AI materials discovery market seen growing at 29.4% CAGR to 2030

The Business Research Company says the artificial intelligence in materials discovery market is on track to top $3 billion by 2030, with North America and the U.S. leading the expansion. Software is expected to dominate the market as companies use AI to speed up materials research in chemicals, semiconductors, clean energy and healthcare.

Why it matters: - Artificial intelligence is moving deeper into materials science, where faster discovery can shorten development cycles and cut research costs. - The market remains small compared with the broader chemicals and advanced materials industries, but the growth rate points to rising adoption across industrial sectors. - Demand is being driven by companies looking for better-performing, more sustainable materials in energy, aerospace, semiconductors and healthcare.

What happened: - The Business Research Company published its Artificial Intelligence (AI) in Materials Discovery Global Market Report 2026 – Market Size, Trends, And Forecast 2026-2035 on Oct. 16, 2026. - The report projects the AI in materials discovery market will exceed $3 billion by 2030. - The market is forecast to grow at a 29.4% compound annual growth rate through 2030. - North America is expected to lead the market by 2030 with a value of $0.9 billion. - The U.S. is projected to be the largest country-level market at $0.8 billion by 2030.

The details: - AI in materials discovery is estimated to make up about 2% of the broader advanced materials market, which is projected to reach about $133 billion by 2030. - The segment represents about 0.04% of the chemicals industry, which the report puts at $7,007 billion by 2030. - The software segment is expected to be the largest category, accounting for 60% of the market, or about $2 billion, by 2030. - The market is segmented by material type, including polymers, metals and alloys, ceramics, composites, nanomaterials and semiconductors. - The technology split includes machine learning, deep learning, generative AI and natural language processing. - Deployment models include on-premise, cloud-based and hybrid systems. - End users include chemical companies, pharmaceutical firms, research institutions and manufacturing companies. - The report says AI adoption is being pulled by the need to accelerate materials development and reduce experimental cycles. - The report says sustainability spending is increasing demand for AI tools that can help identify recyclable components, advanced batteries and lower-carbon manufacturing inputs. - Pharmaceutical and healthcare research is also adding demand through biomaterials, molecular optimization, drug delivery, tissue engineering and diagnostics. - The report highlights software, hardware and services as the most promising growth areas, with those segments expected to generate more than $1.8 billion by 2030. - From 2025 to 2030, the software segment is expected to add $1 billion, services $0.5 billion and hardware $0.3 billion. - Schrödinger Inc. leads the market in 2025 with a 1% share. - Other named players include Dassault Systèmes, Citrine Informatics, CuspAI, QuesTek Innovations, Iktos, Atinary Technologies, Kebotix, Aionics, Materials Zone, Intellegens, Toyota Research Institute, IBM, Exabyte.io, Enthought, Google, Polymerize, Polaron Analytics, Phaseshift Technologies and Microsoft. - The report says the market is fairly fragmented, with the top 10 companies holding about 5% of 2025 revenue. - Listed suppliers include Advanced Micro Devices, Intel, Taiwan Semiconductor Manufacturing Company, Samsung Electronics, SK hynix, Micron Technology, Broadcom, Marvell Technology, Qualcomm, Synopsys, Cadence Design Systems, Ansys, Amazon Web Services, Microsoft Azure, Google Cloud, Oracle Cloud Infrastructure, Dell Technologies, Hewlett Packard Enterprise and Lenovo. - Listed distributors include TD SYNNEX, Ingram Micro, Arrow Electronics, Avnet, Redington, Westcon-Comstor, Exclusive Networks, Crayon Group, Insight Enterprises, CDW, SHI International, Computacenter, Softchoice, Bechtle, Carahsoft Technology, ePlus, Presidio, Bytes Technology Group and SoftwareONE. - Named end users include BASF, Dow, Evonik Industries, Covestro, 3M, LG Chem, Sumitomo Chemical, Mitsubishi Chemical Group, Bayer, Johnson Matthey, Toyota Motor, Airbus, Pfizer, Roche, Merck KGaA, Novo Nordisk, Siemens Energy, Umicore, Albemarle and Saint-Gobain.

Between the lines: - The report shows a niche market becoming commercially relevant because AI can compress the long timelines of materials R&D. - North America’s lead reflects concentration in AI providers, research infrastructure and public-private investment in computational materials science. - The U.S. advantage points to strong scientific funding, high-performance computing access and a growing commercial market for AI materials platforms. - A June 2025 partnership between Hyundai Motor Group and CuspAI shows how automakers are using generative AI to target next-generation mobility materials. - The report’s emphasis on software suggests value is shifting toward models, workflows and cloud-based research tools rather than only lab hardware.

What's next: - The report expects market growth to continue through 2030 as companies expand AI-driven modeling, high-throughput screening and predictive simulation. - The Business Research Company says ongoing partnerships, autonomous labs, foundation models and quantum computing integration will shape competition. - More companies are likely to pursue sustainable materials and faster commercialization as industrial buyers push for shorter development cycles. - The 2026 report edition adds market attractiveness scoring, TAM analysis, company scoring graphics, Excel forecasting dashboards and updated trend visuals.

The bottom line: - AI in materials discovery is still a small market, but the combination of a 29.4% CAGR, strong North American demand and software-led growth signals a fast-rising commercial category.