AI for Science Market Size(US$)

CAGR 2026-2032
28.9%
Market Size,2032
USD 26,230
Million
Market Snapshot
Source: Secondary research, interviews with experts, and QYResearch analysis
The global AI for Science market size was US$ 4538 million in 2025 and is forecast to reach a readjusted size of US$ 26230 million by 2032 with a CAGR of 28.9% during the forecast period 2026-2032.
AI for Science (AI4Science) refers to the application of artificial intelligence (AI) and machine learning (ML) to accelerate scientific discovery, optimize experiments, and solve complex problems in fields like physics, chemistry, biology, and materials science. It combines data-driven modeling with domain knowledge to push the boundaries of research.
In 2025, the North America AI for Science market was US$ million, while the Europe market stood at US$ million. North America accounted for % of the global market in 2025 and Europe for %. Europe’s share is expected to reach % by 2032, corresponding to a CAGR of % over the analysis period.
The global key players of AI for Science include Google DeepMind, OpenAI, IBM, Cerebras Systems, Owkin, Schrödinger, BenevolentAI, SandboxAQ, NVIDIA, XtalPi, among others. In 2025, the top five players accounted for approximately % of global market revenue.
In terms of revenue, the top three players in North America accounted for about % of the market in 2025, while the top three in Europe held nearly %.
The global AI for Science market is strategically segmented by company, region (country), by Type, and by Application. This report empowers stakeholders to capitalize on emerging opportunities, optimize product strategies, and outperform competitors through data-driven insights on revenue and forecasts across regions, by Type, and by Application for 2021-2032.
MARKET SEGMENTATION
Why This Report?
Beyond standard market data, this analysis provides a clear profitability roadmap, empowering you to:
Unlike generic global market reports, this study combines macro-level industry trends with hyper-local operational intelligence, empowering data-driven decisions across the AI for Science value chain, addressing:
- Market entry risks/opportunities by region
- Product mix optimization based on local practices
- Competitor tactics in fragmented vs. consolidated markets
QYRESEARCH'S STRENGTHS
Unlike generic global market reports, this study combines macro-level industry trends with hyper-local operational intelligence, empowering data-driven decisions across the Compound Chocolate value chain, addressing:
We identify regional market threats and growth prospects to guide your overseas layout.
We adjust product portfolios in line with local consumption habits.
We unpack rivals’ operation strategies for scattered and highly concentrated industries.
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TABLE OF CONTENTS
1 Report Overview
1.1 Study Scope
1.2 Market by Type
1.2.1 Global Market Size and Growth by Type: 2021 vs 2025 vs 2032
1.2.2 Closed-loop AI
1.2.3 Human-in-the-loop AI
1.3 Market by Application
1.3.1 Global Market Share by Application: 2021 vs 2025 vs 2032
1.3.2 Biological and Pharmaceutical
1.3.3 Industrial Manufacturing
1.3.4 Material
1.3.5 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global AI for Science Market Perspective (2021-2032)
2.2 Global Market Size by Region: 2021 vs 2025 vs 2032
2.3 Global AI for Science Market Share by Revenue, by Region (2021-2026)
2.4 Global AI for Science Revenue Forecast by Region (2027-2032)
2.5 Major Regions and Emerging Markets Analysis
2.5.1 North America AI for Science Market Size and Prospective (2021-2032)
2.5.2 Europe AI for Science Market Size and Prospective (2021-2032)
2.5.3 China AI for Science Market Size and Prospective (2021-2032)
2.5.4 Japan AI for Science Market Size and Prospective (2021-2032)
