Next-Generation AI in Life Science Market Size, Share, and Trends 2025 to 2034

Next-Generation AI in Life Science Market (By Application Area: Drug Discovery & Development, Clinical Diagnostics, Precision Medicine, Medical Imaging, Healthcare Operations & Workflow Automation, Remote Monitoring & Digital Therapeutics, Omics Data Analytics, Other Emerging Use Cases; By Technology Type: Machine Learning Deep Learning, Natural Language Processing, Computer Vision, Generative AI, Knowledge Graphs & Ontology-Based AI, Federated Learning & Privacy-Preserving AI, Explainable AI; By End User: Pharmaceutical & Biotechnology Companies, Contract Research Organizations, Academic & Research Institutes, Hospitals & Healthcare Providers, Diagnostics Laboratories, Medical Device Companies, Government & Regulatory Agencies; HealthTech & AI Startups By Deployment Mode: On-Premise, Cloud-Based, Edge AI;) - Global Industry Analysis, Size, Trends, Leading Companies, Regional Outlook, and Forecast 2025 to 2034

Last Updated : September 2025  |  Report Code : 6857  |  Category : ICT  |  Format : PDF / PPT / Excel

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Next-Generation AI in Life Science Market 

5.1. COVID-19 Landscape: Next-Generation AI in Life Science Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Next-Generation AI in Life Science Market, By Application Area

8.1. Next-Generation AI in Life Science Market, by Application Area

8.1.1. Drug Discovery & Development

8.1.1.1. Market Revenue and Forecast

8.1.2. Clinical Diagnostics

8.1.2.1. Market Revenue and Forecast

8.1.3. Precision Medicine

8.1.3.1. Market Revenue and Forecast

8.1.4. Medical Imaging & Radiology

8.1.4.1. Market Revenue and Forecast

8.1.5. Healthcare Operations & Workflow Automation

8.1.5.1. Market Revenue and Forecast

8.1.6. Remote Monitoring & Digital Therapeutics

8.1.6.1. Market Revenue and Forecast

8.1.7. Omics Data Analytics

8.1.7.1. Market Revenue and Forecast

8.1.8. Other Emerging Use Cases

8.1.8.1. Market Revenue and Forecast

Chapter 9. Global Next-Generation AI in Life Science Market, By Technology Type

9.1. Next-Generation AI in Life Science Market, by Technology Type

9.1.1. Machine Learning (ML)

9.1.1.1. Market Revenue and Forecast

9.1.2. Deep Learning

9.1.2.1. Market Revenue and Forecast

9.1.3. Natural Language Processing (NLP)

9.1.3.1. Market Revenue and Forecast

9.1.4. Computer Vision

9.1.4.1. Market Revenue and Forecast

9.1.5. Generative AI

9.1.5.1. Market Revenue and Forecast

9.1.6. Knowledge Graphs & Ontology-Based AI

9.1.6.1. Market Revenue and Forecast

Chapter 10. Global Next-Generation AI in Life Science Market, By End User 

10.1. Next-Generation AI in Life Science Market, by End User

10.1.1. Pharmaceutical & Biotechnology Companies

10.1.1.1. Market Revenue and Forecast

10.1.2. Contract Research Organizations (CROs)

10.1.2.1. Market Revenue and Forecast

10.1.3. Academic & Research Institutes

10.1.3.1. Market Revenue and Forecast

10.1.4. Hospitals & Healthcare Providers

10.1.4.1. Market Revenue and Forecast

10.1.5. Diagnostics Laboratories

10.1.5.1. Market Revenue and Forecast

10.1.6. Medical Device Companies

10.1.6.1. Market Revenue and Forecast

10.1.7. Government & Regulatory Agencies

10.1.7.1. Market Revenue and Forecast

10.1.8. HealthTech & AI Startups

10.1.8.1. Market Revenue and Forecast

Chapter 11. Global Next-Generation AI in Life Science Market, By Deployment Mode 

11.1. Next-Generation AI in Life Science Market, by Deployment Mode

11.1.1. On-Premise

11.1.1.1. Market Revenue and Forecast

11.1.2. Cloud-Based

11.1.2.1. Market Revenue and Forecast

11.1.3. Edge AI (for remote or embedded applications)

11.1.3.1. Market Revenue and Forecast

Chapter 12. Global Next-Generation AI in Life Science Market, Regional Estimates and Trend Forecast

