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Part of: AI in Biotechnology Market (Global)

The US AI in Biotechnology Market was valued at $3836.7 Million in 2030 and projected to reach to $8715.3 Million by 2035, representing a compound annual growth rate of 18.0%. The US AI in Biotechnology Market is poised for sustained growth through 2035, driven by continuous technological advancement and increasing adoption across pharmaceutical and biotech sectors.

US AI in Biotechnology Market (2030-2035) : Size and Share
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Market Size in USD 26.32 MN
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US AI in Biotechnology Market Trends and Insights

  • The US market is driven by significant investments in computational biology, drug discovery acceleration, and precision medicine applications.
  • US biotechnology companies are increasingly integrating machine learning and artificial intelligence to streamline research pipelines, reduce time-to-market, and enhance therapeutic efficacy across oncology, immunology, and rare disease segments. The US maintains a competitive advantage through its concentration of leading biotech firms, advanced research infrastructure, and substantial venture capital funding.
  • Between 2030 and 2035, the US market will benefit from regulatory clarity around AI-assisted diagnostics, expanded adoption of AI-powered genomic analysis, and growing partnerships between technology and life sciences organizations.
  • The 18.0% CAGR reflects strong demand for intelligent automation in clinical trials, biomarker discovery, and personalized treatment development across the US healthcare ecosystem..

Key Market Statistics

  • CAGR (2030-2035) 18.0% CAGR
  • Market Size, 2030 ~USD 3836.7 Million
  • Forecast, 2035 ~USD 8715.3 Million
  • Country US

US AI in Biotechnology Market Overview

Market Valuation Growth :

The US AI in Biotechnology Market is valued at $3,836.7 million in 2030 and is projected to reach $8,715.3 million by 2035, representing a robust 18% CAGR over the forecast period.

Drug Discovery Acceleration :

US biotech companies are leveraging machine learning algorithms to dramatically reduce drug discovery timelines, with AI-powered platforms identifying promising compounds in months rather than years, significantly lowering R&D costs.

Precision Medicine Adoption :

American healthcare providers are increasingly deploying AI-driven precision medicine solutions to tailor treatments based on individual genetic profiles, improving patient outcomes and driving market expansion across major US biotech hubs.

Computational Biology Investment :

US biotechnology firms are making substantial investments in computational biology infrastructure, with venture capital and government funding supporting AI applications in genomics, protein folding, and biomarker discovery.

US AI in Biotechnology Market Dynamics

  • Major US research institutions and private companies are accelerating AI integration into core operations, supported by favorable regulatory frameworks and substantial R&D budgets.
  • The convergence of big data analytics, cloud computing, and machine learning is enabling breakthrough discoveries in personalized medicine and rare disease treatment.
  • Investment from both public and private sectors remains strong, with US biotech companies maintaining competitive advantages in AI innovation and implementation capabilities..

Related Ecosystem

Biotechnology

Top Technologies
  • Reagents
  • Polymerase Chain Reaction (PCR)
  • Stem Cells
  • Assay Kits
  • Flow Cytometers
Top Companies
  • Thermo Fisher Scientific Inc.
  • Merck KGaA
  • Danaher Corporation
  • Agilent Technologies, Inc.
  • Bio-Rad Laboratories, Inc.

    Healthcare It

    Top Technologies
    • Computed Tomography (CT)
    • Machine Learning
    • Magnetic Resonance Imaging (MRI)
    • Natural Language Processing (NLP)
    • Predictive Analytics
    Top Companies
    • CERNER CORPORATION
    • PHILIPS HEALTHCARE
    • Oracle Corporation
    • GE HealthCare Technologies Inc.
    • Siemens healthineers

      Key Takeaways

      • The US AI in Biotechnology Market will grow from $3,836.7M (2030) to $8,715.3M (2035), representing a 127% increase over five years.
      • The US market's 18.0% CAGR is driven by accelerated drug discovery, precision medicine adoption, and AI-enabled clinical trial optimization.
      • US biotech companies leverage AI for genomic sequencing, protein folding prediction, and real-world evidence analysis to enhance competitive positioning.
      • Regulatory frameworks and FDA guidance on AI/ML in the US are expected to mature, reducing barriers to market entry and accelerating commercialization.

