AI for Science Market Size(US$)

CAGR 2025-2031
28.9%
Market Size,2031
USD 20,810
Million
Market Snapshot
Source: Secondary research, interviews with experts, and QYResearch analysis
The global market for AI for Science was valued at US$ 3268 million in the year 2024 and is projected to reach a revised size of US$ 20810 million by 2031, growing at a CAGR of 28.9% during the forecast period.
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.
North American market for AI for Science is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for AI for Science is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for AI for Science in Biological and Pharmaceutical is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of AI for Science include Google DeepMind, OpenAI, IBM, Cerebras Systems, Owkin, Schrödinger, BenevolentAI, SandboxAQ, NVIDIA, XtalPi, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for AI for Science, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding AI for Science.
The AI for Science market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global AI for Science market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the AI for Science companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
MARKET SEGMENTATION
CHAPTER OUTLINE
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of AI for Science company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
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.
We cover competition landscape, full supply chain and quantified market size data, and deliver tailor-made customized surveys to meet your unique business demands.
We own self-owned massive exclusive databases, backed by 19 years of global market research experience across thousands of sectors.
Our team operates 24 hours a day, 365 days a year, enabling ultra-fast report turnaround to respond to your research needs efficiently.
We integrate regional risk assessment, localized product optimization and competitor analysis to deliver actionable market strategies.
All data is cross-verified from multiple industry sources to deliver thorough, precise analysis that supports reliable corporate strategic decisions.
We provide responsive, dedicated after-sales support to resolve all follow-up inquiries about reports, data and industry interpretation.
TABLE OF CONTENTS
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global AI for Science Market Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Closed-loop AI
1.2.3 Human-in-the-loop AI
1.3 Market by Application
1.3.1 Global AI for Science Market Growth by Application: 2020 VS 2024 VS 2031
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 (2020-2031)
2.2 Global AI for Science Growth Trends by Region
2.2.1 Global AI for Science Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 AI for Science Historic Market Size by Region (2020-2025)
2.2.3 AI for Science Forecasted Market Size by Region (2026-2031)
2.3 AI for Science Market Dynamics
2.3.1 AI for Science Industry Trends
2.3.2 AI for Science Market Drivers
2.3.3 AI for Science Market Challenges
2.3.4 AI for Science Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top AI for Science Players by Revenue
3.1.1 Global Top AI for Science Players by Revenue (2020-2025)
3.1.2 Global AI for Science Revenue Market Share by Players (2020-2025)
3.2 Global Top AI for Science Players by Company Type and Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by AI for Science Revenue
3.4 Global AI for Science Market Concentration Ratio
3.4.1 Global AI for Science Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by AI for Science Revenue in 2024
3.5 Global Key Players of AI for Science Head office and Area Served
3.6 Global Key Players of AI for Science, Product and Application
3.7 Global Key Players of AI for Science, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 AI for Science Breakdown Data by Type
4.1 Global AI for Science Historic Market Size by Type (2020-2025)
4.2 Global AI for Science Forecasted Market Size by Type (2026-2031)
5 AI for Science Breakdown Data by Application
5.1 Global AI for Science Historic Market Size by Application (2020-2025)
5.2 Global AI for Science Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America AI for Science Market Size (2020-2031)
6.2 North America AI for Science Market Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America AI for Science Market Size by Country (2020-2025)
6.4 North America AI for Science Market Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe AI for Science Market Size (2020-2031)
