Artificial Intelligence (AI) in Life Sciences Market Size & Outlook, 2025-2033

Artificial Intelligence (AI) in Life Sciences Market Size, Share & Trends Analysis Report By Technology (Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Others), By Application (Drug Discovery, Medical Diagnosis, Biotechnology, Clinical Trials, Precision and Personalized Medicine, Patient Monitoring, Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation & Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug), By Drug Type (Small Molecule, Large Molecule), By Offering (Software, Services), By Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, Others), By End user (Pharmaceutical & Biotechnology Companies, Contract Research Organizations (CROs), Research Centres And Academic Institutes, Others) and By Region Forecasts, 2025-2033

Report Code: SRTE2445DR

Last Updated : Sep, 2025

Pages : 110

Author : Pavan Warade

Format : PDF, Excel

Research Methodology – Artificial Intelligence (AI) in Life Sciences Market

At Straits Research, we adopt a rigorous 360° research approach that integrates both primary and secondary research methodologies. This ensures accuracy, reliability, and actionable insights for stakeholders. Our methodology for the Artificial Intelligence (AI) in Life Sciences Market comprises the following key stages:

Market Indicator & Macro-Factor Analysis

Our baseline thesis for the Artificial Intelligence (AI) in Life Sciences Market is developed by integrating key market indicators and macroeconomic variables. These include:

Key Market Indicators

Investment and R&D spending in AI and life sciences sector
Market presence of major industry players and their market share
Market volatility and economic indicators
Technological advancements in AI for life sciences
Adoption rate of AI technology in life sciences by different regions
Market capitalization of companies involved in AI for life sciences
Revenues generated from AI applications in the life sciences sphere
Regulatory changes and impacts

Growth Trends

Increase in adoption of AI-based models for drug discovery and clinical trials
Growth in precision medicine driven by AI technology
Rise in personalized patient care with the help of AI
AI-enabled genomic sequencing for customized healthcare solutions
Increasing partnerships and collaborations between tech firms and pharma companies
Surge in demand for wearable technology and health apps that employ AI
Increasing acceptance of cloud-based applications and services

Secondary Research

Our secondary research forms the foundation of market understanding and scope definition. We collect and analyze information from multiple reliable sources to map the overall ecosystem of the Artificial Intelligence (AI) in Life Sciences Market. Key inputs include:

Company-Level Information

Annual reports, investor presentations, SEC filings
Company press releases and product launch announcements
Public executive interviews and earnings calls
Strategy briefings and M&A updates

Industry and Government Sources

Country-level industry associations and trade bodies
Government dossiers, policy frameworks, and official releases
Whitepapers, working papers, and public R&D initiatives
Relevant Associations for the Artificial Intelligence (AI) in Life Sciences Market

Market Intelligence Sources

Broker reports and financial analyst coverage
Paid databases (Hoovers, Factiva, Refinitiv, Reuters, Statista, etc.)
Import/export trade data and tariff databases
Sector-specific journals, magazines, and news portals

Macro & Consumer Insights

Global macroeconomic indicators and their cascading effect on the industry
Demand–supply outlook and value chain analysis
Consumer behaviour, adoption rates, and commercialization trends

Primary Research

To validate and enrich our secondary findings, we conduct extensive primary research with industry stakeholders across the value chain. This ensures we capture both qualitative insights and quantitative validation. Our primary research includes:

Expert Insights & KOL Engagements

Key Opinion Leader (KOL) Engagements
Structured interviews with executives, product managers, and domain experts
Paid and barter-based interviews across manufacturers, distributors, and end-users

Focused Discussions & Panels

Discussions with stakeholders to validate demand-supply gaps
Group discussions on emerging technologies, regulatory shifts, and adoption barriers

Data Validation & Business POV

Cross-verification of market sizing and forecasts with industry insiders
Capturing business perspectives on growth opportunities and restraints

Data Triangulation & Forecasting

The final step of our research involves data triangulation ensuring accuracy through cross-verification of:

Demand-side analysis (consumption patterns, adoption trends, customer spending)
Supply-side analysis (production, capacity, distribution, and market availability)
Macroeconomic & microeconomic impact factors

Forecasting is carried out using proprietary models that combine: