Artificial Intelligence (AI) in Chemicals Market Eyes USD 28 Billion by 2034 as Sustainability and Digital Twins Transform Production

The global artificial intelligence (AI) in chemicals market size is expected to hit approximately USD 28 billion by 2034 increasing from USD 2.29 billion in 2025 with a strong CAGR of 32.05% from 2025 to 2034. This surge is fueled by AI-driven process optimization, predictive maintenance, accelerated drug and material discovery, and sustainability initiatives that are reshaping the chemical industry worldwide.

Ottawa, Aug. 19, 2025 (GLOBE NEWSWIRE) -- According to Precedence Research, the global artificial intelligence (AI) in chemicals market size was estimated at USD 1.78 billion in 2024 and is expected to exceed USD 2.29 billion in 2025. Between 2025 and 2034, the market is expected to represent a compound annual growth rate (CAGR) of 32.05% 2025 to 2034. It is projected to reach around USD 28 billion by 2034.

AI in the chemical market is driven by process optimization, predictive maintenance, supply chain efficiency, and faster innovation in manufacturing and materials.

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Artificial Intelligence (AI) in Chemicals Market – Key Takeaways

In terms of revenue, the AI in chemicals market has been calculated at USD 2.29 billion in 2025.
It is projected to attain USD 20.59 billion by 2033.
The global market for AI in chemical is expected to expand at a solid CAGR of 32.05% from 2025 to 2034.
North America accounted for the largest market share of 39.4% in 2024.
By type, the services segment contributed the highest market share of 40.22% in 2024.
By end use, the base chemicals and petrochemicals segment held the major market share of 57.5% 2034.
By application, the “others” generated the highest market share of 30.20% in 2024.

Artificial Intelligence (AI) in Chemicals Market Size Analysis from 2022 to 2024

AI in Chemicals Market Size (USD Million) By Type 2022-2024

Type	2022	2023	2024
Hardware	252.5	318.9	403.0
Software	398.9	513.6	662.0
Services	426.7	552.7	716.5

AI in Chemicals Market Size (USD Million) By Application 2022-2024

Application	2022	2023	2024
Discovery of New Materials	114.2	147.0	189.4
Production Optimization	109.0	141.5	183.8
Pricing Optimization	109.0	140.7	181.8
Load Forecasting of Raw Materials	106.8	137.7	177.6
Product Portfolio Optimization	101.3	130.3	167.8
Feedstock Optimization	98.2	126.7	163.7
Process Management and Control	106.8	138.3	179.3
Others	332.7	423.0	538.1

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Artificial Intelligence in Chemicals Market Overview

What is Artificial Intelligence in the Chemical Industry?

Artificial intelligence is revolutionizing the chemical industry through the improvement in efficiency and optimization of processes, and innovation. It makes processes automated, conditions of manufacturing improve, and assists in comprehending chemical reactions, increasing productivity at all phases of the process and product development.

It is also AI that helps the industry towards achieving sustainability due to the potential to design eco-friendly solutions and minimize environmental impact. There is a rising usage as governmental investment in R&D increases, assisting optimal production, better utilization of resources, and satisfaction of regulatory demands.

What are Latest Trends in AI in Chemicals Market:

Generative AI for Molecular Design – Generative AI is enabling the rapid design of new molecules and materials by predicting their properties and behaviors before lab testing begins.
Smart Manufacturing and Digital Twins – AI-driven digital twins and automated systems are revolutionizing chemical production by improving real-time process control and reducing operational inefficiencies.
Predictive Maintenance and Process Optimization – AI tools are enhancing equipment reliability and production efficiency by forecasting failures and dynamically adjusting process parameters.
Sustainability and Energy Efficiency – AI is being increasingly used to reduce emissions, cut energy consumption, and support the development of eco-friendly materials and recycling systems.
AI in Drug and Agrochemical Discovery – Advanced AI models are accelerating the discovery of new pharmaceuticals and agricultural chemicals by significantly shortening the research and development cycle.

Key Applications of AI in Chemicals Sector:

Drug Discovery – AI accelerates the identification and development of new drug molecules by predicting biological activity and optimizing compound structures.
Process Optimization – AI algorithms help enhance chemical production efficiency by analyzing process data to minimize energy use and reduce waste.
Predictive Maintenance – Machine learning models forecast equipment failures in chemical plants, reducing downtime and improving safety.
Material Discovery – AI assists in discovering new materials and polymers by simulating properties and reactions faster than traditional methods.
Supply Chain Management – AI optimizes logistics, demand forecasting, and inventory management, ensuring timely delivery and reduced operational costs.

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Artificial Intelligence in Chemicals Market Opportunity

Advancements in AI Models:

The new method of AI can transform the search for new chemical compounds, catalysts, and materials by forecasting and creating new structures of chemicals that have the desired properties. Generative models may also prove useful in optimizing formulations, searching novel reaction pathways, and finding rare but potentially valuable variants of compounds.

