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市場調查報告書
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2056387

生命科學領域人工智慧市場報告：按交付方式、部署方式、應用領域和地區分類（2026-2034 年）

Artificial Intelligence in Life Sciences Market Report by Offering, Deployment, Application, and Region 2026-2034
出版日期: | 出版商: IMARC | 英文 150 Pages | 商品交期: 2-3個工作天內

價格

2025年，全球生命科學領域的人工智慧（AI）市場規模達到35億美元。展望未來，IMARC Group預測，該市場在2026年至2034年間將以19.84%的複合年成長率成長，到2034年達到188億美元。市場成長的主要促進因素包括疾病複雜性的增加、人工智慧在醫學影像分析領域應用的不斷擴展、人工智慧在基因組研究和分析中的應用，以及人工智慧與新興技術的融合。

生命科學領域人工智慧（AI）市場分析：

  • 關鍵市場促進因素：生命科學領域的人工智慧發展主要受基因組序列和電子健康記錄 (EHR) 等生物醫學數據量不斷成長的驅動。這促使人們需要採用功能強大的人工智慧工具來進行有效管理和分析。因此，人工智慧在加速藥物發現和開發過程中發揮著至關重要的作用，從而顯著降低時間和成本。此外，監管機構對人工智慧在臨床應用的支持，以及機器學習和計算演算法的進步，也進一步推動了生命科學領域人工智慧市場的成長。
  • 關鍵市場趨勢：生命科學領域人工智慧的關鍵市場趨勢包括與雲端運算和物聯網 (IoT) 設備的整合，從而進一步增強資料可存取性和即時分析能力。此外，人工智慧驅動的預測模型的發展也呈現出顯著趨勢，這些模型能夠預測疾病進展和患者預後，從而改善臨床決策。因此，人工智慧技術公司與製藥公司之間的合作日益增多，主要集中在將人工智慧應用於藥物研發和病患監測。另一個值得關注的趨勢是，人們越來越重視符合倫理的人工智慧和透明演算法，以確保患者資料的安全和隱私合規性。此外，人工智慧在機器人流程自動化 (RPA) 中的應用正在簡化醫療保健行業的行政工作，進一步推動人工智慧在生命科學市場的成長。
  • 區域趨勢：從區域來看，北美在人工智慧和生命科學市場處於領先地位。這主要得益於其先進的技術基礎設施、對人工智慧和醫療保健領域的大量投資以及強力的監管支援。歐洲緊隨其後，在醫療保健系統日益普及人工智慧以及政府支持人工智慧研究和資料保護的政策推動下，實現了顯著成長。亞太地區也呈現顯著成長，這主要得益於不斷成長的醫療保健需求、技術進步以及中國、日本和印度等國政府為促進人工智慧發展所採取的舉措。
  • 競爭格局：生命科學產業人工智慧領域的主要市場參與者包括 AiCure LLC、Apixio Inc.（Centene Corporation）、Atomwise Inc.、Enlitic Inc.、國際商業機器公司、Insilico Medicine Inc.、Nuance Communications Inc.、NuMedii Inc.、Sensely Inc. 和 Sophia Genetics SA。
  • 挑戰與機會：人工智慧和生命科學市場面臨許多挑戰，包括高昂的實施成本、人工智慧專業人才短缺以及日益成長的資料隱私和安全擔憂。生物數據的複雜性需要更複雜的人工智慧模型，但這些模型的發展充滿挑戰。另一方面，就機會而言，人工智慧在簡化藥物研發流程、降低成本以及提供針對每位患者的個人化醫療方面展現出巨大潛力。此外，新興市場也蘊藏著巨大的成長潛力，人工智慧可以幫助縮小醫療服務的差距。

