For organizations operating nationally in Canada, Quebec’s anonymization requirements have added a new layer of complexity to data use for analytics, research and AI. In particular, the Quebec anonymization regulations introduce new concepts to the definition of identifiability in a Canadian context, although they have been part of the expectations under the EU’s General Data Protection Regulation (GDPR). For example, concepts such as “inferences” need to be defined and evaluated in data to demonstrate that they meet the anonymity requirements. In practice, many organizations still struggle to interpret these requirements, apply them consistently and produce the necessary evidence for governance, review and approval. Join us on May 20th, 2026 at 11 am EDT for a webinar that will explain what the anonymization requirements mean in practical terms, with a focus on understanding and assessing inference and other privacy risks in anonymized data. Drawing on current regulatory developments and real-world implementation challenges and solutions, we will show how organizations can take a more rigorous and scalable approach. Participants will see how new technologies and standards can help automate these assessments and gives teams a more complete view of privacy exposure, including inference considerations.