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市场调查报告书
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1995877

基因组学市场中的人工智慧 (AI)：策略洞察与预测 (2026–2031)

Artificial Intelligence (AI) in Genomics Market - Strategic Insights and Forecasts (2026-2031)
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 144 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

全球基因组学领域的人工智慧 (AI) 市场预计将从 2026 年的 34 亿美元成长到 2031 年的 143 亿美元，复合年增长率为 33.3%。

基因组学领域的人工智慧（AI）市场处于先进数据分析与生命科学创新的交汇点。随着医疗保健系统向精准医疗、个人化疗法和数据驱动诊断转型，该领域正迅速扩张。定序技术产生的基因组数据量日益增长，对能够提取有意义的生物学见解的计算工具的需求也随之强劲增长。人工智慧技术正日益融入研究、药物发现和临床决策，进一步提升了该市场在整个医疗保健和生物技术生态系统中的战略重要性。

宏观经济驱动因素包括全球疾病负担（尤其是癌症）的加重、基因组学研究投资的增加以及药物研发管线的扩展。人工智慧能够高效分析复杂的基因数据，从而支持标靶治疗的开发并改善患者预后。运算能力、数位医疗基础设施和不断扩展的基因组资料库的整合正在加速人工智慧在研发和临床领域的应用。

市场驱动因素

精准医疗需求的日益增长是推动成长的主要动力。医疗服务提供者正越来越多地利用基因讯息，根据患者的个别特征优化治疗方案。人工智慧工具能够分析大规模基因组数据，帮助识别疾病风险、治疗路径和治疗结果。这项能力在肿瘤学领域尤其重要，因为早期检测和标靶治疗至关重要。

製药和生物技术产业也在推动人工智慧的应用。人工智慧透过识别疾病相关的遗传标记、预测治疗反应和缩短研究週期，加速了药物研发进程。分析大规模基因组数据集的能力提高了识别治疗标靶的准确性和效率。基因组研究投入的增加和定序成本的降低进一步推动了对人工智慧分析工具的需求。

全球癌症发生率不断上升，以及对更广泛疾病管理的需求日益增长，正在推动市场发展。人工智慧驱动的基因组学有助于早期检测和个人化治疗方案的製定，从而改善临床疗效，并最终在长期内降低医疗成本。

市场限制因素

儘管成长潜力巨大，但仍存在一些结构性挑战。基因组数据的复杂性需要高效能运算基础设施和先进的分析能力，这可能会增加营运成本。此外，不同资料来源的整合也为研究系统和临床系统之间的互通性带来了挑战。

数据品质和标准化问题限制了人工智慧模型的可靠性，尤其是在临床应用中。基因组资料集的差异性和隐私问题会限制资料共用和模型训练。有关病患资料使用的法规和伦理考量也给参与企业带来了合规负担。

此外，在医疗保健环境中，人工智慧产生的见解的可解释性对于临床可靠性和决策至关重要，但采用人工智慧仍然面临障碍。

对技术和细分市场的洞察

在市场区隔中，产品分为软体工具和服务两大类。软体平台构成基因组数据解读的分析基础，而服务则支持实施、咨询和研究整合。

就应用领域而言，精准医疗是主要应用场景，其次是诊断和预后、药物发现和开发以及农业基因组学。药物发现应用尤其重要，因为它们需要有效率地识别基因标靶和治疗路径。

终端用户包括製药和生物技术公司、学术和研究机构、医院以及诊断中心。由于基因组治疗方法研发需求旺盛且投资不断增加，製药公司仍是主要采用者。

从区域上看，北美占据了较大的市场份额，这得益于其强大的研究基础设施、先进的医疗保健系统以及对基因组学创新的巨额投资。

竞争格局与策略展望

竞争格局包括技术提供者、基因组学专家和医疗保健分析公司。主要企业致力于开发先进的人工智慧模型、扩展数据整合能力并加强研究合作。

生物技术公司与人工智慧技术公司之间的策略合作日益增加。对预测分析、疾病风险建模和个人化治疗平台的投资正在推动创新。定序、计算生物学和知识图谱分析等领域的持续技术进步可望提升市场竞争力。

