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市場調查報告書
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2045950

基因組學人工智慧市場—全球產業規模、佔有率、趨勢、機會和預測：按組件、技術、功能、應用、最終用途、地區和競爭格局分類，2021-2031年

AI In Genomics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Technology, By Functionality, By Application, By End Use, By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 180 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球基因組學人工智慧市場預計將從 2025 年的 7.3303 億美元成長到 2031 年的 13.1498 億美元，複合年成長率為 10.23%。

該領域專注於運用機器學習演算法和計算智慧來解讀複雜的基因資料集，從而推動精準醫療、臨床診斷和藥物研發的進步。其關鍵成長要素包括DNA定序成本的大幅下降，以及對需要快速分析生物數據的個人化醫療解決方案的迫切需求。根據全球基因組學與醫療保健聯盟（Global Alliance for Genomics and Healthcare）預測，到2024年，其合作夥伴網路將管理超過300萬個基因組，產生大量標準化數據，這些數據對於訓練穩健、高效能的模型至關重要。這為該領域的快速發展奠定了基礎。

市場概覽
預測期 2027-2031
市場規模：2025年 7.3303億美元
市場規模：2031年 1,314,980,000 美元
複合年成長率：2026-2031年 10.23%
成長最快的細分市場 機器學習
最大的市場 北美洲

然而，阻礙市場進一步擴張的一大挑戰是資料隱私和倫理管治嚴格的法規環境。由於基因組資料固有的保密性，必須嚴格遵守國際資料保護框架，這往往導致資訊孤島，阻礙跨國合作。這些複雜的法律和倫理障礙使得演算法檢驗所需的資料共用難以實現，並可能延緩人工智慧工具在不同醫療保健系統中的商業化和部署。

市場促進因素

傳統藥物研發成本不斷攀升且失敗率居高不下，引發了對加速藥物發現和研發的需求，而這正成為市場擴張的主要催化劑。人工智慧技術正被日益廣泛地應用於簡化標靶識別和檢驗，顯著縮短了新治療方法進入臨床試驗階段所需的時間。大量資金湧入人工智慧原生生技公司，正是這股趨勢的象徵，也凸顯了這些運算方法的商業性可行性。例如，2024年4月，Xaira Therapeutics宣布已籌集10億美元承諾資本，用於啟動運營，旨在透過生成式人工智慧模型革新藥物發現。這凸顯了業界正朝著將計算生物學作為開發有效藥物的標準方法的方向轉變。

同時，人工智慧和機器學習能力的快速發展正在打破傳統的技術壁壘，使得多模態基因組資料集的精準解讀成為可能。生成式人工智慧和專用微服務的出現，讓研究人員能夠以前所未有的速度和精確度模擬複雜的生物交互作用，超越簡單的序列比對，邁向預測性功能基因體學。 2024年3月，NVIDIA宣布推出約25項全新的生成式人工智慧微服務，旨在加速藥物發現和基因組學工作流程。此外，演算法的日益精進也提高了預測的準確性。 2024年5月，GoogleDeepMind報告稱，其AlphaFold 3模型在蛋白質-配體相互作用的預測準確率方面，相比傳統方法至少提高了50%。這標誌著基因組分析在精準醫療應用領域取得了根本性的飛躍。

市場挑戰

圍繞著資料隱私和倫理管治的嚴格監管環境，對全球基因組學領域人工智慧市場的成長構成了重大障礙。人工智慧演算法需要龐大且多樣化的資料集來識別罕見的基因關聯並驗證精準醫療模型，但不同的國際資料保護法迫使各機構將資訊儲存在孤立的系統中。這種分散化阻礙了跨國資料聚合，而跨境資料聚合對於檢驗通用模型至關重要，從而限制了人工智慧工具在不同人群中的診斷準確性。

