What the EU AI Act Means for US Companies
When a US business falls under the EU AI Act, how the 4 risk tiers work, the updated 2026-2028 deadlines after the Digital Omnibus, and what to do first.
The policies, roles, and processes that determine how an organization's data is managed, protected, accessed, and kept accurate.
Data governance answers practical questions: who owns each important dataset, who may access it, how quality is checked, how long records are kept, and how the organization meets laws such as GDPR. It typically involves data owners, data stewards who maintain quality, and shared definitions so that terms like active customer mean the same thing in every report.
For example, a retailer might discover that marketing and finance calculate monthly revenue differently. A governance process would agree a single definition, record it in a data catalogue, and assign an owner to maintain it. Good governance supports trustworthy analytics and responsible AI use. It works best when it is proportionate, focusing effort on the most sensitive and business-critical data rather than creating heavy rules for everything.
An approach to data architecture that gives business domains ownership of their own data, shared as products across the organization.
GDPRGeneral Data Protection Regulation: the European Union's law governing how organizations collect, use, and protect personal data.
Synthetic DataArtificially generated data that mimics the patterns of real data, used for testing, training models, or sharing without exposing real records.
When a US business falls under the EU AI Act, how the 4 risk tiers work, the updated 2026-2028 deadlines after the Digital Omnibus, and what to do first.
A plain-English guide to big data: what the 3 Vs mean, real examples, how big data is processed and a simple test for whether your data is actually big enough to matter.
A practical requirements checklist for choosing a BI tool: data sources, users, governance, pricing models and how to run a pilot before you buy.