Automation in Chemicals Petrochemicals Market Size, Share & Trends Analysis Report By Product (Distributed control system (DCS), Supervisory control and data acquisition, Manufacturing execution system), By Applications (Chemicals, Petrochemicals), By End Use, By Region, and Segment Forecasts - 2035

Automation in Chemicals Petrochemicals Market Overview

The automation in chemicals petrochemicals market size is expected to grow from USD 532.88 million in 2025 to USD 570.34 million in 2026 and is forecast to reach USD 699.27 million by 2035 at 7.03% CAGR over 2026-2035.

The automation in chemicals petrochemicals market is entering a more software-intensive phase as chemical producers and petrochemical operators modernize process control, production visibility, plant scheduling, asset monitoring, and operational decision-making. Distributed control system (DCS) installations remain central to continuous-process environments because production facilities frequently operate 24 hours per day and require stable control across thousands of connected measurements and control loops. During 2025-2026, modernization programs are increasingly combining DCS infrastructure with supervisory control and data acquisition and manufacturing execution system capabilities rather than treating the 3 product types as isolated technologies. Large integrated complexes are also moving toward real-time optimization, industrial artificial intelligence, advanced analytics, digital twins, predictive maintenance, and contextualized operational data. The supplied forecast indicates an increase of USD 37.46 million between 2025 and 2026, equivalent to approximately 7.0% annual expansion, while the USD 166.39 million difference between 2025 and 2035 illustrates the continuing importance of automation investment throughout the forecast horizon. Chemical and petrochemical operators are particularly prioritizing brownfield modernization because replacing an entire control architecture can involve multiple production units, thousands of instruments, and scheduled shutdown windows measured in days or weeks.

The United States remains one of the most technologically mature environments for automation in chemicals and petrochemicals, supported by extensive refining, petrochemical, specialty chemical, and downstream manufacturing infrastructure. U.S. plants are increasingly using automation modernization to address operational reliability, cybersecurity, workforce productivity, emissions management, and aging control assets. DCS platforms retain a prominent role because continuous chemical processes can require 99% or higher operational availability objectives at critical production units, while SCADA is increasingly relevant for geographically distributed storage, pipeline, terminal, and utility operations. Manufacturing execution system adoption is also progressing as operators connect production scheduling, quality information, maintenance workflows, and plant-floor data with enterprise systems. During 2024-2026, industrial automation suppliers intensified software-defined control and industrial AI development, with new refinery optimization deployments demonstrating prediction accuracy reaching 98.5% for selected yield and quality applications. These advances are strengthening the case for integrated automation architectures capable of combining process control with AI-assisted optimization without requiring operators to replace every installed control asset simultaneously.

• 

  Download Free sample to learn more about this report.

Key Findings

• Leading Product Type: Distributed control system (DCS) is expected to hold the largest share, accounting for approximately 45% of market deployment as continuous chemical and petrochemical processes require highly available, decentralized control across complex production units.
• Leading Application: Petrochemicals are expected to represent approximately 58% of market demand, supported by automation-intensive cracking, polymerization, separation, refining integration, storage, and utility operations that require continuous process monitoring and coordinated production control.
• Leading Region: North America is expected to lead with approximately 34% market share as operators accelerate modernization of mature chemical and petrochemical assets while expanding industrial AI, advanced control, cybersecurity, and predictive-maintenance capabilities.
• Fastest Growing Region: Asia Pacific is projected to record the fastest regional expansion at approximately 8.5% annually, supported by new chemical complexes, refining-petrochemical integration, manufacturing capacity additions, and increasing adoption of digitally connected production infrastructure.
• Technology Trend: Industrial AI is becoming increasingly important as advanced refinery optimization applications have demonstrated prediction accuracy of up to 98.5%, encouraging chemical operators to connect process models, plant data, and automated decision-support technologies.
• Market Driver: Brownfield digitalization is a major growth driver as automation modernization can connect thousands of plant data points while supporting production environments operating 24 hours daily, increasing demand for interoperable control and execution platforms.
• Competitive Landscape: Competitive activity increasingly centers on integrated digital ecosystems, illustrated by 2 automation-focused agreements announced by a major Indian refining-petrochemical operator in February 2025 to accelerate AI, analytics, optimization, and process-control deployment.
• Future Outlook: Autonomous operations will increasingly influence automation strategies through 2035 as suppliers advance software-defined control, AI and integrated operations platforms, while the market maintains a forecast CAGR of 7.03% between 2026 and 2035.

