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Table Of Content
October 2024
The global AI in materials discovery market is expected to expand significantly, fueled by breakthroughs in deep learning, quantum computing, and big data.The market sizing and forecasts are revenue-based (USD Million/Billion), with 2024 as the base year.
The global AI in materials discovery market trends show rising investments and collaborations between tech firms and research institutions to advance material innovations. The demand for AI in materials discovery is increasing due to the growing need for rapid investments and innovations. The AI adoption is also expected to turn out to be cost-effective in the long run.
The AI in materials discovery market refers to the use of artificial intelligence (AI), machine learning (ML), and data-driven algorithms to accelerate and optimize the discovery, design, development, and testing of new materials. This includes polymers, alloys, composites, ceramics, and nanomaterials across a variety of industrial applications. AI tools reduce the cost, time, and trial-and-error traditionally associated with material R&D by simulating properties, predicting performance, and guiding synthesis strategies.
| Report Coverage | Details |
| Dominating Region | North America |
| Fastest Growing Region | Asia Pacific |
| Base Year | 2024 |
| Forecast Period | 2025 to 2034 |
| Segments Covered | Material Type, Technology Type, Function/Workflow Application, Deployment Mode, End-use Industry and Region |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Rising government initiatives
Multiple governments are focusing on launching strategies and programs to prioritise the use of AI in material innovation. The leading global countries, like the United States, have launched the Material Genome Initiative to boost the discovery, development, and deployment of advanced materials. These factors are playing a crucial role in adopting advanced resources and technologies to improve the outcome of these initiatives.
The rising initiatives are also backed by the rising funding for laboratories, universities and other research centres to focus on the discovery of sustainable materials. The AI in materials discovery market is expanding rapidly as departments like NSF(USA), BMBF(Germany), and DST(India) are leveraging AI and ML to boost their operations.
Higher initial investment
The growth of AI is highly adopted in the developed economies due to the higher institutional and government support. The use of AI in material innovation is limited for some startups or institutions, as it requires advanced software and hardware infrastructure. The lower financial availability in third-world countries restricts them from focusing on innovations and discovery in various industries. Additionally, the AI wave is in its initial phase, which still lacks some trained professionals with specialization in a niche, which increases their demand in the current market situation.
Rise of the AI material discovery platform
The traditional research and development activities are time-consuming and costlier, which adds certain restrictions in some markets. The revolution of technologies like Artificial Intelligence (AI) and Machine Learning (ML) is one of the major innovations that is helping in innovation and discovery. AI-powered platforms are gaining significant popularity due to the structure that provides on-demand solutions to users. Tools like SaaS and PaaS have been in higher demand in recent years, and are being integrated with the material datasets. Some of the current market examples are Citrine Informatics, which is a leading Software-as-a-Service (SaaS) company that utilizes artificial intelligence (AI) and materials science expertise to accelerate the development and optimization of materials and chemicals.
The polymers segment generated the highest revenue share in 2024. These materials are molecules made up of repeating units, which are plastics, rubbers, and resins. The dominance of the segment is attributed to the widespread user base of these materials in various industries like automotive, construction, electronics, healthcare and many more. The AI in materials discovery market is expanding rapidly due to the higher data availability, which helps in the use of AI for more detailed research and development. Additionally, the AI database is highly used in these activities due to the simple structure of the polymer properties. The higher industry use is also expected to drive more innovations for sustainable innovations in the future.
The nanomaterials segment is expected to grow at the fastest CAGR during the projected period of 2025 to 2034. These materials include structural features at the nanoscale that offer unique properties, which make them ideal for applications in medicine, energy and electronics. The growth of the segment is attributed to the functional properties, which often require AI and ML to manage the complex tasks. The rising demand for advancements in electronics, aerospace, and biomedicine is expected to drive innovation from governments and leading companies.
The machine learning segment marked its dominance by contributing the highest revenue share in 2024. The technology involves the use of algorithms that learn patterns from data and make further predictions. The dominance of the segment is attributed to the widespread adoption of ML, which helps in predicting the hardness, thermal resistance and other properties within the spectrum, making it more reliable. The rising requirement has also made the integration easier to implement compared to other technologies. The AI in materials discovery market is expected to gain more popularity as the structural working of ML is more compatible with handling polymers, alloys and other materials.
The generative model segment is anticipated to grow at the fastest CAGR during the forecast period of 2025 to 2034. The technologies create new data or content based on the training inputs, which can help in material design. The growth of the segment is attributed to the high relevance of these materials in drug delivery, battery chemistry and the designing of semiconductors, which is one of the highly popular programs in the recent market situation. These models are marking significant growth as the researchers are applying GANs in their process for faster discovery. The rising R&D activities throughout multiple sectors are expected to drive more demand for such generative models in the upcoming years.
