Artificial intelligence is moving from experimental projects toward practical industrial applications, according to the latest findings from Rockwell Automation’s 2026 State of Smart Manufacturing research.

The report highlights the growing importance of artificial intelligence, digital transformation and connected manufacturing technologies. Manufacturers are increasingly treating AI as a strategic technology that can help improve productivity, operational efficiency, quality and decision-making.

One of the most important developments is the rapid expansion of AI-augmented manufacturing operations. Companies are increasingly exploring AI applications for predictive maintenance, production optimization, quality inspection, process monitoring and industrial data analysis.

This trend is highly relevant to the PLC and DCS industries because artificial intelligence does not simply replace traditional industrial control systems. Instead, AI is increasingly being integrated with existing automation architectures.

A typical smart manufacturing system may include field sensors at the equipment level, PLCs or DCS controllers for real-time control, industrial networks for data communication, SCADA and HMI systems for visualization, and higher-level software platforms for manufacturing analysis and optimization.

Reliable automation infrastructure is therefore becoming even more important. AI applications require accurate and consistent production data. Sensors must collect reliable information, PLCs and DCS systems must process operational signals, and industrial networks must transfer data efficiently and securely.

For PLC engineers and system integrators, this creates a major opportunity to connect existing automation assets with new digital technologies. Older industrial control systems can often become valuable sources of operational data when information is properly collected, standardized and securely integrated with modern software platforms.

The development is also highly relevant to process industries using DCS technology, including oil and gas, chemicals, power generation and pharmaceuticals. AI can support predictive maintenance, energy optimization, abnormal-condition detection and process analysis while the underlying DCS continues to perform deterministic process control.

Another important trend is the move from isolated automation projects toward connected smart factories. Manufacturers increasingly want production equipment, robots, sensors, controllers and enterprise software to exchange information across the entire production environment.

The future of industrial automation is therefore unlikely to depend on AI alone. Instead, successful smart manufacturing architectures will combine PLCs, DCS systems, robotics, sensors, industrial communication, edge computing, cloud platforms and artificial intelligence.

As manufacturers continue investing in digital transformation, the ability to integrate existing automation systems with intelligent technologies will become an increasingly important competitive advantage.

For the global PLC, DCS and industrial automation market, the rapid development of AI represents not only a technological change but also a new opportunity to modernize existing factories and build more flexible, connected and intelligent production systems.