Latest Trends

Industrial artificial intelligence, software-defined automation, edge-to-cloud connectivity, and integrated operational data are reshaping automation strategies across chemicals and petrochemicals. The traditional automation hierarchy is evolving from separately managed control, supervisory, and production systems toward architectures that can contextualize information across plant operations. During 2025, major automation technology developers advanced enterprise operations platforms intended to connect existing operational technology with modern AI applications without requiring complete replacement of installed infrastructure. This approach is particularly relevant to chemical and petrochemical sites where automation systems can remain operational for 15 to 25 years and where wholesale replacement can introduce unacceptable production risks. AI-assisted process models are also becoming more technically credible. In April 2026, a large-scale refinery application using hybrid AI models reported yield and quality prediction accuracy of up to 98.5% in selected processing units. Such performance demonstrates how industrial AI is progressing beyond experimental dashboards toward production planning, process optimization, quality forecasting, and operator decision support.

A second major trend is the convergence of DCS, supervisory control and data acquisition, and manufacturing execution system functions through interoperable data layers and open industrial communications. DCS remains the principal process-control technology for many continuous chemical operations, but operators increasingly expect plant data to move securely into higher-level production, maintenance, energy, and planning applications. Modern DCS releases introduced during 2024-2025 have therefore emphasized industrial network compatibility, virtualization, interoperability, lifecycle modernization, and pathways toward autonomous operation. At the same time, manufacturing execution system capabilities are expanding from conventional production tracking toward workflow automation, data visualization, quality management, energy monitoring, and cross-site production intelligence. Industrial sites may generate millions of time-series data points every day, making contextualization as important as collection. The emerging automation architecture consequently places greater emphasis on unified data models, zero-trust cybersecurity, OPC UA connectivity, real-time optimization, and edge computing, with 1 integrated information environment increasingly replacing several disconnected operational databases.

Market Dynamics

Driver

""Plant digitalization and operational optimization are accelerating automation modernization.""

Increasing pressure to improve plant reliability, production consistency, safety, energy efficiency, and workforce productivity is the strongest driver for automation in chemicals and petrochemicals. Continuous-process facilities typically operate 24 hours per day and 365 days per year, meaning even small improvements in availability or process stability can materially influence production performance. Automation platforms provide operators with continuous visibility into temperatures, pressures, flows, compositions, equipment conditions, alarms, and production schedules while enabling control actions within seconds or milliseconds. Modern DCS infrastructure is particularly important in complex chemical processes where hundreds or thousands of interconnected loops must remain stable despite changes in feed composition, operating rates, energy conditions, or equipment availability. With the overall market projected to expand at 7.03% annually during 2026-2035, modernization of installed automation assets is expected to remain a consistent investment priority.

Industrial AI and advanced analytics are reinforcing this driver by creating additional value from existing operational information. In modern refinery and petrochemical deployments, hybrid process models have achieved prediction accuracy as high as 98.5% for selected yield and product-quality parameters. Such capabilities enable planning systems and operators to evaluate operating scenarios faster than conventional manual analysis while preserving engineering constraints. Chemical companies are therefore shifting from automation focused mainly on maintaining process set points toward systems capable of optimization, prediction, anomaly identification, and decision support. A facility operating 8,760 hours annually can accumulate extremely large datasets from sensors and control systems, and the ability to convert those data into actionable recommendations is becoming an important differentiator between legacy and modern automation environments.

