Dublin, May 23, 2024 (GLOBE NEWSWIRE) -- The "Global AI in Chemicals Market by Component (Hardware, Software (by Type, Technology, Deployment Mode), Services), Business Application, End User (Basic Chemicals, Active Ingredients, Paints & Coatings) and Region - Forecast to 2029" report has been added to ResearchAndMarkets.com's offering.
The global AI in chemicals market is valued at USD 0.7 billion in 2024 and is estimated to reach USD 3.8 billion in 2029, registering a CAGR of 39.2% during the forecast period. Optimizing chemical processes with AI-enabled solutions serves as a potential driver for accelerating the adoption of AI in the chemical sector. As more than 80% of chemical companies now prioritize sustainability alongside revenue growth, AI emerges as a crucial tool for achieving these goals. Notably, in 2022, two-thirds of companies actively developing AI strategies reported significant increases in both productivity and sustainability achievements. 
AI-powered predictive models offer precise recommendations for formulations and manufacturing processes, advancing sustainability objectives while significantly improving return on investment. Companies implementing AI strategies have witnessed notable cost reductions of up to 30% and impressive decreases of 20% in greenhouse gas emissions within their chemical workflows. Successful integration of AI relies on robust data foundations and effective training strategies. Ensuring data diversity and quality is paramount to maintaining accuracy and preventing model drift, safeguarding against suboptimal predictions and investments. Through enriched datasets and curated training sets, companies validate AI models, unlocking new insights and breakthroughs.
By component, the software segment is projected to hold the largest market size during the forecast period
The AI landscape in the chemicals market is multifaceted, encompassing a diverse range of various software solutions tailored to specific industry needs. These software solutions is are categorized by type, including dashboard and analytics tools that enable real-time data visualization and strategic decision-making, process simulation software that aids in modeling and optimizing chemical processes, chemical modeling software for molecular design and analysis, laboratory management software for efficient lab operations, virtual screening tools for drug discovery and materials design, and chemical property prediction tools for predicting material properties and behavior.
This software is further categorized by advanced technologies such as machine learning, deep learning, generative AI, natural language processing (NLP), computer vision, and advanced analytics. Moreover, these software are deployed across different modes, including cloud-based solutions for scalability, flexibility, and accessibility, as well as on-premises deployments for data security, control, and compliance. This diverse software ecosystem forms the foundation for AI-driven innovation, optimization, and transformative advancements in the chemicals industry.
By Business Application, R&D is registered to grow at the highest CAGR during the forecast period
The chemical sector is undergoing a significant transformation driven by the rapid adoption of artificial intelligence (AI) technologies. This shift is propelled by the need for more efficient and sustainable research and development (R&D) processes. In November 2022, Chemical.AI, a Shanghai-based R&D AI technology firm, secured USD 14 million in Series B funding. Chemical.AI specializes in harnessing AI and automation to create an intelligent chemical synthesis platform, thereby boosting research efficacy in chemistry and streamlining drug discovery processes.
Initiatives such as the collaboration between Eastman and NC State's Department of Chemical and Biomolecular Engineering exemplify this trend by leveraging AI, catalysis, and robotics to create self-driving labs. By automating labor-intensive tasks and accelerating compound discovery and property prediction, AI optimizes R&D processes, leading to more sustainable and efficient manufacturing of specialty chemicals. Additionally, companies such as Quantistry, with its advanced cloud-native simulation platform integrating Quantum and AI technologies, are further revolutionizing chemical research and development. Their focus on sustainability and efficiency, coupled with quantum-based simulations and AI-driven insights, enables innovative materials' optimization, discovery, and design.
Asia Pacific is projected to witness the highest CAGR during the forecast period
The Asia Pacific region is experiencing a transformative shift in the chemicals industry due to the integration of artificial intelligence technologies. Countries such as China and Japan are leading this transformation with robust investments in AI research, development, and implementation across the chemical value chain. China, being the largest chemicals market, is leveraging AI for process optimization, predictive maintenance, and supply chain management, driving efficiency and cost savings.
Japan's chemical industry, renowned for its innovation, is adopting AI for product development, quality control, and sustainability initiatives, contributing to its global competitiveness. India's rapidly growing chemical sector is embracing AI for smart manufacturing, safety enhancements, and environmental sustainability, supported by government initiatives and private investments. South Korea, with its focus on AI research and development, is fostering AI-driven innovations in chemical production processes, driving technological advancements and market competitiveness.
Research Coverage
The market study covers AI in chemicals across segments. It aims at estimating the market size and the growth potential across different segments, such as component (hardware, software [by type, technology, and, deployment mode] & services), business application, end users, and region. It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.
