Why is reliable industrial data essential for AI?

AI depends on consistent, trustworthy data to recognize patterns, support decisions, and deliver useful results. zenon connects, structures, and contextualizes operational data to create AI-ready OT data for industrial applications.

How can existing OT data be made usable for AI?

OT data becomes usable for AI when it is connected, contextualized, and accessible through open interfaces. zenon helps manufacturers make OT data usable for AI by providing a consistent data platform connecting existing automation systems and providing contextualized industrial data for AI without requiring a complete infrastructure replacement.

What role does human supervision play when using industrial AI agents?

Human supervision ensures that AI agents in industrial automation operate within safe and clearly defined boundaries. Engineers and operators remain responsible for validating outcomes, setting limits, and maintaining trust in the system.

How can AI improve industrial energy management?

AI can improve industrial energy management by learning from plant data, identifying patterns, and supporting decisions that reduce peaks and improve efficiency. zenon provides the connected environment needed to support these industrial artificial intelligence optimization workflows.

What is closed-loop AI in industrial automation?

Closed-loop AI in industrial automation means the system observes data, analyzes conditions, takes action, and learns from the result. zenon supports this approach by connecting industrial data, service execution, and ongoing feedback for agentic AI industrial automation.

Which engineering tasks could be supported or automated by AI?

AI can support tasks such as knowledge retrieval, documentation, project assistance, configuration workflows, and access to engineering information. This helps engineers reduce repetitive work and focus on higher-value system design.

Does an industrial company need to replace its existing automation infrastructure before using AI?

No. AI can be introduced step by step on top of existing infrastructure. zenon connects legacy and modern systems, allowing manufacturers to build AI-ready OT data and introduce AI capabilities without requiring a complete automation replacement.

What role does zenon play in industrial AI?

zenon provides the connectivity, context, and secure access needed to make OT data usable for AI. It connects industrial systems, provides contextualized industrial data for AI, and supports AI applications, engineering workflows, and AI-supported services close to the industrial process.

AI-Powered Industrial Automation with zenon

zenon supports efforts to make AI work securely and reliably in industrial environments. It connects existing industrial systems, exposes data through open interfaces, and provides contextualized industrial data for AI while ensuring engineers and operators maintain control.

It gives manufacturers a governed foundation for deploying AI and turning intelligent automation into measurable operational improvements. Supported by engineering expertise, service execution, and IIoT-based feedback loops, zenon helps manufacturers create safer, smarter, and more efficient operations.

These companies use zenon

Why industrial AI starts with reliable data

Industrial AI depends on reliable, structured, and contextualized data. zenon creates this foundation by connecting brownfield and greenfield environments, homogenizing and preprocessing data, and providing a centralized information layer across machines, sensors, and software systems.
This gives manufacturers a consistent source of operational information for analytics, decision support, and scalable optimization.

Build industrial AI on a rock-solid data foundation. With zenon, manufacturers can:

Adopt industrial artificial intelligence faster - replace fragmented data silos with one consistent source of operational information.
Enable AI applications - provide reliable inputs for analytics, decision support, and AI agents in industrial automation.
Scale optimization - use harmonized data across assets and sites to provide consistent contextualized industrial data for AI.
Simplify engineering - work with standardized and contextualized data flows.

Why do manufacturing engineering teams need AI tools now?

Manufacturing engineering teams, especially in life sciences, food and beverage, and machine building, face three pressures at once: a shortage of skilled automation and control engineers; shorter project and commissioning timelines; and increasingly complex production systems. AI-assisted automation engineering helps address these pressures by automating repetitive engineering tasks, making OT data usable for AI, and freeing engineers to focus on high-value system design work.

Three pressures on manufacturing engineering teams

Talent scarcity: Experienced control engineers, automation specialists, and validation experts are hard to find. Demand continues to outpace the available workforce, especially for skillsets that combine software knowledge with regulated industry requirements.
Shrinking timelines: Machine builders face compressed delivery schedules for custom equipment, while life sciences and food and beverage manufacturers face pressure to bring new lines online faster without compromising compliance or food safety.
Rising complexity: Modern production systems involve more integration between PLCs, SCADA, MES, and quality systems, more regulatory documentation (GMP, FDA, HACCP), and more customization per line or per client than ever before. At the same time, organizations need to turn operational technology into AI-ready OT data that AI tools can actually use in an industrial context.

Empower your engineers to move from repetitive tasks to strategic system design. AI-powered tools reduce the time engineers spend on repetitive, low-value work such as writing boilerplate PLC code, generating routine documentation, or running manual validation checks. At the same time, contextualized industrial data for AI provides the foundation for AI tools to work with meaningful information from the production environment.

By making OT data usable for AI, manufacturers can connect AI capabilities more effectively with existing automation systems and engineering workflows. This frees engineers to focus on the work only humans can do well: machine and line architecture; process design and enhancement; solving the technical and compliance challenges unique to regulated manufacturing environments.

