In an era defined by rapid digital transformation, metrology—the science of measurement—is at a pivotal crossroads. As industries worldwide integrate artificial intelligence (AI), automation and digital infrastructures, the need for precise, interoperable and trustworthy measurement data has never been greater.

At the Bureau International des Poids et Mesures (BIPM’s) recent Forum on Metrology and Digitalization (FORUM-MD), global experts examined the impact of digital advances on measurement science.

The discussions underscored a fundamental truth: metrology is not just adapting to the digital age—it is shaping its very foundations. 

Building a Digital-Ready Metrology Framework

 At the core of digitalization lies data. But for measurement data to be useful in a connected world, it must adhere to FAIR principles—Findability, Accessibility, Interoperability and Reusability. Experts at the Forum emphasized that structured, machine-readable formats are essential to ensuring seamless integration into AI-driven systems, international regulatory frameworks and industrial processes.

 This shift requires globally recognized digital identifiers and standardized formats that enable cross-border comparability of measurement results. Without these safeguards, the digital ecosystem risks fragmentation—jeopardizing everything from precision manufacturing to medical technologies.

Automation and AI: Transforming Measurement Science  

One of the most significant developments is the transition from traditional paper-based calibration certificates to Digital Calibration Certificates (DCCs).

DCCs provide secure, tamper-proof and machine-readable records, ensuring that calibration data remains accurate and seamlessly integrated into digital infrastructures. By eliminating manual transcription errors and enhancing traceability, DCCs are paving the way for fully automated, real-time measurement systems.

Yet, as AI-driven tools become central to measurement science, experts in the Forum stressed the importance of robust data quality standards. AI models are only as reliable as the data they are trained on—meaning that any errors, biases or inconsistencies in measurement data could have far-reaching consequences.Metrology will be essential to underpin international protocols for AI and ensure trust and accuracy for AI applications.

Looking Ahead: The Global Challenge of Digital Metrology

As metrology enters the digital age, one thing is clear: collaboration is key. The shift to a fully digital measurement ecosystem requires cooperation between national metrology institutes, policymakers, industry leaders and AI experts.

The discussions at FORUM-MD 2025 highlighted the need for a unified approach to digital measurement standards—one that ensures interoperability across industries, enhances global trade and supports emerging technologies.

Photo depicts: Participants from Forum MD 2025.