生命科學市場人工智慧的發展趨勢與促進因素：

加速藥物發現與開發

傳統的藥物研發流程耗時漫長、成本高昂且效率低下，一種新藥從研發到上市往往需要十多年時間。人工智慧正在改變這一現狀，加速藥物研發的各個階段。例如，2023年，Cognizant在舊金山成立了高級人工智慧實驗室，主要專注於核心人工智慧研究、創新以及尖端人工智慧系統的開發。該實驗室擁有一支專業的AI研究人員和開發人員團隊，目前已獲得75項專利（已註冊和正在申請中），並正在拓展與研究機構、客戶和新創公司的合作關係。

機器學習演算法分析大量資料集，包括生物和化學資訊、臨床試驗資料以及現有藥物資料庫，以前所未有的速度和準確度識別有前景的候選藥物。這使得研究人員能夠識別有潛力的化合物、預測其療效並最佳化其性質，從而顯著降低藥物研發所需的時間和成本，並推動生命科學領域人工智慧市場的成長。

個人化醫療和醫療保健

傳統醫療通常採用統一的方法，根據大樣本人群的平均情況來開立藥物和治療方法。人工智慧則利用巨量資料和機器學習的力量，透過分析個體的基因組成、臨床病史、生活方式因素和即時健康數據，制定高度個人化的治療方案。 2023年，OM1推出了PhenOM，這是一個利用豐富的醫療保健資料集和人工智慧技術的個人化醫療人工智慧平台。 PhenOM透過整合縱向健康史數據並識別與疾病相關的獨特數位表現型，為大規模個人化醫療提供了深刻見解。

OM1專注於慢性疾病領域，是創新真實世界數據（RWE）研究的先驅，致力於透過尖端人工智慧解決方案，為患者提供個人化治療方案，從而推動醫學進步。這種個人化治療不僅療效更佳，副作用更小。此外，人工智慧驅動的預測模型有助於識別特定疾病的高風險患者，從而實現早期療育和預防措施。在腫瘤學領域，人工智慧還能幫助識別導致患者癌症的特定基因突變，使腫瘤科醫師能夠推薦標靶治療。

疾病診斷和生物標記發現

人工智慧演算法能夠以極高的準確度和效率分析各種醫療資料來源，包括X光片、核磁共振成像（MRI）和電腦電腦斷層掃描）等醫學影像，以及病患的電子健康記錄和基因組圖譜。在放射學領域，人工智慧驅動的影像分析能夠幫助放射科醫生檢測細微異常並識別潛在的健康問題，從而促進早期診斷和治療。 2024年，Rad AI與Google合作，利用人工智慧技術提昇放射學報告的質量，旨在減少放射科醫生的工作時間，緩解職業倦怠，並提高患者照護品質。此次合作將簡化工作流程，實現重複性任務的自動化，並提昇放射學報告的效率和準確性。

此外，人工智慧在疾病生物標記的發現中發揮著至關重要的作用，這些生物標記對於早期識別疾病和監測疾病進展至關重要。機器學習模型能夠檢測分子數據中的細微模式，從而幫助識別與多種疾病相關的特定生物標記物，包括癌症、阿茲海默症和心血管疾病。這些生物標記可作為早期預警訊號，指南臨床醫師及時做出明智的患者照護決策。

目錄

第1章：序言

第2章：調查方法

  • 調查目的
  • 相關利益者
  • 數據來源
    • 主要訊息
    • 次要訊息
  • 市場估值
    • 自下而上的方法
    • 自上而下的方法
  • 預測方法

第3章執行摘要

第4章：引言

第5章：生命科學領域的全球人工智慧市場

  • 市場概覽
  • 市場表現
  • 新冠疫情的影響
  • 市場預測

第6章 市場區隔：依產品/服務分類

  • 軟體
  • 硬體
  • 服務

第7章 市場區隔：依市場類型分類

  • 現場
  • 基於雲端的

第8章 市場區隔：依應用領域分類

  • 藥物發現
  • 醫學診斷
  • 生物技術
  • 臨床試驗
  • 精準醫療與個人化醫療
  • 病患監測

第9章 市場區隔：依地區分類

  • 北美洲
    • 美國
    • 加拿大
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他
  • 中東和非洲