This approach doesn't replace engineers. It reallocates their time toward high-value work that only humans can do, such as designing safe, compliant, and efficient production systems. With AI-ready OT data, AI-assisted automation engineering, and contextualized industrial data for AI, manufacturers can reduce repetitive engineering work while giving their teams the information and tools they need to design smarter systems.

How zenon makes OT data usable for AI

zenon helps manufacturers make OT data usable for AI by combining connectivity, context, and open access.. Through standard interfaces and APIs such as Python, GraphQL, and REST, industrial data can be retrieved and integrated into customer-specific AI agents and agentic AI workflows for intelligent industrial systems. Existing automation infrastructure can remain in place while new AI capabilities are added step by step. This reduces risk and accelerates time to value.

AI support for engineering teams in manufacturing

The zenon Engineering Studio extends the value of industrial AI beyond runtime optimization and into project work. zenon supports engineers with AI-assisted access to platform knowledge, helping teams find answers faster, reduce repetitive effort, and move more efficiently from concept to implementation.

Engineering tasks such as guided configuration, knowledge retrieval, and structured project support can be accelerated while engineers remain in control of review and execution.

The zenon Engineering Assistant is an AI-powered knowledge assistant that helps engineers find answers about the zenon software platform faster. Instead of searching through documentation, you can ask questions in natural language and receive contextual answers based on official zenon sources. It combines official zenon documentation, COPA-DATA knowledge base articles, and transcripts from zenon Academy training courses. This makes it ideal for engineering, troubleshooting, configuration, automation projects, and technical support in industrial automation, SCADA, HMI, and energy automation.

The assistant complements other COPA-DATA resources:

zenon Online Help – comprehensive product documentation
Self Service Portal – tickets, knowledge base, and community forum
zenon Academy – online courses and training content

Instead of searching through documentation, you can ask questions in natural language and receive contextual answers based on official zenon sources.

Bringing AI into operation

zenon will enable AI to operate close to industrial processes. Manufacturing companies can run AI agents that work in centralized environments as well as on Edge-based industrial PCs. This paves a realistic route for agentic AI to support and add value to industrial automation at scale. AI-supported services can observe conditions, process data, trigger actions, and support continuous improvement inside operational workflows within a runtime environment. You maintain human control by ensuring a human in the loop at all critical decision points.

AI-powered industrial event insights

Turn your plant data into clear, actionable answers. Operators ask questions in natural language directly from the dashboard and get responses grounded in their own industrial data, not a generic model. AI in industrial automation starts with AI-ready OT data and this service makes it usable where it matters most: in existing operational workflows.

How it works

Event and alarm data from your PLCs is retrieved through zenon, prepared for AI, and stored in a knowledge base. A Retrieval-Augmented Generation (RAG) pipeline retrieves the relevant information before every answer is generated, keeping responses grounded in your actual plant data and preventing hallucinations. By delivering contextualized industrial data for AI, zenon helps manufacturers make OT data usable for AI without changing their automation infrastructure. All models run locally, so your data never leaves your infrastructure.

What users get

Summaries, charts, and reports generated from live event data, ready to save and reuse for daily or weekly monitoring. Need more depth? Drill down from any summary to the original events. In this way, industrial automation AI tools can support decisions while keeping your existing setup in place.
Why it matters
• Faster problem diagnosis and quicker decisions
• Traceable answers engineers can verify against source data
• Routine monitoring and reporting without heavy manual work
• Existing automation infrastructure stays untouched

Built on proven technology

The zenon Service Engine brings AI close to the industrial process, with Python-based execution in zenon Logic and flexible Edge or cloud deployment, so AI agents in industrial automation run exactly where you need them. This is the foundation for agentic AI for intelligent industrial systems: applications and agents that operate within your operational environment.

What's next

We're continuously improving real-time extraction, API integration, and long-range analysis. On the roadmap: human-supervised automation for process control and AI-assisted automation engineering with AI assistants that help engineers plan and execute projects.

Operator assistance

An AI-powered assistant helps operators navigate and manage complex industrial production processes using natural language. On a flexible assembly and filling line, operators can quickly access relevant system screens, interpret machine states and alarms, and troubleshoot issues. By making engineering knowledge readily accessible, the assistant enables operators to resolve problems faster, work with greater confidence, and adapt more efficiently to changing production requirements. This is just one product vision for zenon that COPA-DATA has on its future roadmap. It could offer a range of potential benefits.

How it works

Operator assistance
Empower operators with AI-assisted access to machine and process information. The AI would understand the connected zenon project and then help operators to navigate, monitor, and operate the industrial systems using natural language – enabling the operator to understand and operate complex industrial systems more effectively.

Faster orientation
Operators could ask questions about a machine or production process and immediately access the relevant screens and information. This would be particularly useful for new or less-experienced operators who may not yet know where specific information or functions are located.

Clear overview

Gain more context about what is happening
The AI could look beyond the currently visible screen and connect information from the wider system. It could identify relevant alarms, process values, and machine states to explain what is happening and why a production process may have stopped.

