Market Outlook:

The AI in Genomics market size is poised to reach USD 0.6 Billion by 2024, with a projected escalation to USD 12.5 Billion by 2032, reflecting a compound annual growth rate (CAGR) of 39.2% during the forecast period (2025-2032).

Using AI equipment can spot hidden linkages between genetic data that is hard for humans to recognize. British researchers find that putting AI into genomics work creates better medical solutions for diseases and gives patients personalized treatment that helps grow the market.

 Artificial intelligence in the field of genomics uses advanced technology to process and understand genomic data through advanced computational systems. The method uses smart software programs to discover important trends in big genomic databases.

Market Dynamics:

Driver:

The high price of drug discovery makes scientists seek better alternatives to find new medicines. The standard practices of medical testing require both living animal tests and laboratory research taking too long to develop new drugs. It regularly takes 10 years to approve a new drug while developers face USD 2.6 billion expenses.

Among 10,000 new compounds only one turns into a useful treatment option for medical conditions. The majority of drug choices made during discovery do not succeed during final development because their properties become too toxic. Machine learning systems evaluate drug compounds in discovery research to find which ones lack potential before advancing into the early discovery phase. The method will help us find drugs faster and save money on projects that show no promise.

Stakeholders now examine this process for possible time and expense savings because of their interest. In November 2020 Deep Genomics and BioMarin teamed up to create drug candidates using AI technology and BioMarin's rare disease knowledge for four diseases. AI applications in genomic drug discovery will enhance medicine development efficiency by creating products that better serve people with better results.

Restraint:

Companies need special workforce skills to build control and apply AI systems because these systems are hard to manage. Team members who interact with AI need to understand both artificial image recognition and deep learning processes. Integrating AI technologies to match brain-like processing presents a hard process that needs large amounts of processed data. System malfunctions can occur and outputs will suffer when small mistakes are made. The slow growth of AI depends on the need for specific standards and qualifications in AI/ML systems. Because of low client site AI tech expertise and shortage of trained AI experts service providers face multiple delivery and upkeep challenges.

Opportunity:

The primary objective of AI development was to give these systems human understanding and thinking capabilities. Developers still struggle to make AI systems both usable with people and expandable in their functions. Human interaction with AI methods created extra research difficulties particularly in managing interaction between automated and intelligent crowd component operations. AI machines struggle to process and understand the information that humans provide along with specific instructions. Speeding up the delivery of AI output and giving user feedback creates presentation issues for developers. Building AI that recognizes and works with human users presents the greatest chance for AI developers.

Key Players:

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

Recent Development:

• During December 2022, Intel Labs partnered with Penn Medicine to research distributed AI and ML applications that assist international brain tumor detection.

• In September 20222, NVIDIA Corporation worked with the Broad Institute of MIT and Harvard to speed up DNA analysis workloads and develop AI models that identify precise medicines. Together NVIDIA provides AI knowledge while the Broad Institute offers medical research facilities to develop new product applications using NVIDIA Clara Para bricks.

• During August 2021, Illumina purchased GRAIL to enable patients to benefit from a multipurpose cancer test that finds tumors early.

Segment Insights:

By Technology

The market divides into machine learning and other tech sections based on technology usage. The availability of big genomic data and better computer systems helps scientists use advanced learning machines in genomics. These systems process large genomic records to find patterns and anticipate results from them. The market will grow because machine learning offers positive benefits to users. Machine learning technology helps programmers make prognosis allowing precise medical treatments while increasing the market income. In 2024 machine learning took the lead because pharmaceutical firms and other medical organizations already use this technology to process drug genomics data. Machine learning helps researchers learn important facts from stored data to enhance their genomic investigations.

By Application

The market splits into five application areas including diagnostics, drug research & development, precision medicine and agricultural research. In 2024 diagnostics emerged as the biggest application segment of the industry. The drug discovery and development sector keeps expanding because people need newer medicines to cure their ongoing and infectious diseases. The market should grow stronger because government agencies and private investors put money into genomics and support these efforts from public sources.

Regional Insights:

The North American artificial intelligence in genomics market held 51.9% of the total business in 2024. During the forecast period it shows strong growth. Research organizations and biotech firms in North America use their investment capital to develop AI solutions for genomics which drives the regional marketplace. The market growth will speed up because of big players active in the region plus the access to excellent computing resources. The region will successfully add AI to genomics because of government backing and easy rules that help companies use these technologies.

Segmentation:

By Offering

• Software
• Services

By Technology

• Machine Learning
  • Deep Learning
  • Supervised Learning
  • Reinforcement Learning
  • Unsupervised Learning
  • Other Machine Learning Technologies
• Other Technologies

By Functionality

• Genome Sequencing
• Gene Editing
• Clinical Workflows
• Predictive Genetic Testing & Preventive Medicine

By Application

• Diagnostics
• Drug Discovery & Development
• Precision Medicine
• Agriculture & animal Research
• Other Applications

By End User

• Pharmaceutical & Biotech Companies
• Healthcare Providers
• Research Centers, Academic Institutes, & Government Organizations
• Other End Users

By Region

North America

• USA

• Canada

• Mexico

Europe

• France

• UK

• Spain

• Germany

• Italy

• Rest of Europe

Asia Pacific

• China

• Japan

• India

• South Korea

• Rest of Asia Pacific

Middle East & Africa

• GCC

• South Africa

• Rest of the Middle East & Africa

South America

• Brazil

• Argentina

• Rest of South America

What to Expect from Industry Profile?

1. Save time carrying out entry-level research by identifying the size, growth, major segments, and leading players in the AI in Genomics market in the world.

2. Use the PORTER’s Five Forces analysis to determine the competitive intensity and therefore market attractiveness of the Global AI in Genomics market.

3. Leading company profiles reveal details of key AI in Genomics market players’ global operations, strategies, financial performance & recent developments.

4. Add weight to presentations and pitches by understanding the future growth prospects of the Global AI in Genomics market with forecast for the decade by both market share (%) & revenue (USD Million).

FAQ’s

1) What are the major factors driving the growth of the Global AI in Genomics Market?

• Need to accelerate processes and timeline and reduce drug development and discovery costs.

2) What would be the CAGR of the Global AI in Genomics Market over the forecast period?

• The Global AI in Genomics Market is poised to grow at a CAGR of 39.2% from 2025 to 2032.

3) Which region will provide more business opportunities for the growth of the Global AI in Genomics Market in the future?

• The North America region is expected to create more opportunities in the market.

4) Who are the major players dominating the Global AI in Genomics Market?

• IBM, Microsoft Corporation, NVIDIA Corporation, DEEP GENOMICS, Data4Cure, Inc.

5) What are the segments in the Global AI in Genomics Market?

• By offering, By Technology, By Functionality, By Application, By End-use, By Region are the industry key segments considered for research study.

6) What is the estimated market revenue for the Global AI in Genomics Market in 2032?

• The estimated revenue for the Global AI in Genomics Market in 2032 is USD 12.5 Billion.