第10章 SWOT 分析

第11章：價值鏈分析

第12章：波特五力分析

第13章：價格分析

第14章 競爭格局

  • 市場結構
  • 大公司
  • 主要公司簡介
    • AiCure LLC
    • Apixio Inc.（Centene Corporation）
    • Atomwise Inc
    • Enlitic Inc.
    • International Business Machines Corporation
    • Insilico Medicine Inc.
    • Nuance Communications Inc.
    • NuMedii Inc.
    • Sensely Inc.
    • Sophia Genetics SA
Product Code: SR112026A6080

The global artificial intelligence in life sciences market size reached USD 3.5 Billion in 2025. Looking forward, IMARC Group expects the market to reach USD 18.8 Billion by 2034, exhibiting a growth rate (CAGR) of 19.84% during 2026-2034. The rising prevalence of complex diseases, the increasing adoption of AI in medical imaging analysis, the integration of AI into genomics research and analysis, and the convergence of AI with emerging technologies are some of the major factors propelling the market.

Artificial Intelligence in Life Sciences Market Analysis:

  • Major Market Drivers: Artificial intelligence in life sciences is mainly driven by the increase in the volume of biomedical data from genomic sequences and electronic health records which necessitates the incorporation of powerful AI tools for effective management and analysis. In line with this, artificial intelligence is instrumental in accelerating drug discovery and development processes thereby significantly reducing time and costs. Moreover, regulatory support for AI integration in clinical settings and advancements in machine learning and computational algorithms further propel artificial intelligence in life sciences market growth.
  • Key Market Trends: Key market trends in artificial intelligence in the life sciences sector include the integration of artificial intelligence along with cloud computing and Internet of Things (IoT) devices further enhancing data accessibility and real-time analysis. There is also a significant trend toward the development of AI-driven predictive models that forecast disease progression and patient outcomes improving clinical decision-making. In line with this, collaborative efforts between AI tech firms and pharmaceutical companies are on the rise mainly aimed at leveraging AI for drug development and patient monitoring. The growing focus on ethical AI and transparent algorithms to ensure patient data security and privacy compliance is another notable trend. Furthermore, the use of AI in robotic process automation (RPA) is a streamlining administrative task in healthcare further driving artificial intelligence in life sciences market growth.
  • Geographical Trends: Geographically, North America leads the artificial intelligence and life sciences market mainly driven by its advanced technological infrastructure, substantial investment in artificial intelligence and healthcare, and strong support from regulatory bodies. Europe follows closely, with significant growth because of the increase in the adoption of AI in healthcare systems and support from government policies regarding AI research and data protection. Asia Pacific is experiencing significant growth mainly fueled by increasing healthcare demands, technological advancements, and government initiatives to promote AI in countries like China, Japan, and India.
  • Competitive Landscape: Some of the major market players in the artificial intelligence in life sciences industry include AiCure LLC, Apixio Inc. (Centene Corporation), Atomwise Inc, Enlitic Inc., International Business Machines Corporation, Insilico Medicine Inc., Nuance Communications Inc., NuMedii Inc., Sensely Inc. Sophia Genetics SA., among many others.
  • Challenges and Opportunities: The artificial intelligence and life sciences market faces various challenges, which include high implementation costs, a need for more skilled artificial intelligence professionals, and growing concerns over data privacy and security. The complexity of biological data requires more sophisticated AI models, which can be difficult to develop. On the opportunity side, artificial intelligence shows potential in improving drug development efficiency, reducing costs, and in personalized patient care. Furthermore, there is also significant potential for growth in emerging markets where AI can address the gaps in healthcare services.

Artificial Intelligence in Life Sciences Market Trends/Drivers:

Drug Discovery and Development Acceleration

The traditional drug development process is a lengthy, costly, and often inefficient endeavour, taking over a decade to bring a new drug into the market. AI transforms this landscape by expediting various stages of drug development. For instance, in 2023, Cognizant launched an Advanced Artificial Intelligence (AI) Lab in San Francisco to mainly focus on core AI research, innovation, and development of cutting-edge AI systems. The lab, staffed by a team of dedicated AI researchers and developers, has already produced 75 issued and pending patents and will collaborate with research institutions, customers, and startups.

