{"id":96187,"date":"2026-07-06T09:00:28","date_gmt":"2026-07-06T09:00:28","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/96187\/"},"modified":"2026-07-06T09:00:28","modified_gmt":"2026-07-06T09:00:28","slug":"ai-in-materials-discovery-market-to-reach-2-77-billion-by-2030-high-cagr-of-30-expected","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/96187\/","title":{"rendered":"AI in Materials Discovery Market to Reach $2.77 Billion by 2030: High CAGR of 30% Expected"},"content":{"rendered":"

\"Company<\/a> Company Logo <\/p>\n

Key opportunities in AI-driven materials discovery include increasing demand for rapid advanced materials development, growth in AI-based modeling adoption, and collaborations between academia and industry. Additionally, innovations like autonomous labs and cloud platforms enhance results. Rapid growth is expected, especially in Asia-Pacific. <\/p>\n

AI in Materials Discovery Market <\/p>\n

\"AI<\/a> AI in Materials Discovery Market <\/p>\n

Dublin, July 06, 2026 (GLOBE NEWSWIRE) — The “AI in Materials Discovery Global Market Report 2026”<\/a> has been added to ResearchAndMarkets.com’s offering.<\/p>\n

<\/a> <\/p>\n

The artificial intelligence (AI) in materials discovery market is experiencing exponential growth, projected to increase from $0.74 billion in 2025 to $0.97 billion in 2026, with a compound annual growth rate (CAGR) of 30.3%. This growth is driven by the rising adoption of computational modeling, the availability of digital materials datasets, investment in AI-based research, the use of machine learning in laboratories, and industry-academia collaborations. Looking ahead, the market is estimated to reach $2.77 billion by 2030, maintaining a CAGR of 30%. <\/p>\n

Factors fueling this anticipated growth include the urgent need for rapid discovery of advanced materials, demand for high-performance energy storage solutions, and adoption of generative AI models. Additionally, the deployment of cloud-based simulation platforms and pressure to shorten research and development cycles contribute to this trend. Key advancements expected include multimodal AI models, high-throughput computational screening, autonomous lab systems, and quantum-enhanced materials simulations. <\/p>\n

AI-driven computational modeling and simulations are pivotal to market expansion. These technologies predict material properties, design compounds, and optimize structures, minimizing traditional experimentation. There is increasing pressure on research institutions to accelerate innovation and cut costs, which AI is helping to address by enabling high-throughput virtual screening and accurate property prediction. A prime example is Ames National Laboratory’s AI-based modeling, which achieved a 100x speed-up over traditional calculations, leading to the identification of new compounds. <\/p>\n

Industry leaders are focusing on large-scale crystal structure prediction to expand chemical space and accelerate material identification. For instance, Google DeepMind’s GNoME system predicted 2.2 million new crystal structures, identifying 380,000 as potentially stable. This system employs graph neural networks and integrates active learning to refine predictions and validate structural stability, marking significant progress in computational materials discovery. <\/p>\n

Story Continues <\/p>\n

Acquisitions are also shaping the market, as shown by Comstock Inc.’s acquisition of Quantum Generative Materials LLC (GenMat) in 2024. This acquisition is set to bolster Comstock’s materials innovation by integrating GenMat’s generative modeling platform and automated workflows, supporting a portfolio expansion in high-performance, sustainability-focused materials. <\/p>\n

Major companies in the AI materials discovery market include Google LLC, Microsoft Corporation, BASF SE, IBM, Dassault Systemes, and Nautilus Materials Inc. North America was the largest region in 2025, while Asia-Pacific is expected to grow the fastest during the forecast period. <\/p>\n

The market value includes revenues from services like predictive algorithm development, computational simulations, and cloud-based modeling. It comprises sales of AI-driven simulation software and modeling platforms, with offerings spanning software, hardware, and services targeting various material types like polymers, metals, ceramics, and composites. Core technologies include machine learning and generative AI, with deployment modes ranging from on-premises to hybrid solutions. This market is influenced by tariffs impacting hardware costs, prompting a shift towards cloud-based platforms for improved accessibility and scalability. <\/p>\n

