AI in Chemicals Market worth $3.8 billion by 2029- Exclusive Report by MarketsandMarkets™

Browse in-depth TOC on “AI in Chemicals Market”
348 – Tables

69 – Figures

360 – Pages

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Scope of the Report

By component, the services segment to account for higher CAGR during the forecast period.

AI services, including professional and managed services, are transforming the chemicals market by providing expertise, support, and solutions tailored to AI-driven initiatives. Professional services encompass consulting, implementation, and customization of AI solutions, assisting organizations in defining AI strategies, selecting appropriate technologies, and integrating AI into existing workflows. Managed services, on the other hand, offer ongoing support, monitoring, and maintenance of AI systems, enabling organizations to focus on core operations while outsourcing AI management to experts. Managed services providers offer proactive monitoring, troubleshooting, and optimization of AI infrastructure and applications, ensuring reliability, scalability, and security. Both professional and managed services play a crucial role in accelerating AI adoption, driving innovation, and maximizing the benefits of AI technologies in the chemicals industry.

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By Business Application, the production segment is expected to hold the largest market size for the year 2024.

The chemical industry is currently undergoing significant transformation, due to the widespread adoption of artificial intelligence. This revolutionary technology is driving efficiency, promoting innovation, and streamlining production processes in the sector. By utilizing AI-powered solutions such as machine learning algorithms, advanced analytics, and real-time data analysis, chemical companies are optimizing their manufacturing operations like never before. From production planning to quality control, AI is enhancing product quality, maximizing yields, and resulting in significant cost reductions and increased enhances product quality, maximizes yields, significantly reduces costs, and increases productivity. In addition, AI’s ability to analyze vast datasets allows companies to adapt to changing market demands quickly adapt to changing market demands, reducing inventory losses, and optimizing offerings. Furthermore, AI technologies are playing a crucial role in promoting environmental sustainability by minimizing waste and energy consumption. As more organizations recognize the potential benefits of AI integration, the chemical industry is poised for further advancement.

By End User, active ingredients is projected to grow at the highest CAGR during the forecast period.

Active ingredients are specific substances that provide therapeutic or functional properties to products, such as agrochemicals, personal care items, and household chemicals. These ingredients play a critical role in the effectiveness and performance of end products, whether they are medicines, pesticides, skin care products, or cleaning agents. In various sectors, AI is increasingly being used to develop, optimize, and apply active ingredients. In the agrochemical industry, AI algorithms analyze agricultural data to develop novel pesticides and herbicides that have improved efficacy and environmental safety profiles. In the personal care and household chemicals industries, AI assists in the formulation of formulation of skincare products, cosmetics, and cleaning agents with optimized active ingredient concentrations, stability, and performance characteristics. Furthermore, AI-driven predictive modeling and simulation enable manufacturers to forecast market demand, customize formulations based on consumer preferences, and optimize production processes for efficiency and cost-effectiveness.

Asia Pacific is expected to grow at the highest CAGR during the forecast period.

The rapid growth in AI adoption within the chemical sector across Asia Pacific stems from its ability to address industry challenges effectively. AI technologies offer solutions for optimizing manufacturing processes, predicting equipment failures, and improving product quality. Additionally, the region’s burgeoning demand for chemicals necessitates increased efficiency and innovation, driving companies to embrace AI-driven approaches. Moreover, governmental initiatives and investments in AI infrastructure further propel its adoption, positioning Asia Pacific as a frontrunner in leveraging AI for chemical industry advancement.

Top Key Companies in AI in Chemicals Market:

The major AI in chemicals providers include 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). These companies have used both organic and inorganic growth strategies such as product launches, acquisitions, and partnerships to strengthen their position in the AI in Chemicals Market.