Machine learning algorithms analyse vast datasets, including biological and chemical information, clinical trial data, and existing drug databases, to identify potential drug candidates with unprecedented speed and accuracy. This enables researchers to pinpoint promising compounds, predict their efficacy, and optimize their properties, significantly reducing the time and cost required for drug discovery, thereby propelling the artificial intelligence in life sciences market growth.

Personalized Medicine and Healthcare

Traditional medical treatments often follow a one-size-fits-all approach, with medications and therapies prescribed based on broad population averages. AI harnesses the power of big data and machine learning to analyze an individual's genetic makeup, clinical history, lifestyle factors, and real-time health data to develop highly tailored treatment plans. In 2023, OM1 introduced PhenOM, an AI-powered platform for personalized medicine, leveraging enriched healthcare datasets and AI technology. Calibrated using longitudinal health history data, PhenOM identifies unique digital phenotypes associated with conditions, enabling personalized healthcare insights at scale.

With a focus on chronic conditions, OM1 pioneers innovative RWE research, delivering personalized impact on patient outcomes and advancing healthcare through cutting-edge AI solutions.This level of personalization ensures that patients receive treatments that are not only more effective but also less likely to cause adverse side effects. Also, AI-driven predictive models can help identify patients at higher risk of certain diseases, allowing for early intervention and preventive measures. Additionally, in oncology, AI assists in pinpointing the specific genetic mutations driving a patient's cancer, enabling oncologists to recommend targeted therapies that are more likely to be successful.

Disease Diagnosis and Biomarker Discovery

AI algorithms can analyze diverse medical data sources, including medical images, such as X-rays, MRIs, and CT scans, patient electronic health records, and genomic profiles, with exceptional accuracy and efficiency. In radiology, AI-powered image analysis can assist radiologists in detecting subtle abnormalities and flagging potential health issues, aiding in early diagnosis and treatment. In 2024, Rad AI has partnered with Google to enhance radiology reporting by leveraging AI technology, aiming to save radiologists time, reduce burnout, and improve patient care quality. This collaboration will streamline workflows, automate repetitive tasks, and advance the efficiency and accuracy of radiology reporting.

Moreover, AI is instrumental in the discovery of disease biomarkers, which are crucial in identifying diseases at their earliest stages and monitoring their progression. Machine learning models can detect subtle patterns in molecular data, helping to identify specific biomarkers associated with various diseases, including cancer, Alzheimer's, and cardiovascular conditions. These biomarkers serve as early warning signs and can guide clinicians in making timely and informed decisions about patient care.

Artificial Intelligence in Life Sciences Industry Segmentation:

The research provides an analysis of the key trends in each segment of the global artificial intelligence in life sciences market report, along with forecasts at the global, regional, and country levels for 2026-2034. Our report has categorized the market based on offering, deployment, and application.

Breakup by Offering:

  • Software
  • Hardware
  • Service.

Software dominates the market

Software in the context of AI encompasses a wide array of tools, platforms, and applications specifically designed to process, analyze, and interpret the immense volume of data generated in life sciences research. These software solutions utilize machine learning algorithms, natural language processing, deep learning, and other AI techniques to sift through complex biological datasets, making sense of genomics, proteomics, and clinical data. The versatility of AI software allows researchers to explore various aspects of drug discovery, disease diagnosis, and patient care with unprecedented precision and efficiency.

Additionally, the scalability and adaptability of AI software make it a preferred choice for organizations operating in the life sciences domain. Researchers can customize and fine-tune AI algorithms to meet their specific research needs, whether it involves drug target identification, biomarker discovery, or patient stratification for clinical trials. This flexibility empowers scientists to adapt to evolving research objectives and swiftly respond to emerging challenges in healthcare and life sciences. Furthermore, AI software offerings are at the forefront of addressing some of the most pressing issues in the industry.