市场竞争也受到研究经费、平台扩充性和监管合规框架的影响。

重点

基因组学领域的人工智慧市场正发展成为现代医疗创新不可或缺的一部分。对精准医疗的强劲需求、计算分析技术的快速发展以及不断扩大的研究活动正在推动该领域的持续成长。儘管数据管理和监管方面的挑战仍然存在，但持续的技术进步和策略合作有望支撑市场的长期扩张。

本报告的主要益处

  • 深入分析：获得跨地区、客户群、政策、社会经济因素、消费者偏好和产业领域的详细市场洞察。
  • 竞争格局：了解主要企业的策略趋势，并确定最佳的市场进入方式。
  • 市场驱动因素和未来趋势：我们将评估影响市场的主要成长要素和新兴趋势。
  • 实用建议：我们支援制定策略决策以开发新的收入来源。
  • 适合各类读者：非常适合Start-Ups、研究机构、顾问公司、中小企业和大型企业。

我们的报告的使用范例

产业和市场洞察、机会评估、产品需求预测、打入市场策略、区域扩张、资本投资决策、监管分析、新产品开发和竞争情报。

报告范围

  • 2021年至2025年的历史数据和2026年至2031年的预测数据
  • 成长机会、挑战、供应链前景、法律规范与趋势分析
  • 评估竞争对手的市场定位、策略和市场占有率。
  • 细分市场和区域销售成长及预测评估
  • 公司简介，包括策略、产品、财务状况和主要发展动态。

目录

第一章：引言

  • 市场概览
  • 市场的定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年及预测年调查期
  • 相关人员的主要收益

第二章：调查方法

  • 调查设计
  • 研究过程

第三章执行摘要

  • 主要发现

第四章 市场动态

  • 市场驱动因素
  • 市场限制因素
  • 波特五力分析
  • 产业价值链分析
  • 分析师意见

第五章：基因组学市场：依产品/服务分类

  • 软体工具
  • 服务

第六章：基因体学市场：依应用领域划分

  • 精准医疗
  • 诊断和预后
  • 药物发现与开发
  • 农业和畜牧业
  • 其他的

第七章 基因组学市场：依最终用户划分

  • 製药和生物技术公司
  • 学术研究机构
  • 医院和诊断中心
  • 其他的

第八章 基因组学市场：按地区划分

  • 北美洲
    • 报价
    • 透过使用
    • 最终用户
    • 国家
      • 我们
      • 加拿大
      • 墨西哥
  • 南美洲
    • 报价
    • 透过使用
    • 最终用户
    • 国家
      • 巴西
      • 阿根廷
      • 其他的
  • 欧洲
    • 报价
    • 透过使用
    • 最终用户
    • 国家
      • 英国
      • 德国
      • 法国
      • 西班牙
      • 其他的
  • 中东和非洲
    • 报价
    • 透过使用
    • 最终用户
    • 国家
      • 沙乌地阿拉伯
      • 以色列
      • UAE
      • 其他的
  • 亚太地区
    • 报价
    • 透过使用
    • 最终用户
    • 国家
      • 中国
      • 日本
      • 印度
      • 韩国
      • 澳洲
      • 越南
      • 印尼
      • 其他的

第九章：竞争环境与分析

  • 主要企业及策略分析
  • 市占率分析
  • 合併、收购、协议和合作关係
  • 竞争环境仪錶板

第十章：公司简介

  • IBM
  • Sophia Genetics SA
  • QIAGEN NV
  • Fabric Genomics, Inc.
  • Congenica Ltd.
  • Illumina, Inc.
  • Freenome Holdings, Inc.
  • Data4cure, Inc.
  • Tempus Labs, Inc.
  • NVIDIA Corporation
简介目录
Product Code: KSI061614431

The Global Artificial Intelligence (AI) in Genomics market is forecast to grow at a CAGR of 33.3%, reaching USD 14.3 billion in 2031 from USD 3.4 billion in 2026.

