The global Genomics Combined Artificial Intelligence market size is predicted to grow from US$ 799 million in 2025 to US$ 1499 million in 2031; it is expected to grow at a CAGR of 11.1% from 2025 to 2031.

Market Overview:

The combination of AI and genomics has transformed the healthcare, pharmaceutical, and biotech sectors. Rapid advances in genome sequencing technologies, coupled with AI-driven data analytics, are revolutionizing drug discovery, disease diagnostics, and precision medicine.

Key Market Trends:

• Adoption of machine learning (ML) and deep learning (DL) algorithms for genomic data interpretation.
• Expansion of direct-to-consumer (DTC) genomic testing combined with AI for ancestry and health risk assessment.
• Increasing collaborations between pharmaceutical giants and AI-driven biotech startups.
• AI-driven genome editing tools such as CRISPR optimization.

Market Regional Analysis:

The United States leads in research, investment, and AI-driven genomics startups. Strong regulatory frameworks and government initiatives such as NIH funding and AI-driven health policies have fueled growth. Europe is increasingly focusing on precision medicine and AI-based genomic research, supported by regulatory agencies such as the European Health Data Space (EHDS). Asia Pacific is the fastest-growing market, led by China, Japan, and India. China’s government-backed AI and genomics initiatives and significant private sector investment have fueled rapid expansion.

Market Development Opportunities and Risks:

• AI-driven genomics enhances treatment plans for patients and improves clinical outcomes.
• AI-driven drug discovery reduces the time and cost required to develop new drugs.
• Advances in AI-driven genome editing improve the precision of CRISPR-based gene therapies.
• Integration with cloud computing facilitates large-scale genomic data analysis and AI model training.
• The growth of telemedicine and DTC genetic testing expands consumers' access to genomic insights.
• AI-driven genomic analysis requires large data sets, posing safety and ethical challenges.
• Global regulation of genetic data use and AI-driven diagnostics varies.
• High cost and complexity: Despite cost reductions, AI-driven genomic solutions remain expensive in some regions.
• AI models trained on biased data sets may produce inaccurate genomic interpretations.

Segmentation by Type:

• Pharmaco Genomics
• Personal Genomics

Segmentation by Application:

• Hereditary Disease Genetic Testing
• Cancer Genetic Testing
• Ancestry & Traits Genetic Testing
• Others

Market by Region:

• Americas
• United States
• Canada
• Mexico
• Brazil

• APAC
• China
• Japan
• Korea
• Southeast Asia
• India
• Australia

• Europe
• Germany
• France
• UK
• Italy
• Russia

• Middle East & Africa
• Egypt
• South Africa
• Israel
• Turkey
• GCC Countries

Company Coverage:

• Deep Genomics
• Verge Genomics
• Verily Life Sciences
• DeCODE
• GenBio AI
• Insilico Medicine
• Tempus
• Insitro
• Immunai

Key Questions Addressed in this Report