Breakup by Deployment:

  • On-premises
  • Cloud-base.

Cloud-based dominate the market

Cloud-based deployment offers unparalleled scalability and flexibility, which are crucial for the resource-intensive nature of AI applications in life sciences. Researchers and organizations can tap into cloud resources as needed, scaling up or down depending on the complexity and volume of data being processed. This dynamic scalability ensures that computational resources are optimally allocated, avoiding underutilization or resource bottlenecks, which can occur with on-premises solutions. Additionally, cloud-based deployment eliminates the need for significant upfront hardware and infrastructure investments.

This cost-effectiveness is particularly attractive for research institutions, pharmaceutical companies, and healthcare providers looking to leverage AI without the burden of substantial capital expenditures. Cloud services provide pay-as-you-go pricing models, allowing organizations to pay only for the computing resources they consume, thus optimizing cost management. Moreover, cloud-based deployments offer the advantage of accessibility and collaboration. Researchers and scientists can access AI tools and applications from anywhere with an internet connection, facilitating collaboration across geographic boundaries and enabling real-time data sharing and analysis.

Breakup by Application:

  • Drug Discovery
  • Medical Diagnosis
  • Biotechnology
  • Clinical Trials
  • Precision and Personalized Medicine
  • Patient Monitorin.

Drug discovery dominates the market

AI-driven drug discovery is not limited to target identification alone. AI models can predict the pharmacokinetics and toxicity profiles of potential drugs, allowing researchers to assess their safety and efficacy earlier in the development pipeline. This risk mitigation not only saves time but also reduces the likelihood of costly late-stage failures, a common challenge in the pharmaceutical industry. Additionally, AI plays a pivotal role in drug repurposing, where existing drugs are explored for new therapeutic applications. By analyzing biological data, AI algorithms can identify overlooked connections between drugs and diseases, potentially unveiling novel treatment options.

This approach not only accelerates the availability of treatments for various medical conditions but also leverages existing knowledge and resources more efficiently. Furthermore, the personalized medicine revolution is closely linked to AI-driven drug discovery. As AI models analyze patients' genetic profiles, clinical histories, and real-time health data, they can identify specific genetic markers and mutations that influence drug response.

Breakup by Region:

  • North America
  • United States
  • Canada
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
  • Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
  • Latin America
  • Brazil
  • Mexico
  • Others
  • Middle East and Afric.

North America exhibits a clear dominance, accounting for the largest artificial intelligence in life sciences market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.

North America boasts significant investments in AI research and development. Government initiatives, private sector funding, and venture capital investments have poured into AI projects and startups, fueling innovation and technological advancements. This financial backing has accelerated the growth of AI-driven solutions, from drug discovery and genomics to healthcare analytics and personalized medicine. Moreover, North America's robust regulatory framework and intellectual property protection create a conducive environment for AI development and commercialization. Several regulatory agencies have been proactive in engaging with AI developers to establish clear guidelines and approval processes for AI-based medical devices and treatments.

This regulatory clarity gives businesses confidence to invest in AI projects. Furthermore, North America's healthcare infrastructure is among the most advanced globally, making it a prime testing ground for AI applications. The region's large patient population, extensive electronic health record systems, and well-established pharmaceutical and biotech industries provide ample opportunities for AI-driven healthcare solutions to demonstrate their efficacy and impact.

Competitive Landscape:

Numerous companies in this market are focused on using AI to accelerate drug discovery processes. They develop AI algorithms and platforms that analyze biological data, identify potential drug candidates, predict drug interactions, and optimize drug design, all with the goal of bringing new therapies to market faster and more efficiently. Also, AI companies in the life sciences sector work on solutions for genomic analysis. They develop tools that can decipher and interpret genetic information, identify disease markers, predict disease risk, and enable personalized medicine by tailoring treatments based on an individual's genetic profile.