Restraint

""Complex brownfield upgrades and lifecycle costs restrict faster automation replacement.""

The long operational life of chemical and petrochemical assets creates a significant restraint because automation modernization must frequently integrate equipment and software installed across several technology generations. A production complex operating for 20 to 30 years may contain legacy controllers, proprietary networks, older field instruments, newer smart devices, multiple software databases, and different cybersecurity architectures. Replacing these systems can require carefully planned shutdowns because control equipment is directly connected to critical processes. Even a modernization program affecting only 1 production unit can involve engineering, factory acceptance testing, migration planning, operator training, commissioning, and contingency procedures. Consequently, many operators favor phased upgrades, which reduce operational disruption but can prolong the period during which old and new automation environments must coexist.

Cybersecurity and integration requirements further increase implementation complexity. Connecting DCS, supervisory control and data acquisition, and manufacturing execution system environments expands data accessibility but also creates additional interfaces that must be protected. Plants operating 24 hours daily cannot apply conventional information-technology upgrade practices without considering process safety and continuous production requirements. Legacy automation assets may have lifecycles exceeding 15 years, while modern software components can require security updates much more frequently. Operators must therefore balance 2 competing objectives: preserving deterministic, highly available process control while increasing connectivity for analytics and enterprise optimization. This requirement can slow purchasing decisions, particularly at smaller chemical sites with limited automation engineering resources.

Opportunity

""Industrial AI and integrated operations create substantial modernization opportunities.""

The transition toward autonomous and semi-autonomous plant operations represents a substantial opportunity for automation suppliers and chemical producers. Current developments are moving beyond conventional control toward architectures combining real-time plant information, process models, artificial intelligence, predictive analytics, advanced process control, and production planning. Modern platforms increasingly connect field devices, edge infrastructure, control systems, and enterprise software through 1 coordinated operational environment. This structure enables chemical companies to use installed automation assets while progressively adding AI applications instead of undertaking complete replacement programs. With the market expected to advance from USD 570.34 million in 2026 to USD 699.27 million by 2035, suppliers capable of supporting gradual modernization and interoperability are positioned to capture increasing demand.

Asia Pacific presents another important opportunity as refining, petrochemical, and chemical manufacturing investments create demand for both greenfield and brownfield automation. India, China, Southeast Asia, South Korea, and other manufacturing centers are expanding integrated production infrastructure while emphasizing energy management and operational digitalization. Large integrated refinery-petrochemical sites can include more than 10 major processing units alongside utilities, storage, logistics, and supporting facilities, creating extensive requirements for distributed control, supervisory monitoring, and production execution. In India, automation partnerships announced during 2025 specifically targeted AI, advanced analytics, real-time optimization, and digital transformation across refinery and petrochemical process units, demonstrating how emerging markets are increasingly adopting sophisticated automation rather than basic control infrastructure alone.

Challenge

""Interoperability, cybersecurity and workforce readiness complicate connected plant deployment.""

Achieving secure interoperability across multiple generations of operational technology remains one of the industry's most significant challenges. Chemical and petrochemical facilities commonly combine DCS, supervisory control and data acquisition, manufacturing execution system platforms, safety systems, historians, laboratory systems, asset-management applications, and enterprise software. These technologies may originate from several suppliers and can use communication standards developed more than 10 years apart. Operators consequently face the technical challenge of making plant information accessible without weakening control-system reliability or introducing cybersecurity vulnerabilities. Open industrial standards are improving interoperability, but each additional connection can expand the attack surface, making network segmentation, authentication, access management, monitoring, and secure data exchange increasingly important.

Workforce capability is equally important because digital transformation changes the skills required in control rooms and engineering organizations. Modern operators increasingly interact with predictive analytics, advanced visualization, AI recommendations, and integrated production information alongside conventional process alarms and control displays. A chemical complex operating across 3 shifts requires consistent competency across every operating team, meaning technology deployment must be accompanied by training, simulation, procedures, and change management. The challenge becomes greater as experienced personnel retire and organizations attempt to transfer decades of process knowledge into digital workflows. Automation suppliers are responding with more intuitive interfaces and embedded analytics, but successful implementation still depends on combining process engineering knowledge with control, software, data, and cybersecurity skills.

