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AI or PLC engineers: who holds the key in the industrial control industry?

August 05,2025

Introduction:

Once exposed to artificial intelligence, it's like opening Pandora's box—the integration of industrial automation and AI is gradually moving towards deeper, practical applications.

Since ChatGPT became a global sensation, generative AI has become increasingly prominent not only in social media and literary creation, but is also quietly reshaping every corner of the industrial world. This deep integration goes beyond simply increasing automation levels; it is also subverting traditional production models and business logic.

Generative AI is becoming a key driver of rapid growth in industrial productivity, and its integration with programmable logic controllers (PLCs) is opening up a new path for industrial digital transformation. In this era centered on intelligence, companies are focusing not only on the operation of equipment on the shop floor but also on recognizing the unique value of AI in industrial control.

For a long time, PLCs, as the core control unit of industrial automation, have relied on preset logic and fixed programs to achieve precise control of various devices. However, their flexibility and adaptability remain limited. The introduction of AI has enabled PLCs to achieve a new level of intelligence and processing efficiency.

In fact, while most people are still marveling at the power of AI, industrial giants have already pioneered impressive results.

Siemens officially launched Siemens Industrial Copilot, the first generative AI tool for industrial environments. Deeply integrated with the TIA Portal, this product quickly generates basic virtualization tasks and code for PLC engineering teams and automates repetitive programming tasks, significantly reducing the burden on engineers while also reducing design errors, shortening development cycles, and improving productivity and quality.

Furthermore, B&R has partnered with Microsoft to integrate generative AI into its Automation Studio platform, allowing developers to directly generate, optimize, and annotate code using natural language. On the other hand, One has launched the TwinCAT Chat client, which leverages a large language model (LLM) to automate code creation, function block generation, code refactoring, and documentation, improving development efficiency while reducing manual errors.

In the domestic market, automation manufacturers are also actively exploring the industrial application of AI and have made substantial progress.

On April 8th, The Technology launched SCADA version 6.5 at its spring press conference. The newly added AI programming assistant, based on a VBS programming model, enables rapid code generation and functionality expansion. The AI Smart Question function integrates extensive product documentation and application experience, providing users with instant engineering answers and construction guidance.

In the same month, One Technology showcased China's first intelligent controller with an embedded AI model at the Chengdu International Industrial Expo. This product directly converts natural language commands into robot motion control instructions, enabling semantic-based real-time motion control.

Today, PLC manufacturers are embracing AI not simply to cater to the trend of smart manufacturing, but to shape a new competitive landscape. In the past, the market competed on product specifications and price, but now prioritizes brand ecosystems, service capabilities, and system integration advantages. For example, Siemens, leveraging software platforms such as the TIA Portal, not only provides advanced tools for PLC programming and monitoring but also integrates them with the Industrial Internet and digital management to achieve intelligent production and data-driven decision-making. The integration of AI further lowers the barrier to entry, improves production efficiency, and provides customers with customized, intelligent solutions.

AI-driven changes in PLC programming are already underway in the industrial sector. 

However, this has also raised a concern among engineers: Will AI replace PLC engineers?

Realistically, this concern is unfounded. 

First, PLC programming involves multidisciplinary knowledge, including electrical, automation, and programming. While AI can learn and emulate these skills, human judgment and experience remain irreplaceable for complex, non-standardized tasks.

Second, the responsibilities of electrical and automation engineers extend far beyond programming. They also encompass equipment installation, commissioning, maintenance, and troubleshooting, all of which require practical skills and field experience, which AI currently lacks the ability to perform.

Finally, AI's optimal position in industry is as an assistant to engineers, not a replacement. When repetitive programming tasks are handled by AI, engineers can focus more on system optimization and process improvement, thereby improving production quality and efficiency. This not only enhances their work creativity but also further highlights their value.

Thus, the relationship between AI and PLC engineers is more one of mutual success rather than a zero-sum game. Interdisciplinary professionals who master both AI technology and automation knowledge will be more competitive in the future industrial control industry. Actively embracing AI and learning to harness it are the keys to truly seizing the initiative in the future.

Conclusion:
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