Moreover, companies are developing AI-driven solutions that assist radiologists and pathologists in interpreting medical images such as X-rays, MRIs, and CT scans. These tools can help detect diseases and anomalies earlier and with greater accuracy. Companies are also actively engaged in predictive analytics, utilizing AI to identify disease biomarkers, predict patient outcomes, and stratify patients for clinical trials. These AI-driven insights can inform treatment decisions and improve patient care.

The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

  • AiCure LLC
  • Apixio Inc. (Centene Corporation)
  • Atomwise Inc
  • Enlitic Inc.
  • International Business Machines Corporation
  • Insilico Medicine Inc.
  • Nuance Communications Inc.
  • NuMedii Inc.
  • Sensely Inc.
  • Sophia Genetics S.

Key Questions Answered in This Report

  • How big is the artificial intelligence in life sciences market?
  • What is the expected growth rate of the global artificial intelligence in life sciences market during 2026-2034?
  • What are the key factors driving the global artificial intelligence in life sciences market?
  • What has been the impact of COVID-19 on the global artificial intelligence in life sciences market?
  • What is the breakup of the global artificial intelligence in life sciences market based on the offering?
  • What is the breakup of the global artificial intelligence in life sciences market based on the deployment?
  • What is the breakup of the global artificial intelligence in life sciences market based on the application?
  • What are the key regions in the global artificial intelligence in life sciences market?
  • Who are the key players/companies in the global artificial intelligence in life sciences market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Artificial Intelligence In Life Sciences Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Offering

  • 6.1 Software
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Hardware
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Services
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast

7 Market Breakup by Deployment

  • 7.1 On-premises
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Cloud-based
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast

8 Market Breakup by Application

  • 8.1 Drug Discovery
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Medical Diagnosis
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast
  • 8.3 Biotechnology
    • 8.3.1 Market Trends
    • 8.3.2 Market Forecast
  • 8.4 Clinical Trials
    • 8.4.1 Market Trends
    • 8.4.2 Market Forecast
  • 8.5 Precision and Personalized Medicine
    • 8.5.1 Market Trends
    • 8.5.2 Market Forecast
  • 8.6 Patient Monitoring
    • 8.6.1 Market Trends
    • 8.6.2 Market Forecast

9 Market Breakup by Region

  • 9.1 North America
    • 9.1.1 United States
      • 9.1.1.1 Market Trends
      • 9.1.1.2 Market Forecast
    • 9.1.2 Canada
      • 9.1.2.1 Market Trends
      • 9.1.2.2 Market Forecast
  • 9.2 Asia-Pacific
    • 9.2.1 China
      • 9.2.1.1 Market Trends
      • 9.2.1.2 Market Forecast
    • 9.2.2 Japan
      • 9.2.2.1 Market Trends
      • 9.2.2.2 Market Forecast
    • 9.2.3 India
      • 9.2.3.1 Market Trends
      • 9.2.3.2 Market Forecast
    • 9.2.4 South Korea
      • 9.2.4.1 Market Trends
      • 9.2.4.2 Market Forecast
    • 9.2.5 Australia
      • 9.2.5.1 Market Trends
      • 9.2.5.2 Market Forecast
    • 9.2.6 Indonesia
      • 9.2.6.1 Market Trends
      • 9.2.6.2 Market Forecast
    • 9.2.7 Others
      • 9.2.7.1 Market Trends
      • 9.2.7.2 Market Forecast
  • 9.3 Europe
    • 9.3.1 Germany
      • 9.3.1.1 Market Trends
      • 9.3.1.2 Market Forecast
    • 9.3.2 France
      • 9.3.2.1 Market Trends
      • 9.3.2.2 Market Forecast
    • 9.3.3 United Kingdom
      • 9.3.3.1 Market Trends
      • 9.3.3.2 Market Forecast
    • 9.3.4 Italy
      • 9.3.4.1 Market Trends
      • 9.3.4.2 Market Forecast
    • 9.3.5 Spain
      • 9.3.5.1 Market Trends
      • 9.3.5.2 Market Forecast
    • 9.3.6 Russia
      • 9.3.6.1 Market Trends
      • 9.3.6.2 Market Forecast
    • 9.3.7 Others
      • 9.3.7.1 Market Trends
      • 9.3.7.2 Market Forecast
  • 9.4 Latin America
    • 9.4.1 Brazil
      • 9.4.1.1 Market Trends
      • 9.4.1.2 Market Forecast
    • 9.4.2 Mexico
      • 9.4.2.1 Market Trends
      • 9.4.2.2 Market Forecast
    • 9.4.3 Others
      • 9.4.3.1 Market Trends
      • 9.4.3.2 Market Forecast
  • 9.5 Middle East and Africa
    • 9.5.1 Market Trends
    • 9.5.2 Market Breakup by Country
    • 9.5.3 Market Forecast

