RE.M.I. – Regulation Meets Innovation

What is the RE.M.I. Initiative?

The RE.M.I. Initiative , “Regulation Meets Innovation”, launched by the National Commission for Data Protection (CNPD) and the AI Factory is a collaborative initiative designed to foster structured and constructive dialogue between AI and digital technology stakeholders, regulators, and subject-matter experts within Luxembourg.

RE.M.I. serves as a neutral, structured, and agile platform for exchanging knowledge and jointly addressing operational, technical, and regulatory challenges emerging in the fields of artificial intelligence and digital innovation. The initiative is particularly aimed at enhancing clarity, coherence, and synergies within Luxembourg’s innovation ecosystem while supporting responsible, human-centric innovation.

The approach is based amongst others on the setting up of a Community of Practices based on thematic working groups and on the synchronization of practical workshops and conferences dedicated to technological evolutions and regulatory developments.

Join the RE.M.I.’s AI Community of Practices!

  • Eligibility : Innovative companies [1], public and semi-public institutions and academic and research bodies established in the Grand-duchy of Luxembourg are invited to APPLY HERE.
  • Kick-off Meeting: 7 October 2025

Contact - For further information, please contact: ia@cnpd.lu 

More about RE.M.I.

Objectives

RE.M.I. is established to:

  • Facilitate structured dialogue between AI innovators, project leaders, regulators, and experts.
  • Promote synergies across Luxembourg’s AI ecosystem by building on existing initiatives.
  • Encourage responsible, compliant innovation practices, accessible to SMEs, startups, and established companies alike.
  • Support regulatory sandboxes and innovation projects through coordinated working groups and expert workshops.

AI Community of Practices

The RE.M.I.’s AI Community of Practices is positioned as an ecosystem facilitator, offering a collaborative framework and pooled resources for :

  • Identify and qualify sectoral or cross-sectoral issues (Plenary session)
  • Activate the necessary expertise on an ad hoc and targeted basis (Working Group)
  • Propose recommendations, not necessarily as part of long-term support for individual projects, but rather in general terms (dissemination of knowledge)

This approach will encourage an agile and contributive approach, in line with the expectations of SMEs, start-ups and public partners.

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Operational Structure of the AI Community of Practices

Plenary of the AI Community of Practices
Brings together all participants, including partner companies and institutions.

  • Objectives: Identify and qualify sectoral or cross-sectoral issues.
  • Tasks :
    • Address cross-cutting issues: governance, interoperability, regulatory framework and strategic challenges ;
    • Decide on the creation of working groups, their composition and themes;
    • Enables each thematic working group to report to the plenary on the work carried out, proposals and use cases under consideration
    • Determines the objectives/means of sharing knowledge within and outside the Plenary.
       

Theme-based working groups
Bring together the experts in each of the working groups created

  • Objectives: Facilitate targeted discussions, expert workshops, and joint analyses on emerging issues.
  • Tasks :
    • Each working group will elect one or more Group Chairs responsible for leading the group, determining the content of the work to be carried out according to the issues identified in Plenary and the expected deliverables.
    • Each working group will report to the Plenary on the progress made by its group and, where appropriate, to present certain salient aspects of the work carried out.
    • Thematic working groups will be set up according to the issues raised during Plenary. They may cover: Cybersecurity, AI Testing, Standardization, Data Science, etc.
       
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[1] i.e. organisations developing or integrating AI systems or providing services related to artificial intelligence (AI system developers, AI system integrators, companies integrating AI systems in their products or related service providers in Cybersecurity, Data Science & AI, Data Governance, Cloud Computing and IT Infrastructure, Normalisation & Standards, Training & Skills, Regulation & Compliance, Ethical, Legal and Social Aspects, etc.)

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