• 

  Download Free sample to learn more about this report.

Segmentation Analysis

By Types

Distributed control system (DCS): Distributed control system (DCS) represents approximately 46% of the Automation in Chemicals Petrochemicals Market and remains the leading product type because continuous chemical and petrochemical processes require highly reliable, coordinated, and centralized control of complex plant operations. DCS platforms integrate controllers, operator stations, process instrumentation, alarms, historians, and safety-related information into unified plant environments. Chemical producers use these systems to regulate temperature, pressure, flow, level, reaction conditions, and material movement across interconnected production units. Petrochemical facilities depend heavily on DCS because process instability can affect product quality, equipment reliability, energy efficiency, and plant safety. Modern DCS platforms increasingly incorporate advanced analytics, predictive control, digital twins, remote engineering, and cybersecurity features. Operators are also adopting more modular and software-defined architectures that simplify system upgrades and reduce lifecycle complexity. With approximately 46% market share, DCS is expected to remain the largest automation category as chemical and petrochemical companies modernize aging control infrastructure and pursue higher operational efficiency.

Supervisory control and data acquisition: Supervisory control and data acquisition accounts for approximately 31% of market demand and plays an important role in monitoring distributed assets, utilities, storage terminals, pipelines, water systems, and geographically dispersed chemical and petrochemical infrastructure. SCADA systems collect real-time operating data from field devices and remote terminal units, allowing operators to supervise equipment status, process conditions, alarms, and performance from centralized control environments. Petrochemical companies increasingly use SCADA for tank farms, pipeline networks, loading terminals, and remote facilities where continuous visibility is essential. Chemical manufacturers also use SCADA to monitor utility systems, wastewater treatment, energy consumption, and supporting production infrastructure. Modern platforms are incorporating cloud connectivity, edge computing, mobile dashboards, advanced alarming, and cybersecurity controls. Approximately 31% market share reflects SCADA's importance in applications that require broad operational visibility across distributed assets rather than continuous closed-loop plant control alone. Greater industrial connectivity is expected to sustain investment in secure and scalable supervisory systems.

Manufacturing execution system: Manufacturing execution system represents approximately 23% of the Automation in Chemicals Petrochemicals Market and is gaining importance as producers seek stronger coordination between plant-floor operations and enterprise-level planning. MES platforms help manufacturers manage production schedules, batch execution, material genealogy, quality information, equipment utilization, inventory movement, and manufacturing records. Chemical companies increasingly use these systems to improve traceability and maintain consistent production across multiple process stages. Petrochemical operators can use MES to integrate operational data with planning systems and improve visibility into plant performance, product movement, and production efficiency. Digital transformation is accelerating demand as manufacturers seek real-time performance indicators rather than relying on manual reporting. Modern MES platforms increasingly connect with DCS, SCADA, laboratory systems, maintenance software, and enterprise applications to create integrated production environments. With approximately 23% market share, the segment remains smaller than DCS but offers strong long-term potential as chemical and petrochemical producers increase investment in data-driven manufacturing, production optimization, and plant-wide digitalization.

By Applications

Chemicals: Chemicals represents approximately 54% of the Automation in Chemicals Petrochemicals Market and remains the leading application because chemical manufacturing involves complex reactions, batch processes, continuous operations, hazardous materials, and demanding quality-control requirements. Automation systems help producers regulate process variables such as temperature, pressure, flow, concentration, and mixing conditions while maintaining consistent product specifications. DCS platforms are widely used in continuous chemical operations, while MES supports production scheduling, recipe management, traceability, and quality documentation. SCADA systems provide additional visibility across utilities, storage, water-treatment facilities, and distributed assets. Automation also helps reduce operator exposure to hazardous environments by enabling remote monitoring and automated process intervention. Chemical manufacturers are increasingly adopting predictive analytics, digital twins, advanced process control, and condition monitoring to improve equipment reliability and reduce unplanned shutdowns. Approximately 54% application share reflects the broad automation requirements of specialty chemicals, industrial chemicals, intermediates, and other process-intensive production environments where quality, safety, efficiency, and regulatory compliance remain critical.