10 SWOT Analysis

  • 10.1 Overview
  • 10.2 Strengths
  • 10.3 Weaknesses
  • 10.4 Opportunities
  • 10.5 Threats

11 Value Chain Analysis

12 Porters Five Forces Analysis

  • 12.1 Overview
  • 12.2 Bargaining Power of Buyers
  • 12.3 Bargaining Power of Suppliers
  • 12.4 Degree of Competition
  • 12.5 Threat of New Entrants
  • 12.6 Threat of Substitutes

13 Price Analysis

14 Competitive Landscape

  • 14.1 Market Structure
  • 14.2 Key Players
  • 14.3 Profiles of Key Players
    • 14.3.1 AiCure LLC
      • 14.3.1.1 Company Overview
      • 14.3.1.2 Product Portfolio
    • 14.3.2 Apixio Inc. (Centene Corporation)
      • 14.3.2.1 Company Overview
      • 14.3.2.2 Product Portfolio
    • 14.3.3 Atomwise Inc
      • 14.3.3.1 Company Overview
      • 14.3.3.2 Product Portfolio
    • 14.3.4 Enlitic Inc.
      • 14.3.4.1 Company Overview
      • 14.3.4.2 Product Portfolio
    • 14.3.5 International Business Machines Corporation
      • 14.3.5.1 Company Overview
      • 14.3.5.2 Product Portfolio
      • 14.3.5.3 Financials
      • 14.3.5.4 SWOT Analysis
    • 14.3.6 Insilico Medicine Inc.
      • 14.3.6.1 Company Overview
      • 14.3.6.2 Product Portfolio
    • 14.3.7 Nuance Communications Inc.
      • 14.3.7.1 Company Overview
      • 14.3.7.2 Product Portfolio
      • 14.3.7.3 SWOT Analysis
    • 14.3.8 NuMedii Inc.
      • 14.3.8.1 Company Overview
      • 14.3.8.2 Product Portfolio
    • 14.3.9 Sensely Inc.
      • 14.3.9.1 Company Overview
      • 14.3.9.2 Product Portfolio
    • 14.3.10 Sophia Genetics SA
      • 14.3.10.1 Company Overview
      • 14.3.10.2 Product Portfolio
      • 14.3.10.3 Financials