      AI in Biotechnology Market Report Scope

      Report Metric Details
      Base Year 2030
      Fastest Growing Segment DRUG DISCOVERY (Type)
      Forecast Period 2030–2035
      Growth Rate CAGR of 18.5% from 2030 to 2035
      Largest Segment CLOUD-BASED SOLUTIONS (Deployment Mode)
      Market Size Base Year (Billions) ~USD 9.72 (2030)
      Revenue Forecast (Billions) ~USD 22.72 (2035)
      Segments Covered Offering, Function, Type, Deployment Mode, End User

      US AI in Biotechnology Market Report Segmentation

      5 segment dimensions are covered across the global market.

      By Offering

      • End-To-End Solutions
      • Niche Solutions
      • Services
      • Technologies
      • Technology

      By Function

      • Corporate
      • Launch & Commercial
      • Manufacturing & Supply Chain
      • Post-Marketing Surveillance & Patient Support
      • Regulatory Compliance
      • Research & Development

      By Type

      • Adverse Event Reporting
      • Biomarker Discovery
      • Clinical Data Assessment
      • Clinical Development
      • Compliance Monitoring
      • Consulting Services
      • Demand Forecasting
      • Drug Discovery
      • Hybrid Cloud
      • Implementation Services & Ongoing It Support
      • Inventory Management
      • Launch Coordination
      • Logistics Optimization
      • Marketing Operations
      • Medication Adherence
      • Molecular Design & Optimization
      • Monitoring & Drug Adherence
      • Multi Cloud
      • Other Corporate Functions
      • Other Manufacturing & Supply Chain Functions
      • Patient Engagement
      • Patient Monitoring
      • Patient Support Programs
      • Post-Sales & Maintenance Services
      • Predictive Maintenance
      • Predictive Pricing
      • Predictive Toxicity & Risk Monitoring
      • Private Cloud
      • Public Cloud
      • Real-World Evidence (Rwe) Analysis
      • Real-World Evidence(Rwe) Analysis
      • Recruitment
      • Risk Management
      • Sales Force Optimization
      • Site Selection
      • Structure-Activity Relationship (Sar) Modeling
      • Supply Chain Planning
      • Training & Education Services
      • Trial Design

      By Deployment Mode

      • Cloud-Based Solutions
      • On-Premises Solutions

      By End User

      • Biotechnology Companies
      • Clinical Research Organizations
      • Contract Research Organizations
      • Healthcare Providers
      • Pharmaceutical Companies
      • Research Institutes & Labs

      Target Audience

      • Pharmaceutical Companies : US pharma executives need detailed market intelligence to optimize AI investments in drug discovery, clinical trials, and regulatory compliance, ensuring competitive advantage in a rapidly evolving landscape.
      • Biotech Startups & Entrepreneurs : Emerging biotech founders require comprehensive market data to validate business models, identify funding opportunities, and understand competitive positioning within the US AI biotechnology ecosystem.
      • Venture Capital & Private Equity : US investment firms need precise market forecasts and segment analysis to identify high-potential portfolio companies, assess deal valuations, and optimize returns in the AI biotech sector.
      • Healthcare Technology Providers : Software and platform vendors serving US biotech need market insights to align product development, target customer segments, and demonstrate ROI to healthcare and pharmaceutical decision-makers.
      • Government & Policy Makers : US regulatory agencies and policymakers require market intelligence to inform funding decisions, regulatory frameworks, and innovation policies supporting the competitive growth of domestic AI biotechnology capabilities.