此外，遵守這些不同框架的複雜性增加了營運成本，延長了研發週期，並有效地延緩了基因組創新成果的商業化進程。對違規和數據濫用的擔憂嚴重阻礙了醫療專業人員對這些技術的採用，而這對市場擴張至關重要。根據美國醫學會 (AMA) 預測，到 2024 年，87% 的醫生會將資料隱私保障視為在臨床實踐中部署人工智慧驅動工具的關鍵要求。這種由監管複雜性導致的普遍抵觸情緒，直接減緩了個人化醫療解決方案的普及，並限制了市場的擴充性。

市場趨勢

大規模基因組模型的出現標誌著從特定任務演算法到能夠解讀跨越不同生物領域生命基本密碼的通用架構的關鍵轉變。與以往僅限於狹窄應用的模型不同，這些「DNA語言模型」利用龐大的未註釋序列語料庫進行自監督學習，無需顯式標記即可解讀複雜的演化模式和非編碼區域的功能。這種架構上的進步使得以前所未有的預測精度產生新型基因組序列成為可能，加速了合成生物學的突破性進展。據Arc研究所稱，他們在2025年2月發布了「Evo 2」模型，該模型基於來自超過12.8萬個基因組的9.3兆個DNA鹼基對進行訓練，在預測突變效應和設計合成生物學系統方面達到了最先進的精度。

同時，人工智慧驅動的精準腫瘤學工具的普及正在推動臨床診斷的快速商業化，基因組分析也正從研究實驗室走向常規患者照護。人工智慧原生診斷公司透過整合多分子臨床和分子數據來拓展業務，有效地彌合了定序能力與可操作治療見解之間的差距。這種應用激增表明，醫療服務提供者在製定複雜癌症病例的治療決策時越來越依賴計算智慧，凸顯了市場向可擴展的臨床效用發展的趨勢。根據Tempus AI截至2025年8月的會計年度財務報告，其基因組學相關收入年增115.3%至2.418億美元，這支撐了其人工智慧驅動的腫瘤檢測產品組合處理量的加速成長。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：全球基因組學人工智慧市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 按組件（硬體、軟體、服務）
    • 依技術分類（機器學習{深度學習、監督學習、無監督學習等}、電腦視覺）
    • 按功能（基因測序、基因編輯等）
    • 按應用領域（藥物發現/開發、精準醫療、診斷等）
    • 依最終用途（製藥和生物技術公司、醫療保健提供者、研究機構、其他）
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美基因組學人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國別分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲基因組學人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國別分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太地區基因組學人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國別分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲基因組學人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東與非洲：國別分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：南美洲基因組學人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國別分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進因素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 近期趨勢

第13章：全球基因體學中的人工智慧市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的潛力
  • 供應商的議價能力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

  • IBM Corp.
  • Deep Genomics Inc.
  • Nvidia Corporation
  • Data4Cure, Inc.
  • Illumina, Inc.
  • Thermo Fisher Scientific Inc.
  • Sophia Genetics SA
  • Freenome Holdings, Inc.
  • BenevolentAI Ltd.
  • Genentech, Inc.

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
Product Code: 23959

The Global AI in Genomics Market is projected to expand from USD 733.03 Million in 2025 to USD 1314.98 Million by 2031, registering a CAGR of 10.23%. This sector centers on the utilization of machine learning algorithms and computational intelligence to decode intricate genetic datasets, thereby fostering advancements in precision medicine, clinical diagnostics, and drug discovery. A primary growth engine is the substantial decrease in DNA sequencing costs coupled with the urgent demand for personalized healthcare solutions that necessitate the rapid analysis of biological data. According to the Global Alliance for Genomics and Health, in 2024, their partner network managed over 3,000,000 genomes, creating a massive volume of standardized data essential for training robust, high-performance models, which serves as a foundational pillar for the sector's accelerated development.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 733.03 Million
Market Size 2031USD 1314.98 Million
CAGR 2026-203110.23%
Fastest Growing SegmentMachine Learning
Largest MarketNorth America

Nevertheless, a major challenge hindering broader market scalability is the strict regulatory environment regarding data privacy and ethical governance. The inherent sensitivity of genomic data demands rigorous adherence to international data protection frameworks, often resulting in informational silos that impede cross-border collaboration. These complex legal and ethical obstacles complicate the data sharing required for algorithmic validation, potentially delaying the commercialization and deployment of AI tools across diverse healthcare systems.