The artificial intelligence in genomics market is positioned at the intersection of advanced data analytics and life sciences innovation. The sector is expanding rapidly as healthcare systems shift toward precision medicine, personalized therapies, and data-driven diagnostics. Growing volumes of genomic data generated through sequencing technologies are creating strong demand for computational tools capable of extracting meaningful biological insights. AI technologies are increasingly embedded in research, drug discovery, and clinical decision-making, strengthening the strategic importance of this market across healthcare and biotechnology ecosystems.

Macroeconomic drivers include rising global disease burden, particularly cancer, increasing investments in genomics research, and expanding pharmaceutical research pipelines. AI is enabling efficient analysis of complex genetic data, supporting targeted treatment development and improved patient outcomes. The convergence of computing power, digital health infrastructure, and expanding genomic databases is accelerating adoption across both research and clinical environments.

Market Drivers

The growing demand for precision medicine is a primary growth catalyst. Healthcare providers are increasingly using genetic information to tailor treatments based on individual patient profiles. AI tools enable large-scale genomic data interpretation, helping identify disease risks, treatment pathways, and therapy effectiveness. This capability is particularly valuable in oncology, where early detection and targeted therapies are critical.

Pharmaceutical and biotechnology industries are also driving adoption. AI accelerates drug discovery by identifying genetic markers linked to disease, predicting treatment responses, and reducing research timelines. The ability to analyze large genomic datasets improves accuracy and efficiency in identifying therapeutic targets. Increasing investment in genomic research and declining sequencing costs are further supporting demand for AI-enabled analytical tools.

Rising global cancer incidence and broader disease management needs are strengthening market momentum. AI-based genomics supports early detection and personalized treatment planning, improving clinical outcomes and reducing healthcare costs over time.

Market Restraints

Despite strong growth potential, several structural challenges remain. Genomic data complexity requires high-performance computing infrastructure and advanced analytical capabilities, which can increase operational costs. Integration of diverse data sources also presents interoperability challenges across research and clinical systems.

Data quality and standardization issues limit the reliability of AI models, particularly in clinical applications. Variability in genomic datasets and privacy concerns can restrict data sharing and model training. Regulatory and ethical considerations around patient data usage also create compliance burdens for market participants.

Additionally, adoption barriers remain in healthcare environments where interpretability of AI-generated insights is critical for clinical trust and decision-making.

Technology and Segment Insights

The market is segmented by offering into software tools and services. Software platforms form the analytical backbone of genomic data interpretation, while services support implementation, consulting, and research integration.

By application, precision medicine represents a central use case, followed by diagnosis and prognosis, drug discovery and development, and agricultural genomics. Drug discovery applications are particularly significant due to the need for efficient identification of genetic targets and therapeutic pathways.

End-user segmentation includes pharmaceutical and biotechnology companies, academic and research institutions, and hospitals and diagnostic centers. Pharmaceutical companies remain major adopters due to intensive research requirements and growing investment in genomic-based therapies.

Geographically, North America holds a substantial market share, supported by strong research infrastructure, advanced healthcare systems, and significant investment in genomics innovation.

Competitive and Strategic Outlook

The competitive environment includes technology providers, genomics specialists, and healthcare analytics firms. Key players are focused on developing advanced AI models, expanding data integration capabilities, and strengthening research collaborations.

Strategic partnerships between biotech firms and AI technology companies are increasing. Investment in predictive analytics, disease risk modeling, and personalized treatment platforms is shaping innovation. Ongoing technological development in sequencing, computational biology, and knowledge graph analytics is expected to enhance market capabilities.

Market competition is also influenced by research funding, platform scalability, and regulatory compliance frameworks.

Key Takeaways

The artificial intelligence in genomics market is evolving into a critical component of modern healthcare innovation. Strong demand for precision medicine, rapid advances in computational analytics, and expanding research activity are driving sustained growth. While data management and regulatory challenges persist, continued technological progress and strategic collaborations are expected to support long-term market expansion.

