Artificial Intelligence in Omics Studies - Global Strategic Business Report

The global market for Artificial Intelligence in Omics Studies was valued at US$913.5 Million in 2024 and is projected to reach US$4.5 Billion by 2030, growing at a CAGR of 30.4% from 2024 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions. The report includes the most recent global tariff developments and how they impact the Artificial Intelligence in Omics Studies market.

Global Artificial Intelligence in Omics Studies Market - Key Trends & Drivers Summarized

Why Is Artificial Intelligence Becoming Indispensable in the Evolution of Omics Research?

Artificial Intelligence (AI) is becoming a transformative force in omics studies - including genomics, transcriptomics, proteomics, metabolomics, and epigenomics - by enabling the analysis of vast, high-dimensional biological datasets that would otherwise be too complex and voluminous for traditional bioinformatics. Omics technologies generate massive quantities of multi-layered data, often requiring integrative and dynamic modeling approaches to uncover meaningful biological patterns, disease mechanisms, and therapeutic targets. AI, particularly machine learning (ML) and deep learning algorithms, is proving instrumental in identifying correlations, predicting gene-disease associations, modeling protein structures, and discovering biomarkers with far greater precision and scalability than conventional methods.

As life sciences shift toward personalized, systems-level medicine, the need for computational tools that can synthesize cross-omics data into actionable insights is becoming increasingly urgent. AI-driven platforms facilitate this by detecting hidden patterns, reducing dimensionality, and generating predictive models that are central to early diagnosis, drug response profiling, and disease progression monitoring. The convergence of omics research and AI is redefining how biomedical researchers, pharmaceutical companies, and precision medicine platforms develop hypotheses, accelerate discovery, and move closer to individualized treatment strategies.

How Are AI Models Enhancing Multi-Omics Integration and Predictive Accuracy?

The application of AI in omics is particularly transformative in multi-omics integration - combining data across genomic, transcriptomic, proteomic, and metabolomic layers to build holistic biological models. Machine learning algorithms, including support vector machines (SVMs), random forests, and deep neural networks, are enabling researchers to uncover latent associations between molecular signatures and complex phenotypes, such as cancer subtypes, neurodegenerative conditions, or rare diseases. AI models excel at managing data heterogeneity, missing values, and non-linear relationships - common challenges in multi-omics analytics.

Deep learning architectures, including convolutional neural networks (CNNs) and autoencoders, are being used to map genotype-to-phenotype links, predict protein folding (e.g., AlphaFold’s breakthrough in structural biology), and identify novel drug targets. Natural language processing (NLP) tools are extracting knowledge from unstructured biological literature to enrich omics annotations and hypotheses. Moreover, unsupervised learning is helping in clustering omics data for patient stratification and disease classification without prior labeling. These AI capabilities are empowering researchers to move from descriptive to predictive and even prescriptive analytics - creating dynamic, learning-based models of biology that can evolve with new data inputs.

Where Is AI in Omics Gaining Momentum and Which Fields Are Leading Applications?

AI applications in omics are gaining momentum in academic research, pharmaceutical R&D, precision oncology, rare disease diagnostics, and agricultural biotechnology. North America dominates the market, with leading institutions, genomics startups, and biopharma companies deploying AI to accelerate biomarker discovery, optimize trial designs, and develop companion diagnostics. Europe, particularly Germany, the U.K., and the Nordic countries, is seeing robust growth in AI-driven omics collaborations through EU-funded research frameworks. Meanwhile, Asia-Pacific - driven by China, Japan, and South Korea - is making strategic investments in AI genomics platforms to support national precision medicine initiatives and population-scale sequencing projects.

Cancer research remains the most active area, with AI models being applied to stratify tumors based on molecular subtypes, predict therapy response, and monitor resistance mechanisms using real-time omics data. In pharmacogenomics, AI is guiding drug metabolism studies by linking genotypes with drug response profiles. Neurodegenerative diseases such as Alzheimer’s and Parkinson’s are also gaining attention, where AI models analyze multi-omics and imaging data to uncover early biomarkers and progression patterns. In the agricultural space, AI-powered omics is enabling the development of climate-resilient crops, trait selection, and pathogen resistance optimization. This broad scope of application is catalyzing interdisciplinary collaborations and creating new commercialization pathways.

What Is Driving the Global Growth of Artificial Intelligence in Omics Studies?