Petrochemicals: Petrochemicals accounts for approximately 46% of market demand and represents a highly automation-intensive application because large processing facilities operate continuously and handle complex combinations of hydrocarbons, high temperatures, pressure conditions, and interconnected production units. DCS is particularly important for controlling cracking, separation, compression, distillation, heat-exchange, and material-transfer processes. SCADA provides monitoring across pipelines, storage terminals, utilities, and geographically dispersed supporting infrastructure, while MES improves production coordination and operational visibility. Petrochemical plants increasingly invest in advanced process control, predictive maintenance, digital twins, remote operations, and energy-management software to improve plant efficiency and reduce unplanned downtime. Automation also supports safer operations by monitoring abnormal conditions and enabling faster response to equipment or process deviations. Cybersecurity is becoming increasingly important as more plant assets become connected to industrial networks. With approximately 46% market share, Petrochemicals remains a major source of automation demand as operators modernize aging infrastructure and pursue higher reliability, energy efficiency, safety performance, and digital integration.

• 

  Download Free sampleto learn more about this report.

Regional Outlook

North America

North America is expected to retain the leading position with approximately 34% market share, supported by a mature chemical and petrochemical production base and sustained modernization of aging automation infrastructure. The United States represents the principal contributor as operators upgrade process controls, industrial networks, production information systems, cybersecurity architecture, and advanced analytics. Many major chemical and petrochemical facilities operate continuously for more than 8,000 hours annually, making automation reliability an important operating requirement. Modernization projects increasingly focus on replacing obsolete controllers and workstations while maintaining compatibility with installed field devices, thereby allowing companies to improve digital capabilities without undertaking complete plant reconstruction.

Industrial artificial intelligence and advanced process optimization are strengthening the region's automation outlook. North American technology suppliers are increasingly integrating AI-assisted analytics, digital twins, predictive maintenance, and software-defined automation into existing process-control environments. For complex facilities containing thousands of process measurements, these technologies can identify operating deviations considerably faster than conventional manual analysis. The regional transition is also supported by growing emphasis on cybersecurity as connected plants increase communication between operational and enterprise environments. Automation systems installed 15 to 25 years ago are becoming important modernization candidates, creating recurring opportunities for DCS migration, supervisory control upgrades, manufacturing execution system integration, and lifecycle services throughout 2026-2035.

Europe

Europe is estimated to account for approximately 24% of the automation in chemicals petrochemicals market, supported by established chemical clusters in Germany, the Netherlands, Belgium, France, Italy, and other industrial economies. European operators increasingly use automation to improve energy management, production flexibility, plant reliability, and emissions visibility while maintaining competitiveness in an environment characterized by volatile energy costs and stringent operational requirements. Chemical manufacturing facilities can operate across more than 300 days per year, making continuous process optimization important for controlling energy consumption and minimizing unplanned production interruptions. DCS modernization remains central to large continuous-process facilities, while manufacturing execution system adoption is increasing as companies pursue better production traceability and cross-site visibility.

European automation strategies are also becoming more closely connected with electrification, circular production, low-carbon processing, and digital energy management. Chemical plants increasingly require automation platforms capable of coordinating conventional feedstocks with recycled or alternative materials whose process characteristics can vary between production batches. Advanced control can evaluate hundreds of process variables simultaneously and adjust operating conditions faster than manual intervention. European manufacturers are also strengthening industrial cybersecurity as plants connect more operational information to enterprise applications and remote engineering environments. With the region representing nearly 1 quarter of global demand, suppliers offering lifecycle modernization, secure connectivity, advanced process control, and energy-focused analytics are positioned to benefit from ongoing digital transformation.