Major vendors offering AI in chemicals hardware, software and services across the globe are IBM (US), Microsoft (US), Schneider Electric (France), AWS (US), Google (US), SAP (Germany), NVIDIA (US), C3.ai (US), GE Vernova (US), Siemens (Germany), Hexagon (Sweden), Engie Impact (US), TrendMiner (Belgium), Xylem (US), NobleAI (US), Iktos (France), Kebotix (US), Uptime AI (US), Canvass AI (Canada), Nexocode (Poland), SandboxAQ (US), Deepmatter (England), Zapata AI (US), Citirne Informatics (US), Chemical.AI (China), Augury (Israel), Intellegens (UK), Ripik.AI (India), Tractian (US), Polymerize (Singapore), ScienceDesk (Germany), OptiSol Business Solutions (India), NuWater (Africa) and VROC (Australia).
Key Attributes
| Report Attribute | Details |
| No. of Pages | 361 |
| Forecast Period | 2024-2029 |
| Estimated Market Value (USD) in 2024 | $0.7 Billion |
| Forecasted Market Value (USD) by 2029 | $3.8 Billion |
| Compound Annual Growth Rate | 39.2% |
| Regions Covered | Global |
Premium Insights
- Rising Demand for AI-Enhanced Process Optimization to Boost Market Growth
- AI in Chemicals Market to Witness Minor Decline in Y-O-Y Growth in 2024
- Services Segment to Grow at Highest CAGR During Forecast Period
- Software and Basic Chemicals Segments to Account for Significant Shares in AI in Chemicals Market in 2024
- North America to Account for Largest Market Share in 2024
Market Dynamics
- Drivers
- Growing Demand for AI for R&D Purposes in Chemicals and Materials Sectors
- Rising Demand for AI-Enhanced Chemical Process Optimization
- Restraints
- High Cost Associated with AI Implementation in Chemical Industry
- Regulatory Constraints Posing Obstacles to Scalability of AI Solutions in Chemical Sector
- Opportunities
- Growing Demand for AI-based Predictive Maintenance
- Growing Integration of Generative AI to Unlock Unprecedented Opportunities
- Challenges
- Issues Related to Converting Chemical Data into Machine-Readable Data
- Lack of Skilled Workforce
Ecosystem Analysis
- Software Providers
- Service Providers
- End-users
- Regulatory Bodies
Case Study Analysis
- Evonik Collaborated with IBM Research Europe and MIT-IBM Watson AI Lab to Leverage AI to Accelerate Development and Optimization of Materials
- Indorama Ventures Optimized Risk Management with SAP's Intelligent Asset Management and Aslnt's Solutions
- Terray Therapeutics Revolutionized Drug Discovery with AI-Driven Molecular Design Coati by Leveraging Nvidia DGX Cloud
- BASF Optimized Chemical Plant Uptime with AI-Driven Remote Monitoring Substation 6 Build with Help of Schneider Electric
- Large European Specialty Chemicals Manufacturer Implemented C3 AI Process Optimization Application to Improve Manufacturing Yields
Technology Analysis
- Key Technologies
- Conversational AI
- LLMS
- Context-Aware Computing
- Cloud Computing
- Augmented Analytics
- Adjacent Technologies
- Digital Twins
- IoT
- RPA
- Blockchain
- Cybersecurity
Pricing Analysis
- Indicative Pricing Analysis of AI in Chemicals, by Component
- Average Selling Price Trend of Key Players: Top Three Business Applications
Patent Analysis
- Methodology
- Patents Filed, by Document Type
- Innovation and Patent Applications
- Top 10 Applicants in AI in Chemicals Market
Trade Analysis
- Import Scenario of Automatic Data-Processing Machines and Units
- Export Scenario of Automatic Data-Processing Machines and Units
Technology Roadmap
- Short-Term Roadmap (1-3 Years)
- Long-Term Roadmap (3-10 Years)
Companies Featured
- IBM
- Microsoft
- Nvidia
- Schneider Electric
- Aws
- SAP
- Siemens
- C3 AI
- GE Vernova
- Hexagon Ab
- Engie Impact
- Trendminer
- Xylem
- Nobleai
- Iktos
- Kebotix
- Uptime AI
- Canvass AI
- Nexocode
- Sandboxaq
- Deepmatter
- Zapata AI
- Citrine Informatics
- Chemical.AI
- Augury
- Intellegens
- Ripik.AI
- Tractian
- Polymerize
- Sciencedesk
- Optisol Business Solutions
- Nuwater
- Vroc
For more information about this report visit https://www.researchandmarkets.com/r/7iozjn
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