2.5.5 India AI for Science Market Size and Prospective (2021-2032)
3 Breakdown Data by Type
3.1 Global AI for Science Historical Market Size by Type (2021-2026)
3.2 Global AI for Science Forecasted Market Size by Type (2027-2032)
3.3 Representative Players for Different Types of AI for Science
4 Breakdown Data by Application
4.1 Global AI for Science Historical Market Size by Application (2021-2026)
4.2 Global AI for Science Forecasted Market Size by Application (2027-2032)
4.3 New Sources of Growth in AI for Science Applications
5 Competitive Landscape by Players
5.1 Global Top Players by Revenue
5.1.1 Global Top AI for Science Players by Revenue (2021-2026)
5.1.2 Global AI for Science Market Share by Revenue, by Players (2021-2026)
5.2 Global Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
5.3 Players Covered: Ranking by AI for Science Revenue
5.4 Global AI for Science Market Concentration Analysis
5.4.1 Global AI for Science Market Concentration Ratio (CR5 and HHI)
5.4.2 Global Top 10 and Top 5 Companies by AI for Science Revenue in 2025
5.5 Global Key Players of AI for Science Head Offices and Areas Served
5.6 Global Key Players of AI for Science, Product and Application
5.7 Global Key Players of AI for Science, Date of Entry into This Industry
5.8 Mergers & Acquisitions, Expansion Plans
6 Region Analysis
6.1 North America Market: Players, Segments, Downstream and Major Customers
6.1.1 North America AI for Science Revenue by Company (2021-2026)
6.1.2 North America Market Size by Type
6.1.2.1 North America AI for Science Market Size by Type (2021-2026)
6.1.2.2 North America AI for Science Market Share by Type (2021-2026)
6.1.3 North America Market Size by Application
6.1.3.1 North America AI for Science Market Size by Application (2021-2026)
6.1.3.2 North America AI for Science Market Share by Application (2021-2026)
6.1.4 North America AI for Science Major Customers
6.1.5 North America Market Trends and Opportunities
6.2 Europe Market: Players, Segments, Downstream and Major Customers
6.2.1 Europe AI for Science Revenue by Company (2021-2026)
6.2.2 Europe Market Size by Type
6.2.2.1 Europe AI for Science Market Size by Type (2021-2026)
6.2.2.2 Europe AI for Science Market Share by Type (2021-2026)
6.2.3 Europe Market Size by Application
6.2.3.1 Europe AI for Science Market Size by Application (2021-2026)
6.2.3.2 Europe AI for Science Market Share by Application (2021-2026)
6.2.4 Europe AI for Science Major Customers
6.2.5 Europe Market Trends and Opportunities
6.3 China Market: Players, Segments, Downstream and Major Customers
6.3.1 China AI for Science Revenue by Company (2021-2026)
6.3.2 China Market Size by Type
6.3.2.1 China AI for Science Market Size by Type (2021-2026)
6.3.2.2 China AI for Science Market Share by Type (2021-2026)
6.3.3 China Market Size by Application
6.3.3.1 China AI for Science Market Size by Application (2021-2026)
6.3.3.2 China AI for Science Market Share by Application (2021-2026)
6.3.4 China AI for Science Major Customers
6.3.5 China Market Trends and Opportunities
6.4 Japan Market: Players, Segments, Downstream and Major Customers
6.4.1 Japan AI for Science Revenue by Company (2021-2026)
6.4.2 Japan Market Size by Type
6.4.2.1 Japan AI for Science Market Size by Type (2021-2026)
6.4.2.2 Japan AI for Science Market Share by Type (2021-2026)
6.4.3 Japan Market Size by Application
6.4.3.1 Japan AI for Science Market Size by Application (2021-2026)
6.4.3.2 Japan AI for Science Market Share by Application (2021-2026)
6.4.4 Japan AI for Science Major Customers
6.4.5 Japan Market Trends and Opportunities
6.5 India Market: Players, Segments, Downstream and Major Customers
6.5.1 India AI for Science Revenue by Company (2021-2026)
6.5.2 India Market Size by Type
6.5.2.1 India AI for Science Market Size by Type (2021-2026)
6.5.2.2 India AI for Science Market Share by Type (2021-2026)