      Key Companies in the US AI in Biotechnology Market

      CompanyHQOwnershipStrongest segments
      NVIDIA CORPORATIONUnited StatesPublic CompanyData Center AI Compute & Networking,Gaming GPUs (GeForce),Professional Visualization (RTX/Quadro),
      ILLUMINA, INC.United StatesPublic CompanySequencing instruments,Sequencing consumables (reagents, flow cells, library prep),Arrays and genotyping consumables,
      RECURSIONUnited StatesPublic CompanyPlatform collaboration and milestones,Internal pipeline R&D funding (capitalized/other income),Other services and data partnerships,
      SCHRöDINGER, INC.United StatesPublic CompanySoftware,Drug Discovery – Collaborations (e.g., Novartis and others),Drug Discovery – Internal Pipeline,
      BENEVOLENTAIUnited KingdomPrivate CompanyAI discovery platform and licenses,Collaborative R&D projects and services,Custom data/ontology and analytics solutions,
      QIAGENNetherlandsPublic CompanySample technology consumables and instruments,Molecular diagnostics assays (TB, oncology, sexual and reproductive health, transplant, viral load),PCR and digital PCR instruments and consumables,
      TEMPUSUnited StatesPublic CompanyOncology NGS diagnostics (xT, xR, solid tumor and hematologic panels),Other diagnostics (PCR profiling, pathology, inherited conditions, pharmacogenomics nP),Data licensing and software (Insights, Lens, Hub, Next, Algos, Organoids, Trials),
      SOPHIA GENETICSSwitzerlandPublic CompanySOPHiA DDM platform subscriptions and usage-based analytics,Implementation, support, and workflow services,Biopharma collaborations and data-driven research solutions,
      PREDICTIVE ONCOLOGYUnited StatesPublic CompanyCompute Services and Treasury Management,Drug Discovery Services,
      XTALPI INC.ChinaPublic CompanyAI-driven drug discovery solutions (hit discovery, optimization, biology, PepiX),Computational software platforms (XFEP, XMolGen, PatSight, XtalGazer),Automation hardware and integrated workstations (XmartChem, ChemPlus),

      NVIDIA CORPORATION

      NVIDIA Corporation is a publicly traded technology company founded in 1993 and headquartered in the United States. With 42,000 employees, the company designs and manufactures graphics processing units and system-on-chip units. NVIDIA serves markets including gaming, professional visualization, data centers, and artificial intelligence.

      ILLUMINA, INC.

      Illumina, Inc. is a publicly traded genomics company founded in 1998 and based in the United States. The company employs 8,625 people and specializes in DNA sequencing and array-based technologies. Illumina's platforms are used for applications in research, clinical diagnostics, and precision medicine.

      RECURSION

      Recursion is a publicly traded biotechnology company founded in 2013 and headquartered in the United States. With 600 employees, the company uses machine learning and high-throughput biology to discover and develop therapeutics. Recursion focuses on identifying novel drug candidates through computational and experimental approaches.

      SCHRöDINGER, INC.

      Schrödinger, Inc. is a publicly traded computational chemistry and drug discovery company founded in 1990 and based in the United States. The company employs 850 people and develops software platforms for molecular simulation and drug design. Schrödinger's tools are used by pharmaceutical and biotechnology companies to accelerate drug development.

      BENEVOLENTAI

      BenevolentAI is a privately held artificial intelligence company founded in 2013 and headquartered in the United Kingdom. With 173 employees, the company applies machine learning and AI to drug discovery and development. BenevolentAI focuses on identifying new therapeutic targets and repurposing existing drugs for various diseases.

      QIAGEN

      QIAGEN is a publicly traded life sciences company founded in 1984 and headquartered in the Netherlands. With 5,500 employees, the company develops and manufactures sample preparation and molecular testing technologies. QIAGEN serves customers in molecular diagnostics, applied testing, and academic research.

      TEMPUS

      Tempus is a publicly traded artificial intelligence and precision medicine company founded in 2015 and based in the United States. With 3,800 employees, the company leverages machine learning and data analytics to improve cancer treatment and outcomes. Tempus analyzes clinical and molecular data to provide actionable insights for oncology care.

      SOPHIA GENETICS

      Sophia Genetics is a publicly traded digital health company founded in 2011 and headquartered in Switzerland. With 415 employees, the company develops AI-powered platforms for genomic data interpretation and clinical decision support. Sophia Genetics serves hospitals, diagnostic laboratories, and research institutions globally.

