Global AI In Genomics Market By Type (Software, Services), By Application (Genome Sequencing, Gene Editing, Gene Mapping), By Region, And Segment Forecasts, 2023 to 2032

Artificial Intelligence (AI) has revolutionised various sectors, and genomics is no exception. The integration of AI in genomics has led to significant advancements in understanding genetic data, diagnosing diseases, and developing personalised medicine. The rapid development of AI technology and its cost-effectiveness are the main factors driving demand for AI in the genomics industry. Recent AI-powered software solutions tailored to the genomics industry are being developed as a result of the technology's rapid advancements. Due to the increased sophistication and efficiency of these solutions, researchers can now handle and analyse genomic data more successfully than ever.

The Global AI in Genomics Market was estimated to be worth USD 0.6 billion in 2024 and is projected to reach USD 2.1 billion by 2029, growing at a CAGR of 32.4% during the forecast period 2024-2029. AI's growth in the genomics market is also being driven by the growing demand for customised drugs as well as rising R&D costs. The COVID-19 pandemic had a positive impact on the market as it accelerated the development of computing solutions that sped up the understanding of the scope, scale, and severity of the pandemic.

Premium Insights:

• Governments and private entities are heavily investing in genomic research and AI technologies, further propelling market growth. Notable investments include funding for AI-driven genomic projects and collaborations between tech companies and research institutions.

AI in Genomics Market Dynamics:

Drivers: growth of genomic data, AI in drug discovery and development and Advancements in AI techniques and machine learning

The rapid pace of DNA sequencing technologies generates massive amounts of genomic data. Traditional analysis methods struggle to keep pace. AI algorithms excel at processing and extracting valuable insights from these complex datasets.

AI can analyse vast genomic datasets to identify potential drug targets, optimise drug design, and predict drug efficacy. This accelerates the drug discovery process and leads to more targeted and effective therapies.

Continuous advancements in deep learning and other AI techniques provide researchers with more powerful tools to analyse complex genomic data and unlock new biological insights.

Restraints: Limited availability of high-quality training data, Issues in interpretability and explainability of AI Models, regulatory and ethical considerations,  skill gap and integration challenges

Developing effective AI models for genomics requires large amounts of high-quality annotated genomic data. Data collection, curation, and standardisation can be time-consuming and expensive.

While AI models can generate valuable insights, understanding how they arrive at their conclusions is crucial for scientific validation and clinical decision-making. Improving the interpretability and explainability of AI models remains a challenge.

The use of AI in healthcare raises ethical considerations and requires clear regulatory frameworks. Defining responsible AI development and deployment in genomics is essential for ensuring patient safety and data privacy.

Effectively utilising AI in genomics necessitates collaboration between data scientists, bioinformaticians, and healthcare professionals. Addressing the skills gap and fostering seamless integration of AI into existing workflows is critical.

Opportunities: Cloud-based AI solutions, public and private investment in AI research and standardisation efforts

Cloud-based AI platforms can provide researchers with access to powerful computing resources and AI tools without requiring significant upfront investments. This can democratise access to AI for smaller institutions and researchers.

Continued investment in AI research specific to genomics will fuel the development of new algorithms, tools, and applications. Public-private partnerships can further accelerate innovation in this field.

Standardizing data formats and promoting interoperability between AI platforms will enable seamless data sharing and collaboration across institutions, accelerating research progress.

Market By AI in genomics type insights:

Based on technology the market is segmented into machine learning and other technologies. The machine learning segment dominated the market in 2023 due to pharmaceutical companies, biotechnology companies and CROs widely adopting machine learning for drug genomics applications due to its ability to extract insights from data sets, accelerating growth in genomic research.

Based on application, the market is segmented into drug discovery and development, precision medicine, diagnostics and other applications. The drug discovery and development segment dominated the market in 2023 with a revenue share of over 35%, this is because of the surge in demand for innovative medicines to address infectious and chronic diseases. 

Based on functionality the market is segmented into gene editing, genome sequencing and other functionalities. The genome sequence segment is expected to dominate the market in 2023 as the utilisation of AI-powered algorithms for genomic data interpretation increases the ability to detect rare genetic variants and reveal critical insights that an guide clinical decision-making.

Market By End-Use Insights: 

The pharmaceutical and biotech companies dominate the end-user segment as artificial intelligence and machine learning play a crucial role in clinical data management, automated illness prevention and prediction and biomarker identification. The healthcare sector is the second-largest end-user 

Market By Region Insights: 

Based on regional coverage the global AI in genomics market is segmented into North America, Asia-Pacific and Europe. North America generated about 30% of the revenue in 2023, as it is home to several of the world's biggest and best-funded biotechnology firms and research institutes that are making significant investments in the creation of AI-driven genomics solutions. This is propelling the creation of new tools and software for the analysis of genomic data and fueling the expansion of AI in the genomics market in North America.

Competitive Scenario:

Major players in this industry are IBM, Microsoft Corporation, NVIDIA Corporation, DEEP GENOMICS, Data4Cure, Inc., Freenome Holdings, Inc., Thermo Fisher Scientific, Illumina, Inc.

Scope of Work-AI In Genomics Market

Key Market Developments

• June 2022- Ultima Genomics, Inc. collaborated with NVIDIA to deliver some genome sequencing with AI and accelerated computing. 
  

• February 2023- Prominent competitor in precision medicine and artificial intelligence (AI)-Tempus, announced a strategic partnership with Pfizer. The multi-year partnership aims to advance therapeutic development initiatives driven by artificial intelligence and machine learning.

• March 2023-A collaboration between 9xchange, a biopharma marketplace that makes it easier to trade drug assets, and BenevolentAI, a well-known business that specialises in AI-enabled drug discovery and development, has been announced.

Frequently Asked Questions (FAQs)

1. What is the current size of the AI in genomics market?

Ans. The Global AI in Genomics Market was estimated to be worth USD 0.6 billion in 2024 and is projected to reach USD 2.1 billion by 2029

2. What are the key drivers of the AI in genomics market?

Ans. Major drivers include the growth of genomic data, AI in drug discovery and development and Advancements in AI techniques and machine learning

3. What are the main challenges faced by the AI in genomics market?

Ans. Challenges include limited availability of high-quality training data, Issues in the interpretability and explainability of AI Models, regulatory and ethical considerations,  skill gaps and integration challenges

4. What opportunities exist in the AI in genomics market?

Ans. Opportunities include Cloud-based AI solutions, public and private investment in AI research and standardisation efforts