Moreover, these entities must inform patients of any breaches compromising their data privacy and security. Consequently, accessing curated data is challenging due to privacy concerns, record identification issues, and security requisites. Thus lack of skilled personnel proves to be a hindrance to the growth of the market.

Opportunities

Developing Interactive and Scalable AI Systems

The primary goal behind developing AI technologies has been to imbue them with human-like awareness and thinking capabilities. However, developers encounter significant hurdles in creating interactive and scalable machines. Moreover, increased human involvement in AI techniques has introduced novel research challenges, including interpretation and presentation difficulties. Interpretation challenges involve AI machines grappling with understanding human input, encompassing knowledge and specific instructions.

Presentation challenges encompass issues related to delivering the output and feedback of AI systems. Thus, the foremost opportunity for AI developers lies in crafting AI systems that are attuned to human behavior and cognition.

Impact of Macroeconomic Factors

The AI in genomics market is intricately linked to macroeconomic factors that influence healthcare spending, research funding, and technological advancements. Economic downturns may restrict healthcare budgets and research grants, slowing AI development in genomics. Conversely, economic growth often correlates with increased investment in healthcare and biotechnology, fostering innovation in AI-driven genomics. Additionally, government policies, regulatory frameworks, and global trade dynamics shape market growth.

Technological infrastructure, workforce skills, and access to capital further influence AI adoption in genomics. Understanding and navigating these macroeconomic factors are crucial for stakeholders to anticipate market trends, foster innovation, and sustain growth in AI-driven genomics.

Latest Trends

One of the main trends observed in the market is the use of deep learning for base calling within genomic instrument. Such a process involves the use of RNN and convoluted neural network models to interpret the instrument-generated data, which assists in inferring the nucleotide pairs on the genome. Thus, the introduction of AI introduced efficiency in the process of short-read and   long-read genome sequencing. Furthermore, there’s a growing focus on ethical considerations, data privacy, and regulatory compliance in genomic research and clinical applications.

Collaborations between AI startups, biotech companies, and research institutions continue to drive innovation and accelerate the development of AI-powered tools for genomics, paving the way for advancements in disease diagnosis, drug discovery, and genomic medicine.

Regional Analysis

North America is leading the AI in Genomics Market

In 2022, North America commanded the majority share of the global AI in genomics market, accounting for approximately 31.7% of the revenue. This prominent position can be attributed to the presence of numerous market players, including Danone, Abbott, Nestlé, Targeted Medical Pharma, Inc., and Mead Johnson & Company, LLC, among others.

North America hosts some of the world’s largest and most well-funded research institutions and biotechnology companies, which are heavily investing in the development of AI-powered solutions for genomics. Consequently, there’s a surge in the creation of new software and tools tailored for genomic data analysis, thus fostering the growth of the AI in genomics market in the region.

Key Regions and Countries

North America

• US
• Canada

Europe

• Germany
• France
• The UK
• Spain
• Italy
• Russia
• Netherland
• Rest of Europe

Asia Pacific

• China
• Japan
• South Korea
• India
• New Zealand
• Singapore
• Thailand
• Vietnam
• Rest of APAC

Latin America

• Brazil
• Mexico
• Rest of Latin America

Middle East & Africa

• South Africa
• Saudi Arabia
• UAE
• Rest of MEA

Key Players Analysis

The competitive landscape for AI in genomics is dynamic, with numerous companies and research institutions driving innovation in data analysis, interpretation, and application within the genomics domain. Key players include established biotechnology firms, such as Illumina, Thermo Fisher Scientific, and IBM, which integrate AI technologies into their sequencing platforms and analysis software to enhance genomic data analysis capabilities.

Additionally, specialized AI startups like Deep Genomics and DNAnexus focus on developing advanced algorithms and machine learning models tailored for genomics research and clinical applications. Academic institutions and research centers also contribute to the competitive landscape by pioneering novel AI techniques for genomics, fostering collaborations, and sharing data through initiatives like the Global Alliance for Genomics and Health (GA4GH). As competition intensifies, companies differentiate themselves through the development of proprietary algorithms, partnerships with healthcare providers, and regulatory compliance, shaping the future of AI-driven genomics and personalized medicine.

Recent Developments

• In September 2023, Deep Genomics introduced an artificial intelligence-driven foundational model aimed at investigating RNA biology. This model delves into the role of small genetic material pieces in contributing to diverse diseases and identifying potential avenues for novel therapies.
• In December 2023, Microsoft partnered with Genoox, a healthcare technology firm. This venture will merge the capabilities of Microsoft Genomics’ Azure Cloud with Genoox’s comprehensive cloud-based advanced framework for Next-Generation DNA Sequencing (NGS), based in Tel Aviv, Israel.

Market Key Players

• IBM
• Microsoft Corporation
• NVIDIA Corporation
• DEEP GENOMICS
• Data4Cure, Inc.
• Freenome Holdings, Inc.
• Thermo Fisher Scientific
• Illumina, Inc.
• SOPHiA GENETICS
• BenevolentAI
• Fabric Genomics
• Other Key Players

Report Scope