The “Artificial Intelligence (AI) in Materials Discovery Market Global Report 2026” offers an in-depth analysis essential for strategists, marketers, and senior management to evaluate market dynamics. With a focus on an industry experiencing robust growth, this report outlines emerging trends set to influence the market over the next decade. <\/p>\n

Reasons to Purchase: <\/p>\n

Obtain a global perspective with the most comprehensive market coverage across 16 geographies. <\/p>\n

Analyse macro factors like geopolitical conflicts, trade policies, and economic variables impacting the market. <\/p>\n

Develop regional strategies based on local data and analysis. <\/p>\n

Identify investment opportunities in growth segments. <\/p>\n

Surpass competitors with data-driven insights on market drivers and trends. <\/p>\n

Leverage end-user analysis for customer insights. <\/p>\n

Benchmark your company against key competitors in market share, innovation, and brand strength. <\/p>\n

Evaluate the total addressable market and market attractiveness scoring to measure potential. <\/p>\n

Utilize reliable data and analysis to support presentations and strategic planning. <\/p>\n

Receive updates with the latest data delivered within 2-3 days of order, along with an Excel data sheet for analysis. <\/p>\n

Description <\/p>\n

This comprehensive report addresses critical questions surrounding the AI in materials discovery market, examining market relationships to the broader economy and other sectors. It highlights forces such as technological disruption and changing consumer preferences shaping the market. <\/p>\n

The report encompasses market characteristics, size, growth, segmentation, regional breakdowns, total addressable market, market attractiveness scores, competitive landscape, and strategic trends. It offers historical and forecast market growth by geography, expanding coverage to regions like Taiwan and Southeast Asia, crucial in the global value chain. <\/p>\n

Market characteristics: Examines key products\/services, brand differentiation, and innovation trends. <\/p>\n

Supply chain analysis: Provides an overview of the value chain and competitor insights. <\/p>\n

Trends and strategies: Focus on digital transformation, automation, sustainability, and AI-driven innovation. <\/p>\n

Regulatory and investment landscape: Details on regulatory frameworks and investment trends influencing growth. <\/p>\n

Market size: Covers historic and forecasted market size, considering technological impacts and global events. <\/p>\n

Total addressable market analysis: Measures potential against current market size, offering strategic insights. <\/p>\n

Market attractiveness scoring: Evaluates growth, competition, and strategic fit with interpretive implications. <\/p>\n

Regional and country breakdowns: Analyzes market size and growth across geographies. <\/p>\n

Competitive landscape: Details market nature, shares, leading companies, and significant financial deals. <\/p>\n

Company scoring matrix: Ranks companies on market share, product innovation, and brand recognition. <\/p>\n

Report Scope: <\/p>\n

Offering: Software, Hardware, Services <\/p>\n

Material Type: Polymers, Metals and Alloys, Ceramics, Composites, Nanomaterials, Semiconductors <\/p>\n

Technology: Machine Learning, Deep Learning, Generative AI, Natural Language Processing <\/p>\n

Deployment Mode: On-Premise, Cloud-Based, Hybrid <\/p>\n

End-User: Chemical, Pharmaceutical, Research, Manufacturing, Other End-Users <\/p>\n

Key Attributes: <\/p>\n

Report Attribute <\/p>\n

Details <\/p>\n

No. of Pages <\/p>\n

250 <\/p>\n

Forecast Period <\/p>\n

2026 – 2030 <\/p>\n

Estimated Market Value (USD) in 2026 <\/p>\n

$0.97 Billion <\/p>\n

Forecasted Market Value (USD) by 2030 <\/p>\n

$2.77 Billion <\/p>\n

Compound Annual Growth Rate <\/p>\n

30.0% <\/p>\n

Regions Covered <\/p>\n

Global <\/p>\n

Companies Featured <\/p>\n

The companies featured in this AI in Materials Discovery market report include: <\/p>\n

For more information about this report visit https:\/\/www.researchandmarkets.com\/r\/ne73a8<\/a> <\/p>\n

About ResearchAndMarkets.com
ResearchAndMarkets.com is the world’s leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends. <\/p>\n

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