Key Benefits of this Report

  • Insightful Analysis: Gain detailed market insights across regions, customer segments, policies, socio-economic factors, consumer preferences, and industry verticals.
  • Competitive Landscape: Understand strategic moves by key players to identify optimal market entry approaches.
  • Market Drivers and Future Trends: Assess major growth forces and emerging developments shaping the market.
  • Actionable Recommendations: Support strategic decisions to unlock new revenue streams.
  • Caters to a Wide Audience: Suitable for startups, research institutions, consultants, SMEs, and large enterprises.

What businesses use our reports for

Industry and market insights, opportunity assessment, product demand forecasting, market entry strategy, geographical expansion, capital investment decisions, regulatory analysis, new product development, and competitive intelligence.

Report Coverage

  • Historical data from 2021 to 2025 and forecast data from 2026 to 2031
  • Growth opportunities, challenges, supply chain outlook, regulatory framework, and trend analysis
  • Competitive positioning, strategies, and market share evaluation
  • Revenue growth and forecast assessment across segments and regions
  • Company profiling including strategies, products, financials, and key developments

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base and Forecast Years Timeline
  • 1.8. Key Benefits for the Stakeholders

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Process

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. AI IN GENOMICS MARKET BY OFFERING

  • 5.1. Introduction
  • 5.2. Software tools
  • 5.3. Services

6. AI IN GENOMICS MARKET BY APPLICATION

  • 6.1. Introduction
  • 6.2. Precision medicine
  • 6.3. Diagnosis and prognosis
  • 6.4. Drug discovery and development
  • 6.5. Agriculture and animal breeding
  • 6.6. Others

7. AI IN GENOMICS MARKET BY END-USER

  • 7.1. Introduction
  • 7.2. Pharmaceutical and biotechnology companies
  • 7.3. Academic and research institutes
  • 7.4. Hospitals and diagnostic centers
  • 7.5. Others

8. AI IN GENOMICS MARKET BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. By Offering
    • 8.2.2. By Application
    • 8.2.3. By End-User
    • 8.2.4. By Country
      • 8.2.4.1. USA
      • 8.2.4.2. Canada
      • 8.2.4.3. Mexico
  • 8.3. South America
    • 8.3.1. By Offering
    • 8.3.2. By Application
    • 8.3.3. By End-User
    • 8.3.4. By Country
      • 8.3.4.1. Brazil
      • 8.3.4.2. Argentina
      • 8.3.4.3. Others
  • 8.4. Europe
    • 8.4.1. By Offering
    • 8.4.2. By Application
    • 8.4.3. By End-User
    • 8.4.4. By Country
      • 8.4.4.1. United Kingdom
      • 8.4.4.2. Germany
      • 8.4.4.3. France
      • 8.4.4.4. Spain
      • 8.4.4.5. Others
  • 8.5. Middle East and Africa
    • 8.5.1. By Offering
    • 8.5.2. By Application
    • 8.5.3. By End-User
    • 8.5.4. By Country
      • 8.5.4.1. Saudi Arabia
      • 8.5.4.2. Israel
      • 8.5.4.3. UAE
      • 8.5.4.4. Others
  • 8.6. Asia Pacific
    • 8.6.1. By Offering
    • 8.6.2. By Application
    • 8.6.3. By End-User
    • 8.6.4. By Country
      • 8.6.4.1. China
      • 8.6.4.2. Japan
      • 8.6.4.3. India
      • 8.6.4.4. South Korea
      • 8.6.4.5. Australia
      • 8.6.4.6. Vietnam
      • 8.6.4.7. Indonesia
      • 8.6.4.8. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. IBM
  • 10.2. Sophia Genetics SA
  • 10.3. QIAGEN N.V.
  • 10.4. Fabric Genomics, Inc.
  • 10.5. Congenica Ltd.
  • 10.6. Illumina, Inc.
  • 10.7. Freenome Holdings, Inc.
  • 10.8. Data4cure, Inc.
  • 10.9. Tempus Labs, Inc.
  • 10.10. NVIDIA Corporation