How the first AI-generated control cabinet was created

Control cabinet engineering is one of the most demanding disciplines in electrical design. Design, layout, wiring, labelling, and documentation are closely interlinked. In addition, manufacturing data must be generated for wires and harnesses, mounting plates, and cabinet enclosures. In practice, these steps are often executed separately.
The use of artificial intelligence now enables these steps to be systematically integrated and, based on existing digital schematics, to generate a production-ready control cabinet layout. The AI analyses the schematic data and uses it as a basis to automate and link subsequent design steps. This allows control cabinet design to be systematically automated for the first time, bringing multiple advantages.

The role of the electrical designer

Even with a high degree of automation, the electrical designer remains a central figure. The AI does not take on technical responsibility but supports the implementation of defined design logics. The designer defines the framework within which the AI operates and reviews the generated results.

For project-specific requirements, custom solutions, or customer-specific standards, human expertise remains indispensable. Normative requirements, company regulations, or individual preferences cannot be fully automated. The designer checks the AI-generated proposals, makes targeted adjustments, and releases the final layout. Decisions, rules, and standards are stored in the system and made available to the AI in future projects, making experiential knowledge reproducible, consistently applied, and independent of individual users.

How is knowledge integrated and preserved using AI?

The quality of AI-assisted design depends significantly on the integration of corporate and customer-specific knowledge. Users can incorporate their own documents, such as specifications, internal design guidelines, standard interpretations, or manufacturer approvals, into the AI Copilot. This information is available across projects and can be queried, for example, for questions about permissible technical design or the selection of approved components.

The AI’s responses are based exclusively on these stored documents, ensuring experiential knowledge is applied consistently and permanently anchored, while the electrical designer retains full professional responsibility. Corporate collaboration also benefits, as design logics are systematically documented rather than being dependent on individuals, while the expertise of experienced designers remains decisive for the quality and precision of design outcomes.

Major advantages of AI in electrical engineering

1. Speed – Design steps that were previously sequential and manual can now be executed in parallel and automated, significantly reducing engineering lead times while increasing consistency. Inconsistencies between schematic, layout, wiring, and labelling are systematically avoided.
2. Consistent data availability for downstream processes – Material lists, terminal plans, wiring information, and labelling data are generated directly from the engineering model. These data can be passed to manufacturing and documentation systems without manual transfer, eliminating media breaks and reducing coordination effort.
3. Automatic translation of project contents – Individual texts or full documentation can be translated directly within the system into any language, including electrical terminology and project-specific designations. This drastically reduces the effort for multilingual documentation in international projects..
4. Mitigating skilled labour shortages – Less experienced users are supported with structured suggestions, while experienced designers can scale their knowledge. Design quality becomes less dependent on individual resources.

Limitations of AI

• Despite the advantages, AI is not a substitute for engineering responsibility. The quality of results depends on the quality of input data. Incomplete or inconsistent information directly affects design outcomes, so a clean data basis is essential.
• AI also reaches its limits where project-specific decisions, exceptions, or normative interpretations are required. Standards allow for technical judgement, which cannot be fully automated.
• In addition, AI works probabilistically, producing technically plausible and consistent suggestions that must always be reviewed. Without clear boundaries, defined standards, and responsible approvals, formally correct but practically suboptimal solutions may arise. AI’s greatest benefit emerges when embedded in a clearly structured design workflow: it supports, accelerates, and structures processes, but does not make independent decisions.

How the AI-generated control cabinet is shaping the future of electrical engineering

The world’s first AI-generated control cabinet, presented by WSCAD and partners at SPS 2025, marks a fundamental change in electrical engineering. Artificial intelligence enables the integration of complex design processes, consistent use of data, and relief for the electrical designer, while professional responsibility remains with humans. The true potential of AI-assisted electrical engineering lies in combining automated support with engineering expertise.