What's Happening?
The automation industry is experiencing a shift towards integrating IT best practices into operational technology (OT) due to a shortage of skilled workers and volatile supply chains. This trend is leading to the adoption of generative AI, such as Industrial Copilot for Engineering, which provides intelligent code assistance and knowledge preservation. This integration aims to bridge the skills gap as experienced programmers retire. Additionally, standardized data models like OPC-UA and MQTT are being adopted to ensure compatibility and interoperability across systems, simplifying control structures and enhancing IIoT functionality.
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Why It's Important?
The integration of AI and standardized data models in industrial controller programming is crucial for addressing the skills gap and improving system interoperability. As experienced programmers retire, AI tools like Industrial Copilot can help preserve knowledge and assist new engineers, ensuring continuity in automation processes. The adoption of standardized data models facilitates seamless data processing and analysis, enhancing the efficiency of IIoT systems. This shift is expected to improve performance, support ongoing system updates, and drive innovation in automation engineering.
What's Next?
Organizations may need to plan phased migrations to newer controllers to integrate modern engineering tools and improve system performance. Knowledge transfer sessions and updated training materials will be essential to equip new engineers with the necessary skills. As AI tools become more prevalent, companies might invest in further developing these technologies to enhance automation processes and address the skills gap.