Market Driver

The imperative to accelerate drug discovery and development acts as a primary catalyst for market expansion, driven by the escalating costs and high failure rates associated with traditional pharmacological research. AI technologies are increasingly deployed to streamline target identification and validation, significantly reducing the time required to advance novel therapies to clinical trials. This trend is exemplified by substantial capital inflows into AI-native biotech firms, which confirm the commercial viability of these computational approaches. For instance, Xaira Therapeutics announced in April 2024 that it launched with $1 billion in committed capital to revolutionize drug development through generative AI models, underscoring the industry's pivot toward computational biology as a standard modality for creating effective medicines.

Simultaneously, rapid advancements in AI and machine learning capabilities are dismantling previous technical barriers, enabling the precise interpretation of multimodal genomic datasets. The emergence of generative AI and specialized microservices allows researchers to model complex biological interactions with unprecedented speed and fidelity, moving beyond simple sequence alignment to predictive functional genomics. In March 2024, NVIDIA introduced roughly 25 new generative AI microservices specifically designed to accelerate workflows in drug discovery and genomics. Furthermore, algorithmic sophistication is enhancing predictive precision; in May 2024, Google DeepMind reported that its AlphaFold 3 model demonstrated at least a 50% improvement in prediction accuracy for protein-ligand interactions compared to traditional methods, marking a fundamental leap for scaling genomic analysis in precision medicine applications.

Market Challenge

The stringent regulatory landscape surrounding data privacy and ethical governance constitutes a formidable barrier to the growth of the Global AI in Genomics Market. While AI algorithms require vast, diverse datasets to identify rare genetic correlations and validate precision medicine models, varying international data protection laws compel organizations to store information in isolated silos. This fragmentation prevents the cross-border data aggregation necessary for training universally applicable models, thereby limiting the diagnostic accuracy of AI tools across different demographics.

Furthermore, the complexity of adhering to these divergent frameworks increases operational costs and extends development timelines, effectively slowing the commercialization of genomic innovations. The fear of non-compliance and data misuse significantly stalls the adoption of these technologies among practitioners who are essential for market expansion. According to the American Medical Association, in 2024, 87% of physicians cited data privacy assurances as a critical requirement before they would integrate AI-driven tools into their clinical practices. This widespread reluctance, driven by regulatory complexities, directly delays the deployment of personalized healthcare solutions and restricts the market's scalability.

Market Trends

The emergence of Large Genomic Foundation Models marks a pivotal shift from task-specific algorithms to generalized architectures capable of interpreting the fundamental code of life across diverse biological domains. Unlike earlier models limited to narrow applications, these "DNA language models" utilize self-supervised learning on vast corpora of unannotated sequences to decipher complex evolutionary patterns and non-coding region functions without explicit labeling. This architectural advancement enables the generative design of novel genomic sequences with unprecedented predictive fidelity, facilitating breakthroughs in synthetic biology. According to the Arc Institute, in February 2025, the organization introduced its Evo 2 model, trained on 9.3 trillion DNA base pairs from over 128,000 genomes, achieving state-of-the-art accuracy in predicting mutation effects and designing synthetic biological systems.

Concurrently, the proliferation of AI-enhanced precision oncology tools is driving the rapid commercialization of clinical diagnostics, transitioning genomic analysis from research laboratories to routine patient care. AI-native diagnostic firms are scaling their operations by integrating multimodal clinical and molecular data, effectively bridging the gap between sequencing capabilities and actionable therapeutic insights. This surge in adoption demonstrates that healthcare providers are increasingly relying on computational intelligence to guide treatment decisions for complex cancer cases, validating the market's move toward scalable clinical utility. According to Tempus AI's August 2025 earnings report, the company's genomics revenue increased 115.3% year-over-year to $241.8 million, underscored by accelerating volume growth in its AI-enabled oncology testing portfolio.