The growth in artificial intelligence in omics studies is driven by several factors, including the explosion of high-throughput sequencing technologies, the affordability of multi-omics platforms, and the critical need for integrative analytics in personalized medicine. A key driver is the exponential increase in omics data generation from large-scale cohort studies, clinical trials, and population-wide genome initiatives. AI provides the computational infrastructure necessary to extract value from these datasets - turning them into actionable insights for diagnostics, therapeutics, and preventive healthcare.

Supportive policies and investments from governments, health systems, and private stakeholders are also fueling market expansion. Initiatives like the NIH’s All of Us Research Program, UK Biobank, and the China Precision Medicine initiative are deploying AI for genomic interpretation and risk modeling. Cloud-based bioinformatics platforms and AI-as-a-service models are further lowering barriers for adoption by research institutions and mid-sized biotech firms. Enhanced data sharing frameworks, coupled with advances in data anonymization and federated learning, are helping address privacy concerns while maximizing model robustness. As AI continues to reshape biomedical research, a critical question emerges:Can artificial intelligence enable a scalable, ethical, and clinically actionable integration of omics into mainstream healthcare and population-level disease prevention?

Report Scope

The report analyzes the Artificial Intelligence in Omics Studies market, presented in terms of market value (US$ Thousand). The analysis covers the key segments and geographic regions outlined below.

Segments: Offering (Software, Services); Technology (Sequencing, Epigenomics, Proteomics, Metabolomics, Other Technologies); Application (Oncology, Infectious Diseases, Neurology, Cardiovascular Diseases, Immunology, Other Applications); End-User (Academic & Research Institutes, Biopharmaceutical Company, Other End-Users).

Geographic Regions/Countries: World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Key Insights:

• Market Growth: Understand the significant growth trajectory of the AI Software segment, which is expected to reach US$2.7 Billion by 2030 with a CAGR of a 27.7%. The AI Services segment is also set to grow at 35.3% CAGR over the analysis period.
• Regional Analysis: Gain insights into the U.S. market, valued at $240.1 Million in 2024, and China, forecasted to grow at an impressive 28.9% CAGR to reach $679.7 Million by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.

Why You Should Buy This Report:

• Detailed Market Analysis: Access a thorough analysis of the Global Artificial Intelligence in Omics Studies Market, covering all major geographic regions and market segments.
• Competitive Insights: Get an overview of the competitive landscape, including the market presence of major players across different geographies.
• Future Trends and Drivers: Understand the key trends and drivers shaping the future of the Global Artificial Intelligence in Omics Studies Market.
• Actionable Insights: Benefit from actionable insights that can help you identify new revenue opportunities and make strategic business decisions.

Key Questions Answered:

• How is the Global Artificial Intelligence in Omics Studies Market expected to evolve by 2030?
• What are the main drivers and restraints affecting the market?
• Which market segments will grow the most over the forecast period?
• How will market shares for different regions and segments change by 2030?
• Who are the leading players in the market, and what are their prospects?

Report Features:

• Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2024 to 2030.
• In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
• Company Profiles: Coverage of players such as Agilent Technologies, Amazon Web Services, Anima Biotech, Antiverse, Atomwise and more.
• Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.

Some of the 32 companies featured in this Artificial Intelligence in Omics Studies market report include:

• Agilent Technologies
• Amazon Web Services
• Anima Biotech
• Antiverse
• Atomwise
• BenevolentAI
• BGI Genomics
• Bio-Rad Laboratories
• Bruker Corporation
• Caris Life Sciences
• Danaher Corporation
• Deep Genomics
• Exscientia
• Fabric Genomics
• GE Healthcare
• GeneDx
• Genetic Leap
• Healx
• Illumina Inc.
• Insilico Medicine

Tariff Impact Analysis: Key Insights for 2025

Global tariff negotiations across 180+ countries are reshaping supply chains, costs, and competitiveness. This report reflects the latest developments as of April 2025 and incorporates forward-looking insights into the market outlook.

The analysts continuously track trade developments worldwide, drawing insights from leading global economists and over 200 industry and policy institutions, including think tanks, trade organizations, and national economic advisory bodies. This intelligence is integrated into forecasting models to provide timely, data-driven analysis of emerging risks and opportunities.

What's Included in This Edition:

• Tariff-adjusted market forecasts by region and segment
• Analysis of cost and supply chain implications by sourcing and trade exposure
• Strategic insights into geographic shifts

Buyers receive a free July 2025 update with:

• Finalized tariff impacts and new trade agreement effects
• Updated projections reflecting global sourcing and cost shifts
• Expanded country-specific coverage across the industry