US Artificial Intelligence (AI) In Genomics Market - Strategic Insights and Forecasts (2026-2031)

The US AI in Genomics Market is expected to grow at a CAGR of 33.6%, reaching a market size of USD 5,342.4 million in 2031 from USD 1,256.4 million in 2026.

The US AI in genomics market is currently witnessing a structural acceleration as the shift toward precision medicine forces a move from descriptive genomics to predictive, AI-enabled diagnostics. Biotechnology firms are successfully enlisting large language models (LLMs) and physical AI to navigate the biological "search space," currently reducing the time required for lead optimization in drug discovery. This transition is becoming critical as the FDA’s 2025–2026 draft guidance is currently forcing a "Total Product Life Cycle" approach, requiring transparency in dataset bias and model opacity for AI-enabled medical devices. Strategic importance is mounting in the public sector, where the NIH is currently enlisting unified funding strategies to harmonize research participant data policies and support computational genomics through 2027. Consequently, the industry is reaching a structural outcome where "Agentic AI Factories", capable of processing 10 terabytes of data with 10x better cost of ownership, are becoming the primary infrastructure for sovereign health data.

Market Dynamics

Drivers

• Multiomic Data Explosion: The rising complexity of aging and Alzheimer's research is currently forcing a surge in demand for AI tools that can integrate NGS with proteomics and spatial omics.

• Drug Discovery Efficiency: Pharmaceutical leaders are successfully enlisting AI to mitigate the "performance drift" and dataset bias challenges that historically slowed clinical development.

• Democratization of Precision Medicine: Cloud-based AI platforms are currently enabling over 800 healthcare institutions to perform data-driven medicine without massive in-house server clusters.

• Agentic AI Adoption: Enterprises are currently transitioning from passive software to "AI Agents" that pull from open model ecosystems to safely build and deploy genomic workflows.

Restraints and Opportunities

• Model Opacity and Bias: The lack of transparency in black-box algorithms is currently forcing a transitory pause in some clinical applications until new FDA transparency standards are met.

• Data Harmonization Barriers: Inconsistent research participant data policies are currently creating "red tape" that limits the interoperability of large-scale genomic datasets.

• Physical AI in Labs (Opportunity): Robotics leaders are successfully enlisting physical AI models to navigate real-world laboratory environments, currently automating high-throughput sample processing.

• Sovereign AI Infrastructure (Opportunity): US-based health systems are successfully enlisting "AI Factories" to maintain sovereign control over sensitive genomic data while accelerating discovery.

Supply Chain Analysis

The AI in genomics supply chain is currently transitioning from "Fragmented Hardware/Software" to "Integrated AI Factories" to support the scale-out of new genomic capacity. Technology giants like NVIDIA are successfully enlisting rack-scale systems and supercomputers to provide a unified architecture from the desktop to the data center. This evolution is becoming critical as genomic companies like QIAGEN are currently enlisting strategic acquisitions, such as Parse Biosciences, to expand their portfolios into single-cell analysis and high-throughput automation.

Government Regulations

Key Developments

• NVIDIA Vera Rubin and Rosa Launch (March 2026): NVIDIA unveiled a full-stack platform and the Rosa CPU (named for Rosalind Franklin) to accelerate physical and agentic AI in biology.

• October 2025: Illumina, Inc. announced the launch of BioInsight, a new business unit focused on developing data assets, software, and AI solutions to accelerate life science discoveries. This product launch solidifies the company’s transition from a hardware focus to a data and AI services model. It significantly increases competition in the Software Tools and Services segments by bringing a major sequencing incumbent's resources directly into the AI-driven interpretation space, directly meeting industry demand for larger-scale multiomic data analysis.

• June 2025: Illumina announced an agreement to acquire SomaLogic, accelerating its proteomics business and advancing the company's multiomics strategy. This merger and acquisition event creates an expanded product portfolio that combines high-throughput sequencing with advanced proteomics technology. The integration immediately increases the demand for AI Software capable of processing and interpreting multimodal (genomic and proteomic) data simultaneously, which is crucial for advancing precision medicine and drug target identification.

• May 2025: Deep Genomics announced the latest addition to its AI foundation model platform, the REPRESS model, which accurately predicts microRNA (miRNA) binding and mRNA degradation directly from RNA sequences. This product launch directly accelerates the discovery of disease mechanisms and the design of targeted RNA therapeutics. The new model creates focused demand for high-level AI Software and Services among pharmaceutical and biotechnology companies looking to leverage unprecedented insight into gene regulation for their drug pipelines.

Market Segmentation

By Offering

Software currently anchors the market, as enterprises are successfully enlisting cloud-based multiomic visualization and interpretation platforms to turn innovation into impact. Services are currently witnessing a growth surge as hospitals and biotech firms enlist specialized AI expertise to manage the "Total Product Life Cycle" of AI-enabled medical devices. This transition is resulting in an outcome where recurring software revenue is reaching a structural reliance point for firms aiming for "combined annual pillar sales" of at least $2 billion.

By Application

Drug Discovery and Development remains the dominant application, currently driving the adoption of "Feynman generation" computing to advance every pillar of the AI factory. Precision Medicine is forecast to expand rapidly as health systems are successfully enlisting liquid biopsy applications and AI-driven variant interpretation to democratize data-driven care. Consequently, the segment is reaching a structural outcome where diagnosis and prognosis tools are becoming a mechanical necessity for handling the 105,000+ analyses performed quarterly on top platforms.

By End-User

Pharmaceutical and Biotechnology Companies currently lead demand, successfully enlisting AI to produce data for regulatory filings regarding the safety and effectiveness of biologics. Academic and Research Institutes are currently enlisting NIH-funded computational genomics programs to understanding the genetic architecture of complex human traits through 2027. This movement is resulting in an outcome where Hospitals and Diagnostic Centers are reaching a structural reliance on streamlined benchtop sequencers to enable rapid, end-to-end analysis at the point of care.

List of Companies

• IBM

• Sophia Genetics SA

• QIAGEN N.V.

• Fabric Genomics, Inc.

• Congenica Ltd.

• Illumina, Inc.

• Freenome Holdings, Inc.

• Data4cure, Inc.

• Tempus Labs, Inc.

• NVIDIA Corporation

Company Profiles

• NVIDIA Corporation: Strategically distinct for its "AI Factory" reference designs, the company is successfully enlisting its BioNeMo Physical AI models to navigate both digital and physical biological research.

• Illumina, Inc.: Notable for its "NovaSeq X innovation roadmap," the company is currently enlisting cloud-based multiomics and streamlined benchtop systems to accelerate performance and value for researchers.

• SOPHiA GENETICS SA: Distinguished by its scale, the company is successfully enlisting AI and cloud computing across 70 countries to democratize precision medicine for over 800 healthcare institutions.

Analyst View

The US AI in genomics market is entering an "Agentic AI Factory" phase. Success for participants now depends on successfully enlisting AI agents and risk-based credibility frameworks to satisfy 2026 FDA regulatory updates and capture the exponential growth toward an opportunity.

US AI in Genomics Market Scope: