Programmable Logic Controllers (PLCs) have been the backbone of industrial automation for decades. They are trusted because they provide deterministic control, high reliability, rugged hardware, and long operating lifecycles. But the role of the PLC is changing.
Modern factories increasingly expect controllers to do more than execute ladder logic. PLCs are becoming part of connected industrial architectures that combine edge computing, artificial intelligence, cloud platforms, digital twins, open communication standards, advanced cybersecurity, and software-based deployment.
Understanding current programmable logic controllers trends is important for machine builders, automation engineers, maintenance teams, and manufacturers planning new equipment or modernization projects.
The PLC is unlikely to disappear. Instead, it is evolving from an isolated machine controller into a more connected, software-driven, data-aware industrial control platform.
Key PLC Technology Trends
1. Software-Defined Automation Is Growing
Traditional PLC systems closely tie automation software to specific controller hardware.
Software-defined automation is beginning to change this model.
The concept separates more of the control application from dedicated hardware so automation software can be deployed, managed, and updated with greater flexibility.
Industrial suppliers are actively developing this approach. Siemens, for example, offers the SIMATIC S7-1500V virtual PLC, which runs through its Industrial Edge environment. Schneider Electric is also promoting open, software-defined automation architectures designed to reduce dependence on fixed proprietary hardware.
Potential benefits include:
- Easier application deployment
- Centralized management
- Greater hardware flexibility
- Faster system updates
- Better integration with IT workflows
- Improved application portability
Traditional hardware PLCs will remain important, particularly where ruggedness and deterministic control are essential. However, virtual and software-based controllers are likely to become more common in suitable industrial applications.
2. Virtual PLCs Will Expand
A virtual PLC performs control functions in software rather than depending entirely on a dedicated physical PLC CPU.
Virtualization can allow industrial users to run control workloads on industrial computers or edge infrastructure.
This can provide advantages such as:
- Central controller deployment
- Simplified backups
- Easier version management
- Flexible scaling
- Integration with edge applications
- Reduced dependence on individual controller hardware
Siemens describes its S7-1500V as a hardware-independent virtual controller that can be centrally managed through Industrial Edge.
This does not mean every physical PLC will be replaced.
Dedicated hardware controllers remain valuable for many machines because of their predictable behavior, environmental durability, safety certification, and long service life.
The future is more likely to include both traditional and virtual PLC architectures.
3. Artificial Intelligence Will Support PLC Engineering
One of the most important programmable logic controllers trends is the increasing use of artificial intelligence in automation engineering.
AI tools can assist engineers with tasks such as:
- Generating PLC code
- Explaining existing logic
- Creating HMI screens
- Detecting programming errors
- Building documentation
- Troubleshooting
- Optimizing machine control
In 2026, Siemens announced an engineering agent integrated with TIA Portal that can generate PLC code, create HMI visualizations, configure devices, and check its own work.
This shows how AI is moving from general-purpose engineering assistance toward automation-specific workflows.
Engineers will still need to validate generated logic, particularly where equipment safety, machine behavior, quality, or regulatory requirements are involved.
AI should be treated as an engineering tool rather than an automatic replacement for qualified automation professionals.
4. AI Will Move Closer to Machine Control
AI is also beginning to move from engineering assistance into machine optimization.
Traditional PLC control is usually based on explicitly programmed rules.
Future systems may increasingly combine deterministic PLC logic with machine-learning models for applications such as:
- Process optimization
- Adaptive machine control
- Energy optimization
- Quality prediction
- Motion optimization
- Anomaly detection
Siemens AI Motion, for example, uses reinforcement learning with a digital twin to develop control strategies that can be deployed as PLC code or run through an Industrial Edge environment.
This represents an important change.
Instead of engineers manually tuning every control strategy, AI may help determine better control parameters based on machine objectives such as throughput, quality, energy consumption, or mechanical wear.
5. Edge Computing Will Become More Important
Factories generate large volumes of data from PLCs, sensors, drives, robots, cameras, and production equipment.
Sending all data directly to the cloud is not always practical.
Industrial edge computing processes data closer to the machine.
Typical edge applications include:
- Predictive maintenance
- Machine vision
- Quality inspection
- Local analytics
- Production optimization
- Protocol conversion
- Data preprocessing
- AI inference
Edge computing complements rather than replaces the PLC.
The PLC can continue handling deterministic machine control while the edge layer performs computing-intensive analysis.
This architecture allows automation systems to combine fast local control with advanced analytics.
6. PLC, Edge, and Cloud Architectures Will Work Together
Future automation systems are increasingly likely to use multiple computing layers.
A simplified architecture may look like:
- Sensors
- PLC
- Industrial Edge
- Plant Systems
- Cloud
Each layer serves a different purpose.
| Layer | Typical Role |
|---|---|
| Sensors/devices | Generate field data |
| PLC | Real-time machine control |
| Edge | Local analytics and AI |
| MES/SCADA | Production supervision |
| Cloud | Enterprise analytics and large-scale services |
Not every factory requires every layer.
The architecture should depend on latency, security, availability, business requirements, and the amount of data being processed.
The important trend is that PLCs are increasingly becoming part of a broader industrial computing environment.
7. OPC UA Will Continue Expanding Interoperability
One challenge in automation is that industrial devices from different manufacturers often use different communication technologies.
OPC UA provides a vendor-independent framework for secure industrial information exchange.
The OPC Foundation describes OPC UA as a platform-independent architecture that can operate from embedded systems and PLCs through enterprise and cloud environments.
Its capabilities include:
- Structured information models
- Authentication
- Encryption
- Auditing
- Secure communication
- Device-to-enterprise integration
OPC UA is also increasingly connected with digital twins, cloud applications, AI, and industrial data ecosystems.
This makes interoperability an important part of future PLC design.
8. PLC Data Will Become More Semantic
Traditional PLC applications often expose data as individual tags.
For example:
Motor_01_Speed
Motor_01_Current
Motor_01_Status
The next step is to provide more context about what the data means.
Semantic information models make it easier for external applications to understand machines without building large amounts of custom integration logic.
The OPC Foundation and PLCopen maintain an OPC UA information model for controllers based on IEC 61131-3.
As factories become more connected, machine data will increasingly need standardized meaning, not just connectivity.
This can improve integration with:
- MES
- Digital twins
- AI systems
- Maintenance platforms
- Cloud applications
- Industrial data spaces
9. Digital Twins Will Influence PLC Engineering
A digital twin is a digital representation of a physical machine, process, or system.
Digital twins can support PLC projects by allowing engineers to test automation behavior before physical equipment is fully available.
Potential applications include:
- Virtual commissioning
- Sequence testing
- Motion simulation
- Operator training
- Fault simulation
- Control optimization
- AI training
This can reduce commissioning risk and help engineers detect problems earlier.
Digital twins are particularly useful in complex automation systems where physical testing is expensive or difficult.
Future PLC engineering environments are likely to integrate simulation and digital-twin workflows more closely with control software development.
10. IT and OT Engineering Will Continue to Converge
PLC engineering has traditionally belonged to Operational Technology (OT).
Modern automation increasingly uses practices that originated in Information Technology (IT), including:
- Version control
- Software repositories
- Automated testing
- Central deployment
- Containerization
- DevOps-style workflows
- APIs
Siemens has been expanding its Simatic AX engineering environment with IT-style development workflows while also supporting familiar PLC programming approaches.
This convergence can improve collaboration between software engineers and automation engineers.
However, industrial systems have different requirements from normal enterprise software.
Control systems must still prioritize deterministic operation, availability, safety, and controlled changes.
11. PLC Programming Standards Will Continue Evolving
IEC 61131-3 remains one of the key standards for PLC programming.
The 2025 edition defines Structured Text, Ladder Diagram, Function Block Diagram, and Sequential Function Chart concepts for programmable controllers.
The updated edition also added features such as UTF-8 strings and related functions.
Standardization remains important because industrial automation systems often operate for decades.
Future programming environments may offer more modern development tools, but IEC 61131-3 languages will continue to play a major role in industrial automation.
12. Cybersecurity Will Become a Core PLC Requirement
As PLC systems become more connected, cybersecurity becomes increasingly important.
Historically, many industrial controllers operated in relatively isolated networks.
Modern PLCs may communicate with:
- Plant networks
- Edge platforms
- Remote service systems
- Cloud applications
- MES
- Enterprise systems
This expands the potential attack surface.
Future PLC architectures will increasingly require features such as:
- Authentication
- Encryption
- Secure communication
- Certificate management
- Role-based access
- Security logging
- Controlled software updates
- Network segmentation
The objective is not simply to connect more equipment but to connect it securely.
13. Open Automation Will Increase Vendor Flexibility
Industrial automation has traditionally been highly vendor-specific.
Controller software, I/O systems, engineering environments, and communication architectures are often tightly connected to one supplier.
Open and software-defined automation initiatives are challenging this model.
The objective is to make automation applications more portable and reusable across compatible platforms.
Potential benefits include:
- Reduced vendor lock-in
- Greater hardware choice
- Easier modernization
- Improved software reuse
- More flexible system integration
This transition will take time because industrial users prioritize reliability and long-term support.
However, hardware-independent automation is becoming an important industry direction.
14. Predictive Maintenance Will Use More PLC Data
PLCs already collect valuable operating information such as:
- Motor runtime
- Cycle count
- Temperature
- Pressure
- Current
- Alarm history
- Machine state
Historically, much of this information remained inside the PLC or HMI.
Edge analytics and AI make it easier to use this data for predictive maintenance.
Instead of waiting for a component to fail, systems can identify patterns indicating developing problems.
Examples include:
- Increasing motor current
- Higher cycle time
- Repeated sensor errors
- Abnormal vibration
- Temperature increases
- More frequent drive faults
The PLC can therefore become an important data source for condition-based maintenance systems.
Key PLC Technology Trends at a Glance
| Trend | Expected Impact |
|---|---|
| Software-defined automation | More flexible control deployment |
| Virtual PLCs | Reduced dependence on dedicated hardware |
| AI engineering assistants | Faster programming and diagnostics |
| AI-based control | Adaptive optimization |
| Industrial edge | Local analytics and AI processing |
| OPC UA | Greater interoperability |
| Semantic data | Easier system integration |
| Digital twins | Better virtual commissioning |
| IT/OT convergence | Modern engineering workflows |
| Cybersecurity | Stronger protection for connected systems |
| Open automation | Greater application portability |
| Predictive maintenance | Better use of machine data |
What Should Automation Engineers Learn Next?
Engineers preparing for future PLC systems should expand beyond traditional ladder programming.
Useful areas include:
- Structured Text
- OPC UA
- Industrial Ethernet
- Industrial cybersecurity
- Edge computing
- Python basics
- Data analytics
- AI fundamentals
- Digital twins
- Version control
- Industrial networking
Traditional PLC skills will remain important, but future automation engineers will increasingly combine control engineering with software, networking, data, and cybersecurity knowledge.
Conclusion
The future of the PLC is not simply a faster processor or a larger memory module.
The most important programmable logic controllers trends involve the PLC becoming part of a wider software and data ecosystem.
Software-defined automation, virtual PLCs, AI-assisted engineering, edge computing, OPC UA, digital twins, cybersecurity, and IT/OT convergence are changing how industrial control systems are designed and maintained.
Physical PLCs will continue to play an important role because industrial applications require deterministic control, high availability, safety, and long operating lifecycles.
However, the boundaries between PLCs, industrial computers, edge platforms, and software systems are becoming less rigid.
For manufacturers and automation engineers, the best approach is not to replace proven PLC technology simply because a new trend appears. Instead, organizations should understand where new technologies provide measurable improvements in flexibility, engineering productivity, interoperability, reliability, and production performance.