바이오테크놀러지용 AI 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the aI in biotechnology market size was valued at USD 6.5 billion in 2025 and is estimated to grow from USD 8.5 billion in 2026 to reach USD 31.23 billion by 2031, at a CAGR of 29.70% during the forecast period (2026-2031).

This report is Segmented by Offering (Software, Hardware, Services), Application (Drug Discovery, Multi-Omics, Clinical Development, Diagnostics, Bioprocessing), Technology (ML, Computer Vision, and More), Deployment (Cloud, Hybrid, On-Premises), End User (Pharma, Biotech, CROs/CDMOs, Academic, Healthcare), and Geography (North America, Europe, and More). Value Forecasts (USD).

Global AI In Biotechnology Market Trends and Insights

AI-Led Drug Discovery Accelerates

AI is driving significant advancements in early drug discovery, focusing on speed and compound efficiency alongside model performance. In 2025, Rentosertib became the first fully AI-designed and AI-discovered drug to complete Phase IIa trials, showing a mean forced vital capacity improvement of +98.4 mL compared to -20.3 mL for placebo in idiopathic pulmonary fibrosis patients. Recursion demonstrated its platform's efficiency by synthesizing nearly 330 compounds per program in 17 months, compared to the industry average of 2,500 compounds in 42 months, with its REC-4881 program achieving a 43% median reduction in total polyp burden at 12 weeks in Phase 2 patients.These developments highlight how AI is reshaping drug discovery economics, enabling pharmaceutical companies to diversify targets and indications, reducing reliance on conservative approaches.

Precision Medicine and Biomarkers Take Center Stage

The AI in biotechnology market is advancing with biomarker-guided research, where model quality depends on integrating molecular, clinical, and patient-level data. Sanofi's AI Research Factory improved active ingredient identification in immunology, oncology, and neurology by 20-30% over traditional methods, doubling the number of biologics and vaccines developed with AI since 2019. Precision medicine programs require robust patient stratification, biomarker selection, and early response variability insights. AI platforms capable of analyzing genomic and transcriptomic layers are enabling sponsors to identify enriched populations early, making smaller, complex patient groups commercially viable, especially in rare diseases and specialty areas.

High Implementation and Validation Costs

The AI biotechnology market faces high entry barriers due to production-grade deployment costs exceeding pilot budgets. Challenges extend beyond model building to include data cleaning, workflow integration, validation records, and internal team support for regulated use. Smaller biotechnology firms and academic spinouts often lag large pharmaceutical companies by 12-24 months in commercial deployment due to the absence of established legal and computational frameworks. Limited access to GPUs and specialized infrastructure outside major U.S. hubs further favors well-funded platforms and large enterprise buyers, slowing smaller firms' transition from experimental AI drug discovery to operational use.

Other drivers and restraints analyzed in the detailed report include:

1. Harnessing the Power of Vast Genomic and Multi-Omics Datasets
2. Biopharma-Tech Collaborations Gain Momentum
3. Data Privacy and Regulatory Compliance Challenges

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

In 2025, software accounted for 38.25% of the AI in biotechnology market, maintaining its leading position among offerings. This dominance stems from platform-driven business models by companies like Insilico Medicine and Recursion Pharmaceuticals, leveraging recurring revenues through licenses and API access. The reuse of trained models across multiple programs without proportional cost increases further strengthens software's role. Eli Lilly's TuneLab platform, launched in September 2025, exemplifies scalable software delivery by providing external partners access to drug discovery models while safeguarding proprietary data. Software remains the revenue anchor, aligning with pharmaceutical companies' needs for accessible models and workflows.

Services are the fastest-growing segment in the AI in biotechnology market, with a projected CAGR of 31.45% through 2031. Many drug manufacturers prefer outsourcing tasks like model development and data curation instead of building in-house capabilities. This trend persists as successful deployment requires domain expertise, model tuning, and regulatory support, beyond just tool access.