Asia Pacific

Asia Pacific is estimated to represent approximately 31% market share and is projected to be the fastest-growing region at approximately 8.5% annually. China, India, Japan, South Korea, and Southeast Asian economies continue to invest in chemicals, petrochemicals, refining integration, polymers, specialty materials, and supporting industrial infrastructure. Unlike mature markets dominated primarily by brownfield replacement, Asia Pacific combines modernization requirements with substantial greenfield opportunities. New integrated facilities frequently deploy automation from the initial engineering stage, allowing DCS, supervisory control and data acquisition, and manufacturing execution system platforms to be designed around common data architectures rather than connected through multiple retrofit projects.

India is emerging as an important automation growth environment as refinery and petrochemical operators expand digital transformation initiatives involving AI, advanced analytics, optimization, and integrated process control. In February 2025, a major Indian refining and petrochemical operator announced 2 technology agreements focused on industrial automation and digitalization, illustrating increasing regional demand for sophisticated plant intelligence. China continues to operate one of the world's largest chemical manufacturing ecosystems, while Japan and South Korea maintain technologically advanced process industries with strong demand for reliability and precision. The combination of new capacity and digital modernization is expected to keep Asia Pacific's growth above the global 7.03% CAGR during the 2026-2035 forecast period.

Middle East & Africa

The Middle East & Africa is estimated to hold approximately 11% market share, with demand concentrated in major hydrocarbon-processing economies and emerging industrial centers. Saudi Arabia, the United Arab Emirates, Qatar, and other Gulf markets are expanding downstream integration to convert hydrocarbon resources into higher-value chemicals and petrochemicals. Large integrated complexes can contain more than 10 interconnected processing units together with utilities, storage, terminals, and supporting infrastructure, creating substantial requirements for centralized process control and supervisory visibility. DCS technology is particularly important because many facilities are designed for continuous high-volume production, while supervisory control platforms support distributed infrastructure and manufacturing execution systems provide production coordination.

Automation investment in the region is increasingly connected with operational efficiency, remote monitoring, predictive maintenance, and workforce productivity. Facilities located across geographically dispersed industrial areas can benefit from centralized operations centers capable of monitoring multiple assets from 1 location. Digital twins and advanced analytics are also becoming relevant as producers seek to optimize equipment utilization and energy performance. Africa currently represents a smaller portion of regional deployment, but chemical manufacturing, fertilizer production, storage infrastructure, and downstream industrialization provide longer-term opportunities. As integrated petrochemical capacity expands through 2035, demand is expected to shift progressively from basic instrumentation toward connected automation environments incorporating real-time analytics and secure remote operations.

List of Top Automation in Chemicals Petrochemicals Companies

• Emerson Electric - (U.S.)
• Honeywell - (U.S.)
• Siemens - (Germany)
• Yokogawa Electric - (Japan)

Top two Companies Market Share

Emerson Electric: Emerson Electric is estimated to account for approximately 18% of the addressed competitive market, supported by a large process-automation installed base and extensive participation in continuous chemical and petrochemical operations. Its competitive position is strengthened by DCS capabilities, industrial software, measurement technologies, asset monitoring, advanced control, and modernization services. The company's automation strategy increasingly emphasizes software-defined architectures and enterprise operations capabilities designed to connect established operational technology with newer analytics and AI applications. For customers operating automation assets for more than 15 years, migration flexibility is particularly important because modernization can be completed in stages rather than through a single high-risk replacement project.

Honeywell: Honeywell is estimated to hold approximately 16% of the addressed competitive market, supported by extensive deployment across refining, petrochemical, chemical, and other continuous-process industries. The company's position is reinforced by process control, advanced process optimization, industrial software, cybersecurity, production management, and automation lifecycle capabilities. Honeywell has increased its emphasis on AI-assisted operations and automation as industrial customers pursue more autonomous plants. In 2025, its automation activities included strategic collaboration with a major Indian refinery and petrochemical operator, demonstrating the importance of partnerships that combine process-domain knowledge with digital technology. Together, the 2 leading companies are estimated to represent approximately 34% of the addressed market.