They can facilitate drug discovery in pharmaceuticals in that they can propose viable molecular structures in which target diseases can be designed. They can come up with greener alternatives to toxic chemicals in the context of sustainable chemistry, in line with global environmental agendas.

What is the Limitation of Artificial intelligence in chemicals market?

The use of AI may also incur high costs of efficient software, hardware, and human resources. Numerous chemical firms, especially small firms, have no in-house experience in AI development and integration and must outsource these activities to more costly practices and, in the long term, ongoing expenditures. Smart technologies are also more complex, which makes repairing and upgrading them more expensive, contributing to the overall costs of ownership. Additionally, the development of AI models in chemical applications is also very computationally expensive, and thus, it can increase the operational costs even further.

Scope of Artificial Intelligence (AI) in Chemicals Market

Report Attributes	Key Statistics
Market Size in 2024	USD 1.78 Billion
Market Size in 2025	USD 2.29 Billion
Market Size in 2030	USD 8.56 Billion
Market Size by 2034	USD 28 Billion
CAGR 2025 to 2034	8.82%
Leading Region in 2024	North America
Base Year	2024
Forecast Period	2025 to 2034
Segments Covered	Type, Application, End Use and Region
Regions Covered	North America, Europe, Asia-Pacific, Latin America and Middle East & Africa
Key Players Covered	Manuchar N.V, IMCD N.V., Univar Solutions Inc., Brenntag S.E., Sojitz Corporation, ICC Industries Inc., Azelis Group NV, Tricon Energy Inc., Biesterfeld AG, Omya AG, HELM AG, Sinochem Corporation, Petrochem Middle East FZE and Others.

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Artificial Intelligence in Chemicals Market Key Regional Analysis:

How North America Dominated Artificial intelligence in chemicals market?

North America dominated the artificial intelligence in chemicals market in 2024 because its technological base was well developed, and the research system was powerful. The region is also a world-renowned hub of most AI technology corporations, high-level research centers, and chemical leaders working together to incorporate AI in production, research and development, and supply chains.

An effective regulatory framework is helpful in the deployment of AI by outlining suitable usage to ensure the safety and efficacy of AI in the various industries, including the chemical industry. Also, public and private investments have spurred the use of AI towards optimization of business processes, environmental initiatives, and cost-effectiveness.

How Big is the U.S. Artificial Intelligence (AI) in Chemicals Market?

According to Precedence Research, the U.S. artificial intelligence in chemicals market size surpassed USD 630.29 million in 2024. It is expected to grow from 804.12 million in 2025 to approximately USD 9,050.04 million by 2034. The market is growing at a double-digit CAGR of 30.9% from 2025 to 2034.

United States Artificial Intelligence in Chemicals Market Trends:

The United States is experiencing significant growth in the use of artificial intelligence (AI) within the chemical industry. This surge is being driven by a combination of strong investment in research and development, government support for AI initiatives, and growing demand for efficiency and innovation in chemical production.

AI is transforming various aspects of the sector, including drug discovery, agrochemical development, process engineering, and materials science. In pharmaceuticals, AI accelerates the development of new drugs by predicting molecular interactions and optimizing clinical trial designs. In agriculture, AI tools are helping companies develop more effective herbicides and pesticides in less time.

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Why is Europe the Fastest-Growing in Artificial intelligence in chemicals market?

Europe experiences the fastest growth in the market during the forecast period, owing to the robust government backing, favorable policies, and an increasing number of AI-enhanced chemical manufacturing facilities. The European Union and countries are committing funds to the research and development of artificial intelligence, sustainability programs, and chemical manufacturing modernization to minimize the effect on the environment.

Favorable policies, including the Green Deal developed by the EU, promote developing innovations in energy-efficient and sustainable processes, which boost the adoption of AI. Also, the European increased interest in green chemistry and the shift toward healthier alternatives to toxic substances coincides quite well with the strengths of AI in the research of novel materials and optimization of the processes.

Artificial intelligence in Chemicals Market Segmentation Analysis:

Type Analysis

The services segment dominated the artificial intelligence in chemicals market in 2024 because of the demand for professional services in the process of implementing, customizing, and maintaining the AI solutions. Most chemical companies do not have this in-house technical expertise and hence are motivated to seek the services of specialized companies.

These services comprise consulting, system integration, training, and long-term support so that the AI tools may be highly optimized towards the requirements of individual businesses, like predictive maintenance, process optimization, and chemical reaction modelling.

The software segment is the fastest-growing in the market during the forecast period because of the growing demand for high data management and analysis tools. AI-driven software is able to handle and manage large amounts of data produced in chemistry research and development and especially in drug discovery and material innovation.

These solutions enhance the accuracy of predictive modeling, increase the speed of decision-making, and minimize development costs. As digital transformation, real-time analytics, and sustainability-based innovations gradually gain more focus, AI software and tools are becoming increasingly popular.