Recent Developments:

• In March 2024, AWS and NVIDIA collaborated to enhance computer-aided drug discovery using new AI models. Their collaboration focuses on modeling the efficacy of new chemical molecules, predicting protein structures, and gaining insights into how drug molecules interact with biological targets, contributing significantly to advancements in pharmaceutical research and development.
• In January 2024, a robotic chemistry lab collaborated with Google AI to predict and synthesize novel inorganic materials, leveraging advanced algorithms and automation for accelerated material discovery and development.
• In November 2023, GE Vernova’s Gas Power business announced its collaboration with Duke Energy on the nation’s first 100% green hydrogen-fueled peaking power plant. GE Vernova will support the development of an end-to-end green hydrogen system at Duke Energy’s DeBary plant in Volusia County, Florida, near Orlando.
• In October 2023, NobleAI, known for Science-Based AI solutions in Chemical and Material Informatics, partnered with Azure Quantum Elements (AQE), a Microsoft cloud service merging High-Performance Computing (HPC), AI, and quantum computing. This collaboration integrated AQE’s advanced molecular simulation, and HPC features with NobleAI’s AI-driven solutions.
• In May 2023, Google Cloud unveiled two new AI-powered life sciences solutions to speed up drug discovery and precision medicine for biotech companies, pharmaceutical firms, and public sector organizations. The Target and Lead Identification Suite aids researchers in identifying amino acid functions and predicting protein structures, while the Multiomics Suite accelerates genomic data discovery and interpretation, facilitating the design of precision treatments.
• In May 2023, the chemical industry is collaborating with Siemens on a pilot project to reduce carbon emissions in its supply chain. This partnership is part of the Together for Sustainability initiative, involving 47 chemical companies that opted for Siemens’ “Sigreen” solution for digitally exchanging Product Carbon Footprint (PCF) data.
• In April 2023, Mitsui Chemicals and IBM Japan collaborated to enhance agility and accuracy in discovering new applications by merging Generative Pre-trained Transformer (GPT) with IBM Watson Discovery. They aim to drive sales and market share growth for Mitsui Chemicals products through advanced digital transformation (DX) in the business sector.

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AI in Chemicals Market Advantages:

• The increasing popularity of cloud-based QLM systems can be attributed to their cost-effectiveness, scalability, and flexibility, which enable enterprises to leverage advanced QLM features without making substantial initial expenditures in IT infrastructure.
• Artificial intelligence (AI)-driven optimisation algorithms help to expedite the time it takes to bring new goods to market by streamlining chemical processes, cutting down on waste, minimising experimentation time, and optimising resource usage.
• In order to generate chemicals with improved quality, consistency, and performance that satisfy demanding regulatory standards and customer expectations, artificial intelligence (AI) models can forecast chemical reactions, optimise formulations, and detect process parameters.
• AI models are able to identify process parameters, optimise formulations, and forecast chemical reactions. Artificial intelligence (AI)-enabled systems are able to assess chemical dangers, forecast safety issues, and suggest preventive actions to reduce accidents, guarantee worker safety, and adhere to environmental, health, and safety laws.chemicals that satisfy strict regulatory criteria and customer expectations while improving quality, consistency, and performance.
• Algorithms for AI-based predictive maintenance examine sensor data from chemical processing machinery to find irregularities, forecast equipment breakdowns, and plan maintenance in advance, reducing downtime and increasing output.
• Artificial intelligence (AI) algorithms enhance supply chain operations through demand prediction, inventory management, logistics route optimisation, and cost-effective sourcing strategy identification. These algorithms also improve manufacturing and distribution efficiency and responsiveness in the chemical industry.
• Artificial Intelligence (AI) propels innovation and competitiveness in the chemicals business by enabling the customisation of chemical products and formulations to match individual client requirements, preferences, and applications.

Report Objectives

• To define, describe, and predict the AI in Chemicals Market by component (hardware, software, and services), business application, and end users
• To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
• To forecast the market size of segments with respect to five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
• To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the overall AI in Chemicals Market
• To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
• To analyze competitive developments, such as partnerships, mergers and acquisitions, and product developments, in the AI in Chemicals Market
• To analyze the impact of the recession across all the regions in the AI in Chemicals Market

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