Digitalization & New Technologies

Prevent Fragmented Responsibilities Around Safety and Cybersecurity

Why Restructuring is Now Strategically Necessary

A future-proof data structure is essential to meet new EU regulations, implement scalable AI, and remain competitive.

According to new regulations, technical documentation is entering the path of digitalization. What does this mean? What are the trends? Piotr Garbela, Sales Manager, Technical Communication and Data Solutions at Etteplan, explains.

Requirements engineering is one of the most important phases in product development. It defines what the product does, who it is intended for, and under what conditions it meets technical, regulatory and user-driven requirements. When requirements engineering fails, the entire project can collapse — which is why quality is critical. With AI-based agents, requirements work can be streamlined, enabling projects to progress faster. AI doesn’t replace experts, but it gives them better tools to succeed.

AI doesn’t change anything on its own but people do. Technology creates value only when it is accepted, trusted, and used every day. Successful projects share one thing in common: keeping people involved in decision-making. The human-in-the-loop principle means that people retain control over key decisions – both in the final solution and during the development process. Human involvement is essential in building trust, ensuring adoption, and ultimately achieving business benefits.

When we talk about modern user experience in the manufacturing industry, it’s not just about a visually appealing interface. It’s about connecting the physical and digital worlds, ensuring systems support machine operation by bringing the right information at the right time. Systems guide our work so that collaboration between humans and machines in complex tasks and demanding environments is seamless, efficient, and safe.

Artificial Intelligence is moving from cloud servers into the devices we use every day from medical instruments and industrial robots to energy sensors and connected vehicles. But there is one crucial step that determines whether an AI project succeeds or fails: hardware selection.

As AI moves closer to real-world applications, one challenge remains and that is trust. Customers do not just want intelligent devices. They want secure, reliable, and compliant AI systems that protect privacy, operate offline, and meet evolving regulations.