Drug discovery and development held 45.3% of the AI in biotechnology market share in 2025, making it the largest application area. AI-first platforms significantly reduce synthesized molecules per program by over 90% while maintaining or improving hit rates. Recursion's platform generates over 100 million molecules annually, reducing wet-lab work by 40% and addressing cost and timing challenges in pharmaceutical R&D. AI drug discovery drives adoption by narrowing candidate pools, improving prioritization, and minimizing lab work before advancing programs.

Clinical development is the fastest-growing application in the AI in biotechnology market, with a projected CAGR of 33.24% through 2031. AI enhances trial operations by improving speed, enrollment planning, and execution. For example, AI platforms have reduced patient registration times and Phase III costs significantly. These operational gains justify broader AI deployment in clinical development, making it the fastest-growing area while drug discovery remains the largest application.

Geography Analysis

In 2025, North America commanded a dominant 41.7% share of the AI in biotechnology market, solidifying its top regional position. The region benefits from a strong venture capital base, extensive AI research talent, and a high concentration of pharmaceutical R&D headquarters. Significant infrastructure investments connect computing, biology, and drug development, with major collaborations reflecting the scale of investment in shared discovery environments. This combination of resources positions North America as a leader in platform development and enterprise adoption.

Europe holds a significant position in the AI in biotechnology market, combining a strong pharmaceutical foundation with a coordinated AI policy framework. Key hubs like Germany, the UK, France, Italy, and Spain drive commercial activity, while Austria and Nordic countries contribute research depth. The region's interconnected academic, biotech, and pharmaceutical networks support adoption across discovery and translational research. Stricter governance adds compliance challenges but establishes a formal framework for healthcare AI.

Asia-Pacific is the fastest-growing region in the AI in biotechnology market, with a forecast CAGR of 35.5% through 2031. Growth is driven by policy support, expanding research capacity, and local platform development in China, Japan, South Korea, and India. Milestones include China's launch of an AI-driven drug virtual screening platform and the introduction of AI Kongming for intelligent drug design. These developments highlight the region's focus on building domestic models and scalable research systems. The Middle East and Africa remain in early stages, with GCC precision medicine programs and South Africa's genomics base laying the groundwork for future adoption. South America, led by Brazil's clinical research ecosystem, is also in the early stages of development. While smaller today, these regions are building the foundation for broader AI adoption in biotechnology workflows. North America leads, Europe remains pivotal, and Asia-Pacific drives the fastest growth.

1. BenevolentAI SA
2. BPGbio, Inc.
3. CytoReason Ltd.
4. Deep Genomics, Inc.
5. DNAnexus, Inc.
6. Genialis, Inc.
7. Iktos SA
8. Illumina
9. Insilico Medicine
10. Insitro, Inc.
11. NVIDIA
12. Owkin, Inc.
13. PathAI, Inc.
14. QIAGEN
15. Recursion Pharmaceuticals
16. Schropdinger, Inc.
17. SOPHiA GENETICS SA
18. Tempus AI, Inc.
19. Valo Health, Inc.
20. XtalPi, Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 Introduction

• 1.1 Study Assumptions & Market Definition
• 1.2 Scope of the Study

2 Research Methodology

3 Executive Summary

4 Market Landscape

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 AI-Led Drug Discovery Acceleration
  • 4.2.2 Precision Medicine and Biomarker-Guided Therapeutics
  • 4.2.3 Scaling Genomic and Multi-Omics Datasets
  • 4.2.4 Biopharma-Tech Partnerships and Funding Momentum
  • 4.2.5 Self-Driving Labs and Closed-Loop Wet-Lab Automation
  • 4.2.6 Federated Multi-Institution Model Training
• 4.3 Market Restraints
  • 4.3.1 High Implementation and Validation Cost
  • 4.3.2 Data Privacy and Regulatory Compliance Burden
  • 4.3.3 GPU and Advanced Compute Bottlenecks
  • 4.3.4 IP And GxP Auditability Uncertainty
• 4.4 Value / Supply-Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Competitive Rivalry