Investment Analysis

Investment in automation for chemicals and petrochemicals is increasingly directed toward brownfield modernization, industrial AI, cybersecurity, advanced process control, digital twins, edge infrastructure, and integrated production information. The market's projected 7.03% CAGR between 2026 and 2035 indicates sustained rather than one-time investment as producers progressively modernize installed systems. Automation projects are frequently implemented in phases because chemical facilities may contain equipment installed across 2 or 3 technology generations. Initial spending can focus on obsolete controllers and operator stations, followed by industrial networking, production software, analytics, and enterprise integration. This phased approach reduces shutdown risk while allowing companies to spread modernization across multiple capital cycles. Investment priorities are also moving toward solutions capable of improving existing assets rather than requiring complete replacement, particularly when installed control systems have remaining useful operating life.

Greenfield investment creates a different opportunity because new chemical and petrochemical complexes can integrate automation architecture during engineering and construction. Asia Pacific and the Middle East are especially important because new integrated processing projects can incorporate DCS, supervisory control and data acquisition, manufacturing execution system platforms, cybersecurity, and advanced analytics from the initial design stage. A large integrated complex can contain more than 100,000 instrument and operational data points when field measurements, equipment signals, alarms, calculated variables, and production information are considered collectively. Investors and operators increasingly view the data architecture surrounding these points as a strategic asset. As a result, spending is expanding beyond control hardware toward contextualization, industrial data management, AI models, predictive applications, simulation, and workforce enablement.

New Product Development

New product development is increasingly focused on software-defined automation, AI-enabled control assistance, open industrial architectures, and easier modernization of existing plants. During 2024-2026, automation suppliers expanded platforms designed to separate software functionality from proprietary hardware dependencies while maintaining deterministic process performance. This transition can allow chemical operators to update selected applications on shorter cycles than the 15-to-25-year lifecycle traditionally associated with control infrastructure. New DCS capabilities increasingly incorporate virtualization, integrated cybersecurity, industrial Ethernet, advanced alarm management, and standardized connectivity. Supervisory control products are adding edge analytics and secure remote monitoring, while manufacturing execution system platforms are incorporating more flexible workflow configuration, production intelligence, and contextualized operational data.

Artificial intelligence is becoming another major product-development area as suppliers embed predictive and generative capabilities into industrial environments. Refinery applications reported in 2026 demonstrated up to 98.5% prediction accuracy for selected yield and quality models, indicating that AI can complement physics-based engineering approaches when trained and validated appropriately. Product development is consequently moving toward hybrid models combining first-principles process knowledge with machine-learning techniques. Suppliers are also designing operator interfaces that reduce the time required to interpret thousands of alarms, measurements, and historical trends. The longer-term direction is toward semi-autonomous systems in which AI recommends actions while deterministic automation retains direct process control, creating a practical pathway between today's operator-led plants and increasingly autonomous facilities expected through 2035.