Key Market Players

  • IBM Corp.
  • Deep Genomics Inc.
  • Nvidia Corporation
  • Data4Cure, Inc.
  • Illumina, Inc.
  • Thermo Fisher Scientific Inc.
  • Sophia Genetics S.A.
  • Freenome Holdings, Inc.
  • BenevolentAI Ltd.
  • Genentech, Inc.

Report Scope

In this report, the Global AI In Genomics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI In Genomics Market, By Component

  • Hardware
  • Software
  • Services

AI In Genomics Market, By Technology

  • Machine Learning
  • Computer Vision

AI In Genomics Market, By Functionality

  • Genome Sequencing
  • Gene Editing
  • Others

AI In Genomics Market, By Application

  • Drug Discovery & Development
  • Precision Medicine
  • Diagnostics
  • Others

AI In Genomics Market, By End Use

  • Pharmaceutical and Biotech Companies
  • Healthcare Providers
  • Research Centers
  • Others

AI In Genomics Market, By Region

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global AI In Genomics Market.

Available Customizations:

Global AI In Genomics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global AI In Genomics Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Component (Hardware, Software, Services)
    • 5.2.2. By Technology (Machine Learning {Deep Learning, Supervised Learning, Unsupervised Learning, Others}, Computer Vision)
    • 5.2.3. By Functionality (Genome Sequencing, Gene Editing, Others)
    • 5.2.4. By Application (Drug Discovery & Development, Precision Medicine, Diagnostics, Others)
    • 5.2.5. By End Use (Pharmaceutical and Biotech Companies, Healthcare Providers, Research Centers, Others)
    • 5.2.6. By Region
    • 5.2.7. By Company (2025)
  • 5.3. Market Map

6. North America AI In Genomics Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component
    • 6.2.2. By Technology
    • 6.2.3. By Functionality
    • 6.2.4. By Application
    • 6.2.5. By End Use
    • 6.2.6. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States AI In Genomics Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Component
        • 6.3.1.2.2. By Technology
        • 6.3.1.2.3. By Functionality
        • 6.3.1.2.4. By Application
        • 6.3.1.2.5. By End Use
    • 6.3.2. Canada AI In Genomics Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Component
        • 6.3.2.2.2. By Technology
        • 6.3.2.2.3. By Functionality
        • 6.3.2.2.4. By Application
        • 6.3.2.2.5. By End Use
    • 6.3.3. Mexico AI In Genomics Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Component
        • 6.3.3.2.2. By Technology
        • 6.3.3.2.3. By Functionality
        • 6.3.3.2.4. By Application
        • 6.3.3.2.5. By End Use

7. Europe AI In Genomics Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component
    • 7.2.2. By Technology
    • 7.2.3. By Functionality
    • 7.2.4. By Application
    • 7.2.5. By End Use
    • 7.2.6. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany AI In Genomics Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Component
        • 7.3.1.2.2. By Technology
        • 7.3.1.2.3. By Functionality
        • 7.3.1.2.4. By Application
        • 7.3.1.2.5. By End Use
    • 7.3.2. France AI In Genomics Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Component
        • 7.3.2.2.2. By Technology
        • 7.3.2.2.3. By Functionality
        • 7.3.2.2.4. By Application
        • 7.3.2.2.5. By End Use
    • 7.3.3. United Kingdom AI In Genomics Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Component
        • 7.3.3.2.2. By Technology
        • 7.3.3.2.3. By Functionality
        • 7.3.3.2.4. By Application
        • 7.3.3.2.5. By End Use
    • 7.3.4. Italy AI In Genomics Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Component
        • 7.3.4.2.2. By Technology
        • 7.3.4.2.3. By Functionality
        • 7.3.4.2.4. By Application
        • 7.3.4.2.5. By End Use
    • 7.3.5. Spain AI In Genomics Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Component
        • 7.3.5.2.2. By Technology
        • 7.3.5.2.3. By Functionality
        • 7.3.5.2.4. By Application
        • 7.3.5.2.5. By End Use