5 Market Size & Growth Forecasts (Value, USD)

• 5.1 By Offering
  • 5.1.1 Software
  • 5.1.2 Hardware
  • 5.1.3 Services
• 5.2 By Application
  • 5.2.1 Drug Discovery and Development
  • 5.2.2 Genomics and Multi-Omics Analysis
  • 5.2.3 Clinical Development
  • 5.2.4 Diagnostics and Decision Support
  • 5.2.5 Precision Medicine
  • 5.2.6 Bioprocessing and Manufacturing
• 5.3 By Technology
  • 5.3.1 Machine Learning and Deep Learning
  • 5.3.2 Generative AI and Foundation Models
  • 5.3.3 Natural Language Processing and Knowledge Graphs
  • 5.3.4 Computer Vision
  • 5.3.5 Graph, Causal, and Systems Biology Models
• 5.4 By Deployment Mode
  • 5.4.1 Cloud-Based
  • 5.4.2 Hybrid
  • 5.4.3 On-Premises
• 5.5 By End User
  • 5.5.1 Pharmaceutical Companies
  • 5.5.2 Biotechnology Companies
  • 5.5.3 CROs and CDMOs
  • 5.5.4 Academic and Research Institutes
  • 5.5.5 Healthcare Providers and Diagnostic Laboratories
• 5.6 By Geography
  • 5.6.1 North America
    • 5.6.1.1 United States
    • 5.6.1.2 Canada
    • 5.6.1.3 Mexico
  • 5.6.2 Europe
    • 5.6.2.1 Germany
    • 5.6.2.2 United Kingdom
    • 5.6.2.3 France
    • 5.6.2.4 Italy
    • 5.6.2.5 Spain
    • 5.6.2.6 Rest of Europe
  • 5.6.3 Asia-Pacific
    • 5.6.3.1 China
    • 5.6.3.2 India
    • 5.6.3.3 Japan
    • 5.6.3.4 South Korea
    • 5.6.3.5 Australia
    • 5.6.3.6 Rest of Asia-Pacific
  • 5.6.4 Middle East and Africa
    • 5.6.4.1 GCC
    • 5.6.4.2 South Africa
    • 5.6.4.3 Rest of Middle East and Africa
  • 5.6.5 South America
    • 5.6.5.1 Brazil
    • 5.6.5.2 Argentina
    • 5.6.5.3 Rest of South America

6 Competitive Landscape

• 6.1 Market Concentration
• 6.2 Market Share Analysis
• 6.3 Company Profiles (includes Global level Overview, Market-level Overview, Core Segments, Financials, Strategic Information, Market Rank/Share, Products & Services, Recent Developments)
  • 6.3.1 BenevolentAI SA
  • 6.3.2 BPGbio, Inc.
  • 6.3.3 CytoReason Ltd.
  • 6.3.4 Deep Genomics, Inc.
  • 6.3.5 DNAnexus, Inc.
  • 6.3.6 Genialis, Inc.
  • 6.3.7 Iktos SA
  • 6.3.8 Illumina, Inc.
  • 6.3.9 Insilico Medicine
  • 6.3.10 Insitro, Inc.
  • 6.3.11 NVIDIA Corporation
  • 6.3.12 Owkin, Inc.
  • 6.3.13 PathAI, Inc.
  • 6.3.14 QIAGEN N.V.
  • 6.3.15 Recursion Pharmaceuticals, Inc.
  • 6.3.16 Schropdinger, Inc.
  • 6.3.17 SOPHiA GENETICS SA
  • 6.3.18 Tempus AI, Inc.
  • 6.3.19 Valo Health, Inc.
  • 6.3.20 XtalPi, Inc.

7 Market Opportunities & Future Outlook

• 7.1 White-space and unmet-need assessment