List of Figures

  • Figure 1: Global: Artificial Intelligence In Life Sciences Market: Major Drivers and Challenges
  • Figure 2: Global: Artificial Intelligence In Life Sciences Market: Sales Value (in Billion USD), 2020-2025
  • Figure 3: Global: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Billion USD), 2026-2034
  • Figure 4: Global: Artificial Intelligence In Life Sciences Market: Breakup by Offering (in %), 2025
  • Figure 5: Global: Artificial Intelligence In Life Sciences Market: Breakup by Deployment (in %), 2025
  • Figure 6: Global: Artificial Intelligence In Life Sciences Market: Breakup by Application (in %), 2025
  • Figure 7: Global: Artificial Intelligence In Life Sciences Market: Breakup by Region (in %), 2025
  • Figure 8: Global: Artificial Intelligence In Life Sciences (Software) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 9: Global: Artificial Intelligence In Life Sciences (Software) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 10: Global: Artificial Intelligence In Life Sciences (Hardware) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 11: Global: Artificial Intelligence In Life Sciences (Hardware) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 12: Global: Artificial Intelligence In Life Sciences (Services) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 13: Global: Artificial Intelligence In Life Sciences (Services) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 14: Global: Artificial Intelligence In Life Sciences (On-premises) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 15: Global: Artificial Intelligence In Life Sciences (On-premises) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 16: Global: Artificial Intelligence In Life Sciences (Cloud-based) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 17: Global: Artificial Intelligence In Life Sciences (Cloud-based) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 18: Global: Artificial Intelligence In Life Sciences (Drug Discovery) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 19: Global: Artificial Intelligence In Life Sciences (Drug Discovery) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 20: Global: Artificial Intelligence In Life Sciences (Medical Diagnosis) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 21: Global: Artificial Intelligence In Life Sciences (Medical Diagnosis) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 22: Global: Artificial Intelligence In Life Sciences (Biotechnology) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 23: Global: Artificial Intelligence In Life Sciences (Biotechnology) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 24: Global: Artificial Intelligence In Life Sciences (Clinical Trials) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 25: Global: Artificial Intelligence In Life Sciences (Clinical Trials) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 26: Global: Artificial Intelligence In Life Sciences (Precision and Personalized Medicine) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 27: Global: Artificial Intelligence In Life Sciences (Precision and Personalized Medicine) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 28: Global: Artificial Intelligence In Life Sciences (Patient Monitoring) Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 29: Global: Artificial Intelligence In Life Sciences (Patient Monitoring) Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 30: North America: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 31: North America: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 32: United States: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 33: United States: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 34: Canada: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 35: Canada: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 36: Asia-Pacific: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 37: Asia-Pacific: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 38: China: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 39: China: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 40: Japan: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 41: Japan: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 42: India: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 43: India: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 44: South Korea: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 45: South Korea: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 46: Australia: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 47: Australia: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 48: Indonesia: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 49: Indonesia: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 50: Others: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 51: Others: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 52: Europe: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 53: Europe: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 54: Germany: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 55: Germany: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 56: France: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 57: France: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 58: United Kingdom: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 59: United Kingdom: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 60: Italy: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 61: Italy: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 62: Spain: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 63: Spain: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 64: Russia: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 65: Russia: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 66: Others: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 67: Others: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 68: Latin America: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 69: Latin America: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 70: Brazil: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 71: Brazil: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 72: Mexico: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 73: Mexico: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 74: Others: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 75: Others: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 76: Middle East and Africa: Artificial Intelligence In Life Sciences Market: Sales Value (in Million USD), 2020 & 2025
  • Figure 77: Middle East and Africa: Artificial Intelligence In Life Sciences Market: Breakup by Country (in %), 2025
  • Figure 78: Middle East and Africa: Artificial Intelligence In Life Sciences Market Forecast: Sales Value (in Million USD), 2026-2034
  • Figure 79: Global: Artificial Intelligence In Life Sciences Industry: SWOT Analysis
  • Figure 80: Global: Artificial Intelligence In Life Sciences Industry: Value Chain Analysis
  • Figure 81: Global: Artificial Intelligence In Life Sciences Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: Artificial Intelligence In Life Sciences Market: Key Industry Highlights, 2025 and 2034
  • Table 2: Global: Artificial Intelligence In Life Sciences Market Forecast: Breakup by Offering (in Million USD), 2026-2034
  • Table 3: Global: Artificial Intelligence In Life Sciences Market Forecast: Breakup by Deployment (in Million USD), 2026-2034
  • Table 4: Global: Artificial Intelligence In Life Sciences Market Forecast: Breakup by Application (in Million USD), 2026-2034
  • Table 5: Global: Artificial Intelligence In Life Sciences Market Forecast: Breakup by Region (in Million USD), 2026-2034
  • Table 6: Global: Artificial Intelligence In Life Sciences Market: Competitive Structure