Here is the translation of the text into English:
The adoption of Artificial Intelligence (AI) in measurement systems represents a qualitative leap that requires new guarantees. It is not simply a matter of equipping oneself with the most advanced tools; the rigor with which these tools are verified and calibrated according to accreditation standards is also fundamental, along with the professional competencies of those who use them.
AI is profoundly changing the measurement landscape, spanning from smartwatches that monitor vital parameters such as heart rate and blood oxygen levels to technological systems applied in the aerospace, automotive, and manufacturing sectors. These developments place particular emphasis on speed, automation, and predictive capability, but in the face of such rapid evolution, a crucial question arises: how can we ensure that the data generated, collected, and measured is actually reliable and managed competently?
The combination of AI and metrology marks the beginning of a revolution that requires careful management. The responses provided by algorithms, which have the ability to learn from vast amounts of data and return results promptly, largely depend on the quality of the data used for their training. Erroneous or unreliable data at this stage can compromise the performance of measurement instruments, potentially impacting end products and services.
It is therefore essential that even the most sophisticated devices undergo calibrations carried out by accredited laboratories. These calibrations ensure the quality and reliability of the data readings. Furthermore, the increasing complexity of intelligent measurement systems amplifies the need for technical awareness, which, in the context of accreditation, translates into a fundamental value of competence.
The certification of competencies is a central aspect in this scenario. While Artificial Intelligence offers strategic opportunities to improve the efficiency of measurement systems, its proper use is contingent on the presence of well-prepared professionals. In this context, the certification of competencies according to specific regulatory schemes becomes crucial. These certifications require thorough training, focusing not only on the tools but also on understanding the logic of algorithms, the principles of calibration, and the criteria for ensuring data quality.
Certifications are sometimes issued by accredited independent bodies, in compliance with regulations such as UNI CEI EN ISO/IEC 17024. They attest that a professional possesses and maintains the necessary competencies to operate in a qualified and up-to-date manner even in the field of AI-assisted measurement. Moreover, having an accredited certification not only adds value in the professional market but also encourages professionals to pursue continuous training. This process helps to establish a system based on trust, transparency, and security throughout the entire operational flow.
Without certified competencies, the risk of inadequate use of Artificial Intelligence increases, with potential critical errors concerning data quality and safety. In this context, automation cannot be divorced from qualified and certified human supervision that ensures the effectiveness of measurement systems.
The evolution of measurement processes accompanied by the use of AI offers immense opportunities but requires responsible and competent management. It is essential for professionals to operate within a quality system, both in the choice of tools and in continuous training, to ensure results that can be considered reliable and accurate.
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