Alessandro Fiorente

Physical AI is often portrayed as a technological revolution. But what happens when a machine begins to participate in decision-making? The real challenge may not be algorithms, but control, validation, and engineering responsibility.

When the price of a raw material such as steel increases, attention often shifts toward procurement costs. In special-purpose machinery and engineered-to-order systems, however, the final result depends on a much broader set of design decisions. Materials, geometries, manufacturing processes, and production workflows all influence overall product efficiency. For this reason, every change in context can become a valuable opportunity to reassess solutions that have become established over time.

Is the shortage of engineers really the problem? In reality, many companies are facing a deeper issue: managing variable technical workloads and maintaining coherence across different competencies. When pressure increases, it’s not just about lacking people — integration breaks down. The real issue is not the number of resources, but the technical structure that organizes them.