The property prediction segment accounted for the largest revenue share in 2024. The workflow involves the use of AI to predict the chemical, physical, thermal or mechanical properties of material. The dominance of the segment is attributed to the foundational step in R&D, i.e. property prediction, which leverages the use of AI, enabling the researchers to evaluate the material in a shorter period. The AI in materials discovery market is expanding rapidly due to the availability of a database that allows effective training for more accurate results. The rising R&D activities in various fields like electronics, aerospace, automotive and others are expected to create more rapid demand in the coming years due to lower time consumption.
The synthesis route prediction segment is expected to grow at the fastest CAGR during the forecast period of 2025 to 2034. The workflow is the use of AI to predict the innovation of a material. The growth of the segment is attributed to the higher AI requirement in identifying materials, especially nanomaterials. The use of AI simplifies the process by analyzing massive chemical reaction data. The AI in materials discovery market is expected to gain popularity as the majority of the labs are adopting automation to increase accuracy in their operations. The rising AI adoption is also expected to gain significant popularity in the rise of novel material innovation.
The cloud-based segment generated the highest revenue share in 2024. The dominance of the segment is attributed to the accessibility of these cloud platforms, which allows researchers and companies to manage their requirements without any additional hardware investments. The AI in materials discovery market is expected to gain popularity as SMEs are adopting the use of cloud-based services in their daily operations. The leading companies are also relying on such platforms, as they eliminate the geographical barriers and maintain the workflow throughout various setups. The rising investments in security and constant updates are expected to improve the work pace with fewer distractions.
The hybrid segment is expected to grow at the fastest CAGR during the forecast period of 2025 to 2034. The growth of the segment is attributed to the rising requirement in industries like aerospace, pharmaceuticals and defence, which raises the requirement for both on-premise and cloud infrastructure. The hybrid setups are expected to gain more popularity in the future as AI is helping them to improve their privacy and data security.
The pharmaceuticals and biotechnology segment marked its dominance by generating the highest revenue share in 2024. The industry uses AI for drug material discovery and other operations. The dominance of the segment is attributed to the identification capability in targeted drug materials to improve the treatment effectiveness and patient safety. The AI in materials discovery market is expected to rise rapidly due to stringent regulations in the medical sector that leverage AI for more personalized outcomes. Additionally, the larger data availability is leading towards more demand in material modelling. The rising government support for healthcare improvement is expected to improve the outcomes.
The energy and power segment generated the highest revenue share in 2024. The growth of the segment is attributed to the higher advanced materials for performance optimization. AI is being highly used for predicting the material behaviour that gives real-time data for adopting sustainable and clean energy innovations. The constant government push for zero-net emissions is expected to create a huge demand for AI in the upcoming years. The renewable technologies like solar cells, electric vechicle batteries are also gaining demand at a rapid pace, which will help the market grow rapidly in the future.
North America dominated the global AI in material discovery market by generating the highest revenue share in 2024. The dominance of the segment is attributed to the well-established infrastructure in the United States and Canada. The research institutions and national laboratories like Stanford, MIT and others are highly helping the region to lead in the global AI scenario. The presence of leading tech companies in the region is also creating multiple investments from the governments towards improving the use of AI in material innovation.
U.S. AI in Material discovery market trends
The United States stands as a dominant country in AI in materials discovery market due to the higher investments in R&D. The AI in materials discovery market is expected to maintain its growth throughout due to the growing investments from platforms like Citrine and DeepMind’s with the laboratories in the country. The advancing industries in the US, like automotive and aerospace, are expected to create more demand for cloud-based infrastructure adoption in the coming years. Moreover, the U.S. healthcare system is also expanding rapidly, which will help the market adopt AI in the future.
Asia Pacific AI in Materials Discovery Market Trends:
Asia Pacific is expected to grow at the fastest CAGR during the forecast period of 2025 to 2034. The growth of the segment is attributed to the manufacturing expansion in countries like India, South Korea and China. The AI in materials discovery market is expected to grow more rapidly as these governments are investing in R&D for improvements in their defence, healthcare and other sectors. The governments are also funding institutions like IIT and Tsinghua University, Tokyo University, for using AI in material discovery. The rising economic expansion is also expected to help the growth of startups and tech companies to enter the Asian market for more business growth.
China stands as a leader in the Asian business landscape due to its AI and material innovation focus. The country has been constantly investing in Next-Gen AI development with an aim to improve the workforce at a rapid pace. Additionally, the country is one of the leading electronic manufacturers, which is attracting massive investments for AI and ML adoption. The country contributes a higher number of material innovations on the global stage due to its advanced infrastructure.
By Material Type
By Technology Type
By Function/Workflow Application
By Deployment Mode
By End-use Industry
By Region
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