      PREDICTIVE ONCOLOGY

      Predictive Oncology is a publicly traded cancer diagnostics and treatment company founded in 2002 and based in the United States. With 14 employees, the company develops personalized medicine solutions for oncology patients. Predictive Oncology focuses on tumor profiling and treatment prediction technologies.

      XTALPI INC.

      XtalPi Inc. is a publicly traded artificial intelligence and drug discovery company founded in 2015 and headquartered in China. The company uses machine learning and computational chemistry to accelerate drug discovery and development. XtalPi focuses on molecular simulation and structure-based drug design.

      Reasons to Buy this Report

      • Strategic Market Sizing : Obtain precise US market valuations and growth projections to inform capital allocation decisions, competitive positioning, and long-term strategic planning in the rapidly expanding AI biotechnology sector.
      • Investment Opportunity Identification : Identify high-growth segments within the US market, including drug discovery platforms, precision medicine solutions, and computational biology tools, to guide venture capital and M&A strategies.
      • Competitive Landscape Intelligence : Understand the competitive dynamics specific to the US market, including key players, technology adoption rates, and market consolidation trends to benchmark performance and identify partnership opportunities.
      • Regulatory and Funding Insights : Access detailed analysis of US regulatory environment, government funding initiatives, and policy drivers shaping AI biotechnology adoption to navigate market entry and expansion strategies effectively.
      • Technology Trend Analysis : Gain comprehensive insights into emerging AI applications in US biotech, including machine learning algorithms, data analytics platforms, and integration patterns to stay ahead of market evolution.

      Frequently asked questions

      What is the current size of the US AI in Biotechnology Market in 2030?

      The US AI in Biotechnology Market is valued at $3,836.7 million in 2030, reflecting strong adoption of AI-driven drug discovery and precision medicine solutions across the US biotech sector.

      What is the projected market size for the US by 2035?

      The US AI in Biotechnology Market is forecast to reach $8,715.3 million by 2035, driven by continued innovation in computational biology and expanded clinical applications.

      What is the CAGR for the US AI in Biotechnology Market?

      The US market is expected to grow at an 18.0% compound annual growth rate from 2030 to 2035, outpacing many other healthcare technology segments.

      Which applications are driving growth in the US market?

      Key growth drivers in the US include AI-powered drug discovery, genomic analysis, clinical trial optimization, biomarker identification, and personalized medicine development.

      What factors support the US market's competitive advantage?

      The US benefits from leading biotech research institutions, substantial venture capital investment, FDA regulatory clarity, and strong partnerships between technology and life sciences companies.

      RESEARCH METHODOLOGY

      This market research study primarily relied on secondary sources, directories, and databases to collect information for this technical, market-oriented, and financial analysis of the AI in biotechnology market. In-depth interviews were conducted with various primary respondents, including key industry participants, subject-matter experts (SMEs), C-level executives from major market players, and industry consultants, among others, to gather and verify critical qualitative and quantitative data and assess market prospects. The size of the AI in biotechnology market was estimated using multiple secondary research methods and confirmed with inputs from primary research to determine the final market size.

      Secondary Research

      The secondary research process involved extensively using secondary sources, including directories, databases (such as Bloomberg Businessweek, Factiva, and D&B Hoovers), white papers, annual reports, company house documents, investor presentations, and SEC filings of companies. Some non-exclusive secondary sources include the World Health Organization (WHO), the Organization for Economic Co-operation and Development (OECD), Healthcare Information and Management Systems Society (HIMSS), Centers for Disease Control and Prevention (CDC), ClinicalTrials.gov, expert interviews, and MarketsandMarkets analysis.

      Secondary research was conducted to gather information for the detailed, technical, market-focused, and commercial analysis of the AI in biotechnology market. It was also used to collect key information about major players, market classification, and segmentation based on industry trends, down to the most detailed level, along with significant developments related to market and technology perspectives. Additionally, a database of leading industry players was compiled using secondary research.