Application Analysis

The discovery of new materials segment dominated the artificial intelligence in chemicals market in 2024. This enables the scientists to search a huge chemical space, predict the behavior of materials, and create missing property data on existing and hypothetical materials. Simulation methods also lessen the physical testing that is costly and cumbersome. Creating more efficient discovery schedules and designing complex materials that include high-performance polymers and new catalysts, AI helps chemical firms remain competitive. This fast, cost-effective, innovative ability discovers new materials in the most promising application segment.

The production optimization segment is the fastest-growing in the market during the forecast period. Machine learning algorithms, deep learning methods, and predictive models based on AI allow chemical manufacturers to streamline processes by predicting best working parameters, inefficiencies, and waste. Such systems can also provide real-time monitoring so that timely corrections can be made to an enterprise in a way that avoids shutdowns and maintains stable product quality.

With the growing pressure of competition and environmental regulations, chemical firms are forging AI-enabled production optimization to sustain the profitability objectives and sustainability targets, which makes it the most rapidly growing use case in the market.

End Use Analysis

The base chemicals & petrochemicals segment held the largest share in the artificial intelligence in chemicals market in 2024, due to the large-scale production in the sector, as well as its complicated operations, in which the integration of AI helps in large-scale production. These resolutions assist in the optimization of the reaction, reduction of equipment offline duration, and production of the same quality of the product, which is imperative in the mass manufacture of chemicals. Further, AI helps sustainability efforts through energy efficiency, waste minimisation, and emission reduction, making it compliant with all environmental laws and business objectives on sustainability.

Case Study: SABIC – Predictive Maintenance and AI-Driven Operational Excellence

SABIC, one of the world’s largest chemical producers, has been under pressure to enhance efficiency, cut costs, and meet sustainability goals while running complex petrochemical operations. In 2024, the company accelerated its adoption of AI to improve plant reliability, reduce downtime, and optimize energy consumption.

AI Deployment:

SABIC integrated AI-powered monitoring systems across multiple production facilities to predict equipment failures before they occurred.
Using advanced machine learning models, the system analyzed sensor data from pumps, compressors, and reactors in real time.
The program also incorporated digital twin technology to simulate plant behavior, allowing operators to test scenarios virtually before applying changes on the shop floor.

Results & Impact:

According to case documentation, SABIC’s predictive maintenance deployment prevented an estimated US$107,000 in downtime losses during a single incident, demonstrating immediate ROI.
The AI system improved overall equipment effectiveness (OEE) by boosting availability and reliability across critical assets.
By reducing unplanned shutdowns and energy waste, SABIC aligned the initiative with its sustainability strategy, lowering emissions and resource use.

Why It Matters for the Market:

SABIC’s case illustrates the core value proposition of AI in chemicals:

For process optimization: AI continuously fine-tunes operations for maximum throughput.
For predictive maintenance: It reduces costly downtime and extends asset life.
For sustainability: It supports emission reduction and efficient energy management.

This example reinforces your report’s insight that predictive maintenance and process optimization are among the fastest-growing AI applications in the chemical industry. It also validates why base chemicals & petrochemicals hold the largest end-use share: large-scale, asset-intensive operations benefit most from AI adoption.

Transform Your Chemical Operations with AI

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Artificial Intelligence in Chemicals Market Top Companies

Manuchar N.V
IMCD N.V.
Univar Solutions Inc.
Brenntag S.E.
Sojitz Corporation
ICC Industries Inc.
Azelis Group NV
Tricon Energy Inc.
Biesterfeld AG
Omya AG
HELM AG
Sinochem Corporation
Petrochem Middle East FZE

Recent Developments:

In April 2025, the Icahn School of Medicine at Mount Sinai opened the AI small-molecule drug discovery center, formed to combine the power of AI with conventional drug discovery to discover and design new small-molecule therapeutics with breakthrough speed and accuracy.
In April of 2025, UTulsa started incorporating AI courses in the chemical engineering program. The Russell School of Chemical Engineering at the University of Tulsa has introduced AI into the curriculum to initiate students on the novel technology.
In March 2025, A U.K. start-up described itself as having a plan to use AI to identify previously unknown chemicals and materials and has recruited two distinguished scientists, often called the godfathers of AI, a major AI policy adviser, and a significant quantity of research at a top university in materials sciences.

Artificial Intelligence (AI) in Chemicals Market Segments Covered in the Report

By Type

Hardware
Software
Services

By Application

Discovery of New Materials
Production Optimization
Pricing Optimization
Load Forecasting of Raw Materials
Product Portfolio Optimization
Feedstock Optimization
Process Management & Control

By End Use

Base Chemicals & Petrochemicals
Specialty Chemicals
Agrochemicals

By Geography

North America
Europe
Asia-Pacific
Latin America
Middle East and Africa

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