Five Recent Developments

• April 2026: Honeywell advanced AI-enabled refinery optimization through deployment of hybrid artificial intelligence models for complex process operations, with selected yield and quality prediction models demonstrating accuracy of up to 98.5%. The development highlights a broader shift from conventional monitoring toward predictive automation capable of supporting faster production planning, process optimization, and operational decision-making. For chemicals and petrochemicals, where facilities can operate continuously for more than 8,000 hours annually, higher-quality predictive models can help operators identify process deviations before they translate into significant production losses. The development also illustrates increasing integration between process engineering models, historical plant information, advanced analytics, and automated decision-support environments.
• February 2025: Honeywell and a major Indian refining and petrochemical operator expanded cooperation around industrial automation and digital transformation, with 2 technology-focused agreements announced to support advanced analytics, process optimization, AI-enabled operations, and plant modernization. The initiative demonstrates increasing automation investment across India's refining and petrochemical infrastructure as operators seek stronger integration between existing process-control environments and emerging digital applications. Large integrated facilities can contain thousands of control loops and operate across 24-hour production cycles, making scalable modernization particularly important. The development also reflects a wider Asia Pacific trend in which established plants are adopting advanced software and analytics alongside conventional control-system upgrades.
• November 2024: Emerson Electric strengthened its software-defined automation direction through continued development of next-generation industrial automation architecture designed to improve interoperability between control technologies and software applications. The approach addresses a major chemicals and petrochemicals requirement because installed process-control infrastructure can remain in service for 15 to 25 years, while software innovation occurs on substantially shorter cycles. By separating selected automation functionality from tightly coupled hardware architectures, operators can pursue more incremental modernization. This development supports the industry's transition toward open industrial environments capable of connecting DCS infrastructure, analytics, edge technologies, and enterprise operations without requiring complete replacement of functioning plant assets.
• June 2024: Siemens continued expansion of industrial digitalization capabilities combining automation, industrial software, edge computing, and digital-twin technologies for process-intensive manufacturing environments. Digital twins allow operators to evaluate operating conditions and engineering changes virtually before applying modifications to physical production equipment, reducing implementation risk across facilities that may run 365 days annually. Within chemicals and petrochemicals, the development supports applications ranging from engineering and commissioning to equipment monitoring, process optimization, and workforce training. Increasing interoperability between automation and simulation technologies also creates opportunities to evaluate hundreds of operating variables and alternative scenarios without disturbing live production processes.
• March 2024: Yokogawa Electric continued advancing autonomous-operation technologies and integrated production management capabilities for process industries, emphasizing the transition from industrial automation toward increasingly autonomous industrial operations. The strategy is relevant to chemical and petrochemical facilities where operating teams can supervise thousands of process measurements across multiple production units. Autonomous technologies are being developed to support anomaly detection, operational guidance, optimization, and coordinated decision-making while established control systems continue handling deterministic process functions. With the market projected to expand at 7.03% CAGR from 2026 to 2035, technologies that reduce manual workload while preserving process reliability are expected to gain increasing strategic importance.

Report Coverage

The automation in chemicals petrochemicals market report covers the industry across product type, application, regional demand, technology development, competitive activity, investment patterns, and automation modernization trends over the 2026-2035 forecast period. Product analysis is limited to Distributed control system (DCS), Supervisory control and data acquisition, and Manufacturing execution system, while application analysis covers Chemicals and Petrochemicals. DCS is estimated to represent approximately 45% of market deployment, supervisory control and data acquisition approximately 30%, and manufacturing execution system approximately 25%. By application, petrochemicals are estimated to account for approximately 58% of demand compared with approximately 42% for chemicals. The coverage evaluates how continuous-process requirements, industrial AI, advanced process control, cybersecurity, digital twins, edge computing, interoperability, and production-management integration are changing automation requirements across facilities operating as much as 24 hours per day and 365 days per year.

Regional coverage evaluates North America, Europe, Asia Pacific, and the Middle East & Africa, including the different modernization and greenfield investment conditions influencing automation adoption. North America is estimated at approximately 34% market share, Asia Pacific approximately 31%, Europe approximately 24%, and the Middle East & Africa approximately 11%. Asia Pacific is projected to expand at approximately 8.5% annually, exceeding the overall 7.03% CAGR forecast for 2026-2035 as new chemical and petrochemical capacity is combined with modernization of established industrial assets. Competitive coverage focuses exclusively on Emerson Electric, Honeywell, Siemens, and Yokogawa Electric and examines their positioning across process control, supervisory automation, manufacturing operations, industrial software, AI-assisted optimization, digitalization, and lifecycle modernization. The analysis also considers automation lifecycles extending approximately 15 to 25 years, which make compatibility, phased migration, secure connectivity, and long-term engineering support important purchasing criteria.