CHICAGO, May 22, 2024 (GLOBE NEWSWIRE) — AI in the chemical market According to a new report from MarketsandMarkets™, the market is projected to grow from USD 700 million in 2024 to USD 3.8 billion by 2029, at a CAGR of 39.2% during the forecast period.
AI in the chemical market is experiencing a surge in AI adoption driven by two key factors: increased integration of AI in research and development (R&D) processes and growing demand for AI-powered solutions to optimize chemical processes. These trends reflect a strategic shift in the chemical industry towards innovation and the use of advanced technologies to improve operational efficiency.
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AI in the chemical market dynamics:
driver:
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growing demand artificial intelligence Research and development objectives in the field of chemistry and materials
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Growing demand for AI-powered chemical process optimization
Restraint:
opportunity:
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Growing demand for AI-based predictive maintenance
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Integration continues Generative AI To open up unprecedented opportunities
List of major players AI in the chemical market:
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The field of chemistry is undergoing a remarkable transformation with the integration of artificial intelligence. AI algorithms are being harnessed to tackle complex chemical problems, delivering breakthrough innovations, expanding applications, and shaping the future of this multifaceted field. AI is revolutionizing the field of chemistry by enabling researchers to more efficiently explore the vast chemical space, accelerate materials discovery, optimize chemical processes, and design molecules with specific properties. It's bringing. This trend is also fostering collaboration between chemists, data scientists, and AI experts, facilitating interdisciplinary research and development efforts. Additionally, AI-driven advances are driving greener processes, reduced waste, and increased energy efficiency, making the chemical industry more sustainable. As AI continues to evolve, we can expect even more breakthrough discoveries and applications that will shape the future of chemistry and its impact on society, driving progress towards a more sustainable and innovative chemistry field.
The support and maintenance segment of the market is projected to grow at the highest CAGR during the forecast period. Support and maintenance services include various activities such as proactive monitoring, troubleshooting, software upgrades, performance tuning, etc. The objective is to optimize various activities such as proactive monitoring, troubleshooting, software upgrades, performance tuning, etc. Monitoring toolstroubleshooting, software upgrades, and performance tuning to optimize the uptime and effectiveness of your AI solution. Our support team provides timely assistance, technical issue resolution, and ongoing monitoring of your AI systems to identify and address potential issues before they impact your business. We also provide regular software updates, patches, and enhancements to keep your AI systems up-to-date, secure, and compliant with industry standards.
Maintenance services focus on fine-tuning AI algorithms, optimizing data pipelines, and improving system scalability and responsiveness to changing business requirements. In addition, our support and maintenance teams provide training, documentation, and knowledge transfer to enable internal teams to manage and leverage AI technology, ensuring that internal teams can effectively manage and leverage AI technology. Masu. AI professional service providers provide comprehensive support and maintenance services to help you get the most value from your AI investments, achieve continuous improvement, and stay competitive in a rapidly evolving environment. I can.
By hardware, accelerators are expected to grow at the highest CAGR during the forecast period. Accelerators help drive advances in AI within the chemical market, providing the computational power needed to efficiently process complex algorithms and large datasets. Graphics processing units (GPUs) are one of the most widely used accelerators, providing parallel processing capabilities that significantly accelerate AI model training and inference tasks. These GPUs are often optimized with AI-specific architectures, such as NVIDIA's Tensor Cores, and excel at matrix multiplication operations, which are essential for deep learning computations.
Similarly, Tensor Processing Units (TPUs) developed by Google have gained attention for their specialized design, specifically focused on accelerating machine learning workloads in cloud-based AI applications. Field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs) are also notable accelerators in the AI domain. In addition, advances in hardware accelerators include the integration of AI inference chips directly into sensors and edge devices, enabling real-time AI capabilities at the edge of chemical processes.
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AI presents numerous opportunities for the chemical market, from streamlining R&D to optimizing manufacturing processes and improving product quality. One of the key opportunities is to accelerate materials discovery. AI algorithms can analyze huge data sets and predict new materials with desirable properties, speeding up innovation cycles and reducing time to market for new products. AI also enables predictive maintenance in chemical plants by analyzing sensor data to detect anomalies and potential equipment failures, minimizing downtime and optimizing production schedules. In addition, AI-powered process optimization can improve yields, reduce waste, and improve energy efficiency, helping to reduce costs and achieve sustainability goals. Additionally, AI-driven insights into market trends and consumer preferences can inform strategic decision-making, product development, and marketing strategies, helping chemical companies stay competitive in a rapidly changing environment.
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