6.5.3 India Market Size by Application
6.5.3.1 India AI for Science Market Size by Application (2021-2026)
6.5.3.2 India AI for Science Market Share by Application (2021-2026)
6.5.4 India AI for Science Major Customers
6.5.5 India Market Trends and Opportunities
7 Key Player Profiles
7.1 Google DeepMind
7.1.1 Google DeepMind Company Details
7.1.2 Google DeepMind Business Overview
7.1.3 Google DeepMind AI for Science Introduction
7.1.4 Google DeepMind Revenue in AI for Science Business (2021-2026)
7.1.5 Google DeepMind Recent Development
7.2 OpenAI
7.2.1 OpenAI Company Details
7.2.2 OpenAI Business Overview
7.2.3 OpenAI AI for Science Introduction
7.2.4 OpenAI Revenue in AI for Science Business (2021-2026)
7.2.5 OpenAI Recent Development
7.3 IBM
7.3.1 IBM Company Details
7.3.2 IBM Business Overview
7.3.3 IBM AI for Science Introduction
7.3.4 IBM Revenue in AI for Science Business (2021-2026)
7.3.5 IBM Recent Development
7.4 Cerebras Systems
7.4.1 Cerebras Systems Company Details
7.4.2 Cerebras Systems Business Overview
7.4.3 Cerebras Systems AI for Science Introduction
7.4.4 Cerebras Systems Revenue in AI for Science Business (2021-2026)
7.4.5 Cerebras Systems Recent Development
7.5 Owkin
7.5.1 Owkin Company Details
7.5.2 Owkin Business Overview
7.5.3 Owkin AI for Science Introduction
7.5.4 Owkin Revenue in AI for Science Business (2021-2026)
7.5.5 Owkin Recent Development
7.6 Schrödinger
7.6.1 Schrödinger Company Details
7.6.2 Schrödinger Business Overview
7.6.3 Schrödinger AI for Science Introduction
7.6.4 Schrödinger Revenue in AI for Science Business (2021-2026)
7.6.5 Schrödinger Recent Development
7.7 BenevolentAI
7.7.1 BenevolentAI Company Details
7.7.2 BenevolentAI Business Overview
7.7.3 BenevolentAI AI for Science Introduction
7.7.4 BenevolentAI Revenue in AI for Science Business (2021-2026)
7.7.5 BenevolentAI Recent Development
7.8 SandboxAQ
7.8.1 SandboxAQ Company Details
7.8.2 SandboxAQ Business Overview
7.8.3 SandboxAQ AI for Science Introduction
7.8.4 SandboxAQ Revenue in AI for Science Business (2021-2026)
7.8.5 SandboxAQ Recent Development
7.9 NVIDIA
7.9.1 NVIDIA Company Details
7.9.2 NVIDIA Business Overview
7.9.3 NVIDIA AI for Science Introduction
7.9.4 NVIDIA Revenue in AI for Science Business (2021-2026)
7.9.5 NVIDIA Recent Development
7.10 XtalPi
7.10.1 XtalPi Company Details
7.10.2 XtalPi Business Overview
7.10.3 XtalPi AI for Science Introduction
7.10.4 XtalPi Revenue in AI for Science Business (2021-2026)
7.10.5 XtalPi Recent Development
7.11 DP Technology
7.11.1 DP Technology Company Details
7.11.2 DP Technology Business Overview
7.11.3 DP Technology AI for Science Introduction
7.11.4 DP Technology Revenue in AI for Science Business (2021-2026)
7.11.5 DP Technology Recent Development
7.12 Altair
7.12.1 Altair Company Details
7.12.2 Altair Business Overview
7.12.3 Altair AI for Science Introduction
7.12.4 Altair Revenue in AI for Science Business (2021-2026)
7.12.5 Altair Recent Development
7.13 Westlake Omics
7.13.1 Westlake Omics Company Details
7.13.2 Westlake Omics Business Overview
7.13.3 Westlake Omics AI for Science Introduction
7.13.4 Westlake Omics Revenue in AI for Science Business (2021-2026)
7.13.5 Westlake Omics Recent Development
8 AI for Science Market Dynamics
8.1 AI for Science Industry Trends
8.2 AI for Science Market Drivers
8.3 AI for Science Market Challenges
8.4 AI for Science Market Restraints
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.1.1 Research Programs/Design
10.1.1.2 Market Size Estimation
10.1.1.3 Market Breakdown and Data Triangulation
10.1.2 Data Source
10.1.2.1 Secondary Sources
10.1.2.2 Primary Sources
10.2 Author Details
10.3 Disclaimer
TABLE OF FIGURES
List of Tables
List of Figures
KEY QUESTIONS ADDRESSED BY THE REPORT
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