12.1. North America

12.1.1. Market Revenue and Forecast, by Application Area

12.1.2. Market Revenue and Forecast, by Technology Type

12.1.3. Market Revenue and Forecast, by End User

12.1.4. Market Revenue and Forecast, by Deployment Mode

12.1.5. U.S.

12.1.5.1. Market Revenue and Forecast, by Application Area

12.1.5.2. Market Revenue and Forecast, by Technology Type

12.1.5.3. Market Revenue and Forecast, by End User

12.1.5.4. Market Revenue and Forecast, by Deployment Mode

12.1.6. Rest of North America

12.1.6.1. Market Revenue and Forecast, by Application Area

12.1.6.2. Market Revenue and Forecast, by Technology Type

12.1.6.3. Market Revenue and Forecast, by End User

12.1.6.4. Market Revenue and Forecast, by Deployment Mode

12.2. Europe

12.2.1. Market Revenue and Forecast, by Application Area

12.2.2. Market Revenue and Forecast, by Technology Type

12.2.3. Market Revenue and Forecast, by End User

12.2.4. Market Revenue and Forecast, by Deployment Mode

12.2.5. UK

12.2.5.1. Market Revenue and Forecast, by Application Area

12.2.5.2. Market Revenue and Forecast, by Technology Type

12.2.5.3. Market Revenue and Forecast, by End User

12.2.5.4. Market Revenue and Forecast, by Deployment Mode

12.2.6. Germany

12.2.6.1. Market Revenue and Forecast, by Application Area

12.2.6.2. Market Revenue and Forecast, by Technology Type

12.2.6.3. Market Revenue and Forecast, by End User

12.2.6.4. Market Revenue and Forecast, by Deployment Mode

12.2.7. France

12.2.7.1. Market Revenue and Forecast, by Application Area

12.2.7.2. Market Revenue and Forecast, by Technology Type

12.2.7.3. Market Revenue and Forecast, by End User

12.2.7.4. Market Revenue and Forecast, by Deployment Mode

12.2.8. Rest of Europe

12.2.8.1. Market Revenue and Forecast, by Application Area

12.2.8.2. Market Revenue and Forecast, by Technology Type

12.2.8.3. Market Revenue and Forecast, by End User

12.2.8.4. Market Revenue and Forecast, by Deployment Mode

12.3. APAC

12.3.1. Market Revenue and Forecast, by Application Area

12.3.2. Market Revenue and Forecast, by Technology Type

12.3.3. Market Revenue and Forecast, by End User

12.3.4. Market Revenue and Forecast, by Deployment Mode

12.3.5. India

12.3.5.1. Market Revenue and Forecast, by Application Area

12.3.5.2. Market Revenue and Forecast, by Technology Type

12.3.5.3. Market Revenue and Forecast, by End User

12.3.5.4. Market Revenue and Forecast, by Deployment Mode

12.3.6. China

12.3.6.1. Market Revenue and Forecast, by Application Area

12.3.6.2. Market Revenue and Forecast, by Technology Type

12.3.6.3. Market Revenue and Forecast, by End User

12.3.6.4. Market Revenue and Forecast, by Deployment Mode

12.3.7. Japan

12.3.7.1. Market Revenue and Forecast, by Application Area

12.3.7.2. Market Revenue and Forecast, by Technology Type

12.3.7.3. Market Revenue and Forecast, by End User

12.3.7.4. Market Revenue and Forecast, by Deployment Mode

12.3.8. Rest of APAC

12.3.8.1. Market Revenue and Forecast, by Application Area

12.3.8.2. Market Revenue and Forecast, by Technology Type

12.3.8.3. Market Revenue and Forecast, by End User

12.3.8.4. Market Revenue and Forecast, by Deployment Mode

12.4. MEA

12.4.1. Market Revenue and Forecast, by Application Area

12.4.2. Market Revenue and Forecast, by Technology Type

12.4.3. Market Revenue and Forecast, by End User

12.4.4. Market Revenue and Forecast, by Deployment Mode

12.4.5. GCC

12.4.5.1. Market Revenue and Forecast, by Application Area

12.4.5.2. Market Revenue and Forecast, by Technology Type

12.4.5.3. Market Revenue and Forecast, by End User

12.4.5.4. Market Revenue and Forecast, by Deployment Mode

12.4.6. North Africa

12.4.6.1. Market Revenue and Forecast, by Application Area