7.2 Europe AI for Science Market Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe AI for Science Market Size by Country (2020-2025)
7.4 Europe AI for Science Market Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific AI for Science Market Size (2020-2031)
8.2 Asia-Pacific AI for Science Market Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific AI for Science Market Size by Region (2020-2025)
8.4 Asia-Pacific AI for Science Market Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America AI for Science Market Size (2020-2031)
9.2 Latin America AI for Science Market Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America AI for Science Market Size by Country (2020-2025)
9.4 Latin America AI for Science Market Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa AI for Science Market Size (2020-2031)
10.2 Middle East & Africa AI for Science Market Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa AI for Science Market Size by Country (2020-2025)
10.4 Middle East & Africa AI for Science Market Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Google DeepMind
11.1.1 Google DeepMind Company Details
11.1.2 Google DeepMind Business Overview
11.1.3 Google DeepMind AI for Science Introduction
11.1.4 Google DeepMind Revenue in AI for Science Business (2020-2025)
11.1.5 Google DeepMind Recent Development
11.2 OpenAI
11.2.1 OpenAI Company Details
11.2.2 OpenAI Business Overview
11.2.3 OpenAI AI for Science Introduction
11.2.4 OpenAI Revenue in AI for Science Business (2020-2025)
11.2.5 OpenAI Recent Development
11.3 IBM
11.3.1 IBM Company Details
11.3.2 IBM Business Overview
11.3.3 IBM AI for Science Introduction
11.3.4 IBM Revenue in AI for Science Business (2020-2025)
11.3.5 IBM Recent Development
11.4 Cerebras Systems
11.4.1 Cerebras Systems Company Details
11.4.2 Cerebras Systems Business Overview
11.4.3 Cerebras Systems AI for Science Introduction
11.4.4 Cerebras Systems Revenue in AI for Science Business (2020-2025)
11.4.5 Cerebras Systems Recent Development
11.5 Owkin
11.5.1 Owkin Company Details
11.5.2 Owkin Business Overview
11.5.3 Owkin AI for Science Introduction
11.5.4 Owkin Revenue in AI for Science Business (2020-2025)
11.5.5 Owkin Recent Development
11.6 Schrödinger
11.6.1 Schrödinger Company Details
11.6.2 Schrödinger Business Overview
11.6.3 Schrödinger AI for Science Introduction
11.6.4 Schrödinger Revenue in AI for Science Business (2020-2025)
11.6.5 Schrödinger Recent Development
11.7 BenevolentAI
11.7.1 BenevolentAI Company Details
11.7.2 BenevolentAI Business Overview
11.7.3 BenevolentAI AI for Science Introduction
11.7.4 BenevolentAI Revenue in AI for Science Business (2020-2025)
11.7.5 BenevolentAI Recent Development
11.8 SandboxAQ
11.8.1 SandboxAQ Company Details
11.8.2 SandboxAQ Business Overview
11.8.3 SandboxAQ AI for Science Introduction
11.8.4 SandboxAQ Revenue in AI for Science Business (2020-2025)
11.8.5 SandboxAQ Recent Development
11.9 NVIDIA
11.9.1 NVIDIA Company Details
11.9.2 NVIDIA Business Overview
11.9.3 NVIDIA AI for Science Introduction
11.9.4 NVIDIA Revenue in AI for Science Business (2020-2025)
11.9.5 NVIDIA Recent Development
11.10 XtalPi
11.10.1 XtalPi Company Details
11.10.2 XtalPi Business Overview
11.10.3 XtalPi AI for Science Introduction
11.10.4 XtalPi Revenue in AI for Science Business (2020-2025)
11.10.5 XtalPi Recent Development
11.11 DP Technology
11.11.1 DP Technology Company Details
11.11.2 DP Technology Business Overview
11.11.3 DP Technology AI for Science Introduction
11.11.4 DP Technology Revenue in AI for Science Business (2020-2025)
11.11.5 DP Technology Recent Development
11.12 Altair
11.12.1 Altair Company Details
11.12.2 Altair Business Overview
11.12.3 Altair AI for Science Introduction
11.12.4 Altair Revenue in AI for Science Business (2020-2025)
11.12.5 Altair Recent Development
11.13 Westlake Omics
11.13.1 Westlake Omics Company Details
11.13.2 Westlake Omics Business Overview
11.13.3 Westlake Omics AI for Science Introduction
11.13.4 Westlake Omics Revenue in AI for Science Business (2020-2025)
11.13.5 Westlake Omics Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 Market Size Estimation
13.1.1.3 Market Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer
TABLE OF FIGURES
List of Tables
List of Figures
KEY QUESTIONS ADDRESSED BY THE REPORT
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REPORT COVERAGE
DESCRIPTION
MARKET SEGMENTATION
QYRESEARCH'S STRENGTHS
TABLE OF CONTENTS
TABLE OF FIGURES
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