8. Asia Pacific AI In Genomics Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component
    • 8.2.2. By Technology
    • 8.2.3. By Functionality
    • 8.2.4. By Application
    • 8.2.5. By End Use
    • 8.2.6. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China AI In Genomics Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component
        • 8.3.1.2.2. By Technology
        • 8.3.1.2.3. By Functionality
        • 8.3.1.2.4. By Application
        • 8.3.1.2.5. By End Use
    • 8.3.2. India AI In Genomics Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component
        • 8.3.2.2.2. By Technology
        • 8.3.2.2.3. By Functionality
        • 8.3.2.2.4. By Application
        • 8.3.2.2.5. By End Use
    • 8.3.3. Japan AI In Genomics Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component
        • 8.3.3.2.2. By Technology
        • 8.3.3.2.3. By Functionality
        • 8.3.3.2.4. By Application
        • 8.3.3.2.5. By End Use
    • 8.3.4. South Korea AI In Genomics Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Component
        • 8.3.4.2.2. By Technology
        • 8.3.4.2.3. By Functionality
        • 8.3.4.2.4. By Application
        • 8.3.4.2.5. By End Use
    • 8.3.5. Australia AI In Genomics Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Component
        • 8.3.5.2.2. By Technology
        • 8.3.5.2.3. By Functionality
        • 8.3.5.2.4. By Application
        • 8.3.5.2.5. By End Use

9. Middle East & Africa AI In Genomics Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component
    • 9.2.2. By Technology
    • 9.2.3. By Functionality
    • 9.2.4. By Application
    • 9.2.5. By End Use
    • 9.2.6. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia AI In Genomics Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component
        • 9.3.1.2.2. By Technology
        • 9.3.1.2.3. By Functionality
        • 9.3.1.2.4. By Application
        • 9.3.1.2.5. By End Use
    • 9.3.2. UAE AI In Genomics Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component
        • 9.3.2.2.2. By Technology
        • 9.3.2.2.3. By Functionality
        • 9.3.2.2.4. By Application
        • 9.3.2.2.5. By End Use
    • 9.3.3. South Africa AI In Genomics Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component
        • 9.3.3.2.2. By Technology
        • 9.3.3.2.3. By Functionality
        • 9.3.3.2.4. By Application
        • 9.3.3.2.5. By End Use

10. South America AI In Genomics Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component
    • 10.2.2. By Technology
    • 10.2.3. By Functionality
    • 10.2.4. By Application
    • 10.2.5. By End Use
    • 10.2.6. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil AI In Genomics Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component
        • 10.3.1.2.2. By Technology
        • 10.3.1.2.3. By Functionality
        • 10.3.1.2.4. By Application
        • 10.3.1.2.5. By End Use
    • 10.3.2. Colombia AI In Genomics Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component
        • 10.3.2.2.2. By Technology
        • 10.3.2.2.3. By Functionality
        • 10.3.2.2.4. By Application
        • 10.3.2.2.5. By End Use
    • 10.3.3. Argentina AI In Genomics Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component
        • 10.3.3.2.2. By Technology
        • 10.3.3.2.3. By Functionality
        • 10.3.3.2.4. By Application
        • 10.3.3.2.5. By End Use

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global AI In Genomics Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. IBM Corp.
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. Deep Genomics Inc.
  • 15.3. Nvidia Corporation
  • 15.4. Data4Cure, Inc.
  • 15.5. Illumina, Inc.
  • 15.6. Thermo Fisher Scientific Inc.
  • 15.7. Sophia Genetics S.A.
  • 15.8. Freenome Holdings, Inc.
  • 15.9. BenevolentAI Ltd.
  • 15.10. Genentech, Inc.

16. Strategic Recommendations

17. About Us & Disclaimer