12.4.6.2. Market Revenue and Forecast, by Technology Type

12.4.6.3. Market Revenue and Forecast, by End User

12.4.6.4. Market Revenue and Forecast, by Deployment Mode

12.4.7. South Africa

12.4.7.1. Market Revenue and Forecast, by Application Area

12.4.7.2. Market Revenue and Forecast, by Technology Type

12.4.7.3. Market Revenue and Forecast, by End User

12.4.7.4. Market Revenue and Forecast, by Deployment Mode

12.4.8. Rest of MEA

12.4.8.1. Market Revenue and Forecast, by Application Area

12.4.8.2. Market Revenue and Forecast, by Technology Type

12.4.8.3. Market Revenue and Forecast, by End User

12.4.8.4. Market Revenue and Forecast, by Deployment Mode

12.5. Latin America

12.5.1. Market Revenue and Forecast, by Application Area

12.5.2. Market Revenue and Forecast, by Technology Type

12.5.3. Market Revenue and Forecast, by End User

12.5.4. Market Revenue and Forecast, by Deployment Mode

12.5.5. Brazil

12.5.5.1. Market Revenue and Forecast, by Application Area

12.5.5.2. Market Revenue and Forecast, by Technology Type

12.5.5.3. Market Revenue and Forecast, by End User

12.5.5.4. Market Revenue and Forecast, by Deployment Mode

12.5.6. Rest of LATAM

12.5.6.1. Market Revenue and Forecast, by Application Area

12.5.6.2. Market Revenue and Forecast, by Technology Type

12.5.6.3. Market Revenue and Forecast, by End User

12.5.6.4. Market Revenue and Forecast, by Deployment Mode

Chapter 13. Company Profiles

13.1. NVIDIA

13.1.1. Company Overview

13.1.2. Product Offerings

13.1.3. Financial Performance

13.1.4. Recent Initiatives

13.2. Google DeepMind

13.2.1. Company Overview

13.2.2. Product Offerings

13.2.3. Financial Performance

13.2.4. Recent Initiatives

13.3. Insilico Medicine

13.3.1. Company Overview

13.3.2. Product Offerings

13.3.3. Financial Performance

13.3.4. Recent Initiatives

13.4. Recursion Pharmaceuticals

13.4.1. Company Overview

13.4.2. Product Offerings

13.4.3. Financial Performance

13.4.4. Recent Initiatives

13.5. Exscientia 

13.5.1. Company Overview

13.5.2. Product Offerings

13.5.3. Financial Performance

13.5.4. Recent Initiatives

13.6. BenevolentAI 

13.6.1. Company Overview

13.6.2. Product Offerings

13.6.3. Financial Performance

13.6.4. Recent Initiatives

13.7. Owkin 

13.7.1. Company Overview

13.7.2. Product Offerings

13.7.3. Financial Performance

13.7.4. Recent Initiatives

13.8. Atomwise

13.8.1. Company Overview

13.8.2. Product Offerings

13.8.3. Financial Performance

13.8.4. Recent Initiatives

13.9. PathAI

13.9.1. Company Overview

13.9.2. Product Offerings

13.9.3. Financial Performance

13.9.4. Recent Initiatives

13.10. Valo Health

13.10.1. Company Overview

13.10.2. Product Offerings

13.10.3. Financial Performance

13.10.4. Recent Initiatives

Chapter 14. Research Methodology

14.1. Primary Research

14.2. Secondary Research

14.3. Assumptions

Chapter 15. Appendix

15.1. About Us

15.2. Glossary of Terms

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Frequently Asked Questions

The major players in the next-generation AI in life science market include NVIDIA, Google DeepMind, Insilico Medicine, Recursion Pharmaceuticals, Exscientia, BenevolentAI, Owkin, Atomwise, PathAI, Valo Health, Tempus AI, Aria Pharmaceuticals, BioAge Labs, IBM Watson Health, Microsoft Azure AI for Health, Genesis Therapeutics, XtalPi, and Enveda Biosciences.

The driving factors of the next-generation AI in life science market are the increasing demand for personalized medicine, rapid advancements in computing power and multiomics data, increasing focus on clinical trial optimization.

North America region will lead the global next-generation AI in life science market during the forecast period 2025 to 2034.

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