      Primary Research

      During the primary research process, various sources from both the supply and demand sides were interviewed to gather qualitative and quantitative information for this report. Primary sources mainly include industry experts from core and related industries, preferred suppliers, manufacturers, distributors, technology developers, researchers, and organizations involved in all segments of this industry’s value chain. In-depth interviews were conducted with various primary respondents, such as key industry participants, subject-matter experts (SMEs), C-level executives of leading market players, and industry consultants, among other specialists, to obtain and verify critical qualitative and quantitative information as well as assess prospects.

      Primary research was conducted to identify segmentation types, industry trends, key players, and key market dynamics such as drivers, restraints, opportunities, challenges, and strategies adopted by key players.

      After completing the market engineering process- which includes calculations for market statistics, market breakdown, size estimations, forecasting, and data triangulation- extensive primary research was carried out. This research aimed to gather information and verify the key numbers obtained during the market analysis. Additionally, primary research was used to identify different types of market segmentation, analyze industry trends, evaluate the competitive landscape of AI solutions for biotechnology offered by various players, and understand key market dynamics such as drivers, restraints, opportunities, challenges, industry trends, and strategies employed by key market players.

      In the complete market engineering process, the top-down and bottom-up approaches, along with several data triangulation methods, were extensively used to estimate and forecast the market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was conducted on the entire market engineering process to identify key information and insights throughout the report.

      Breakdown of Primary Interviews

      AI in Biotechnology Market

      Note 1: Others include sales, marketing, and product managers.

      Note 2: Tiers are defined based on a company’s total revenue, as of 2024: Tier 1 = >USD 1 billion, Tier 2 = USD 500 million to USD 1 billion, and Tier 3 = < USD 500 million.

      To know about the assumptions considered for the study, download the pdf brochure

      Market Size Estimation

      The market size estimates and forecasts in this study are based on a combination of the bottom-up approach (revenue share analysis of leading players) and the top-down approach (evaluation of utilization, adoption, and penetration trends by offering, function, deployment mode, end user, and region).

      AI in Biotechnology Market

      Data Triangulation

      After determining the overall market size from the estimation process described above, the market for AI in biotechnology was divided into various segments and subsegments. To finalize the overall market analysis and obtain accurate statistics for all segments and subsegments, data triangulation and market breakdown techniques were used whenever applicable. The data was cross-verified by examining different factors and trends from both the demand and supply sides of the market for AI in biotechnology.

      Market Definition

      The AI in biotechnology market includes technologies that use artificial intelligence to advance drug discovery, genomics, and personalized medicine. This market is defined by the growing utilization of machine learning and data analytics to improve research and development efficiency.

      Stakeholders

      • Healthcare IT service providers
      • Pharmaceutical/Biopharmaceutical companies
      • Biotechnology firms
      • AI technology providers
      • Academic & research institutions
      • Academic medical centers/universities/hospitals
      • Regulatory agencies
      • Clinical research organizations (CROs)
      • Genomic testing labs
      • Government agencies
      • Startups in AI and biotech
      • Pharmaceutical supply chain partners
      • Consulting firms
      • Clinical trial management system providers
      • Bioinformatics companies
      • Advocacy groups
      • Investors & financial institutions

      Report Objectives

      • To define, describe, and forecast the AI in biotechnology market by offering, function, deployment mode, end user, and region
      • To provide detailed information regarding the major drivers, restraints, opportunities, and challenges influencing market growth
      • To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the overall AI in biotechnology market
      • To analyze market opportunities for stakeholders and provide details of the competitive landscape for key players
      • To forecast the size of the AI in biotechnology market in five main regions (and their respective countries): North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
      • To provide key industry insights, such as value chain, regulatory, patent, and recession impact analysis
      • To profile the key players in the market and comprehensively analyze their core competencies
      • To track and analyze competitive developments, such as product launches & upgrades, collaborations, partnerships, acquisitions, investments, contracts, agreements, alliances, mergers, funding, and expansions of the leading players in the market
      • To benchmark players within the market using the company evaluation matrix, which analyzes market players on various parameters within the broad categories of business strategy, market share, and product offering

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