Guided troubleshooting
When an issue occurs, the AI could help to identify the cause and guide the operator through the next steps – from understanding an alarm to restoring the machine once the physical issue has been resolved.

Coordination and management assistance for the zenon ecosystem

IIoT Services turn connectivity into operational value by making industrial data available across systems, departments, and applications. zenon supports this with broad integration capabilities and a structured information layer that helps companies move from data collection to actionable intelligence. This is especially important for closed-loop AI in industrial automation. COPA-DATA’s vision is to enable manufacturing companies to use AI-supported services to observe, analyze, act, and continuously improve industrial processes guided and controlled by zenon. . This will create a strong foundation for AI agents in industrial automation. Let’s look at what could be possible in this scenario.

Coordination & management assistance

Manage industrial systems more efficiently with AI-powered assistance. Connected to IoT Services, the AI provides a central overview of information and actions available in the IIoT-Services such as managing your zenon installations, centralized access permissions, live and archival data and dashboard visualizations.

How it works

Understand your system at a glance
In a large-scale, distributed zenon device management, instead of getting information manually or retrieving it programmatically, simply ask for the information you need. The AI consolidates system data into a clear overview, helping you quickly understand what is running where and identify relevant changes or updates.

Deploy with natural language
Projects could be deployed to connected devices using simple natural-language commands. Existing deployments would be detected automatically, while scheduled deployments could be aligned with defined maintenance windows to minimize operational disruption.

Clear overview

Create better dashboards
Show and analyze important KPIs and relevant data about your machines in a visually pleasing dashboard without the need to manually compile it. By specifying content and style using natural language, the AI could be prompted to either create a new dashboard or modify existing ones. This would make it even easier to turn existing system data into actionable operational information.

Built on IoT Services
zenon IoT Services provides the technical foundation for connected devices, data, and deployments. As part of COPA-DATA’s future roadmap for the zenon software platform, the zenon Coordination & Management Assistance would bring these capabilities together through an intuitive AI interface.

From static automation to adaptive industrial intelligence in manufacturing

Collecting data is only the first step. Real industrial value comes from data that is put into context, analyzed, and fed back into engineering or operational decisions. On the zenon software platform, zenon IIoT Services, zenon Service Engine, and zenon Engineering Studio all work together to create a connected path from industrial data to action. This supports measurable use cases – such as energy optimization, decision support, engineering assistance – and, in the next steps, AI in industrial automation more broadly.

Solutions from COPA-DATA

With zenon, manufacturing companies can connect existing automation systems, and make OT data usable for industrial AI – laying the groundwork to be able to implement agentic AI workflows for intelligent industrial systems in a controlled and scalable way. This will support engineering, service execution, IIoT integration, and long-term optimization on one platform. zenon already helps industrial organizations to introduce AI in industrial automation without replacing their current infrastructure. zenon’s open interfaces, compatibility, and structured data foundation make it a practical choice for companies that want to combine AI with industrial automation step by step.

Ready to see zenon + AI in your plant? We can help design a proof of concept that indexes your event history, wires up a secure retrieval pipeline, and demos plain language querying and operator workflows in your own environment.
Contact COPA-DATA today to talk through what this could look like for your plant.

FAQs

AI depends on consistent, trustworthy data to recognize patterns, support decisions, and deliver useful results. zenon connects, structures, and contextualizes operational data to create AI-ready OT data for industrial applications.
Human supervision ensures that AI agents in industrial automation operate within safe and clearly defined boundaries. Engineers and operators remain responsible for validating outcomes, setting limits, and maintaining trust in the system.
Closed-loop AI in industrial automation means the system observes data, analyzes conditions, takes action, and learns from the result. zenon supports this approach by connecting industrial data, service execution, and ongoing feedback for agentic AI industrial automation.
No. AI can be introduced step by step on top of existing infrastructure. zenon connects legacy and modern systems, allowing manufacturers to build AI-ready OT data and introduce AI capabilities without requiring a complete automation replacement.

OT data becomes usable for AI when it is connected, contextualized, and accessible through open interfaces. zenon helps manufacturers make OT data usable for AI by providing a consistent data platform connecting existing automation systems and providing contextualized industrial data for AI without requiring a complete infrastructure replacement.
AI can improve industrial energy management by learning from plant data, identifying patterns, and supporting decisions that reduce peaks and improve efficiency. zenon provides the connected environment needed to support these industrial artificial intelligence optimization workflows.
AI can support tasks such as knowledge retrieval, documentation, project assistance, configuration workflows, and access to engineering information. This helps engineers reduce repetitive work and focus on higher-value system design.
zenon provides the connectivity, context, and secure access needed to make OT data usable for AI. It connects industrial systems, provides contextualized industrial data for AI, and supports AI applications, engineering workflows, and AI-supported services close to the industrial process.

I'm COPA-DATA's AI Assistant and happy to help with general info. Got any questions?