AQCLab has become the first organisation to obtain accreditation for evaluating data quality in Artificial Intelligence (AI) systems. After successfully passing the extension audit carried out by ENAC, the laboratory has added the evaluation of data completeness in accordance with ISO/IEC 5259-2 to its ISO/IEC 17025 accreditation scope, adding to the product quality and data quality accreditations that AQCLab pioneered more than 15 years ago.

ISO/IEC 5259-2 defines a data quality model for advanced analytics and AI systems based on Machine Learning (ML), ensuring that training and analysis processes are supported by reliable, complete and comprehensive data.

With this new accredited test, AQCLab offers companies the possibility of validating the quality of data in their AI systems, providing the confidence that comes with an internationally recognised accreditation backed by a team of software and data quality experts.

Why is it important to evaluate data quality in AI? It is a critical factor for the success of Artificial Intelligence systems because:

• It prevents bias and errors in Machine Learning models.
• It ensures that AI-based decisions are reliable and transparent.
• It reinforces regulatory compliance and trust in digital processes.

IIf your company wants to evaluate the quality of data in its AI systems, you can contact AQCLab via our form.