Does your company work with AI—or plan to—and are you unsure how to turn AI Governance into concrete practice? This foundational course gives you a clear, hands-on starting point. In short: if you want to document control of AI in line with AI regulation and internal policies, you need clear roles, controls, and processes that work in day-to-day operations. This course shows you how.

AI Governance helps you to run your AI responsible, compliant, and effective in your organisation. The goal is to make requirements tangible: establish clear accountability, right-size controls to risk, and create the necessary documentation needed for later audits. When governance is implemented correctly, leadership and stakeholders gain confidence that you can deliver AI solutions that meet internal policies, regulatory expectations, risk-management requirements.

This course focuses on the practical application of AI Governance and gives you the overview and insight needed to document your governance effort, identify gaps, and understand how governance (policies, controls, roles/RACI, etc.) are implemented in practice—illustrated with concrete examples.

Course objectives

After the course, participants will have:

• An overview of the structure, content, and practical requirements of AI Governance (policies, controls, roles/RACI, audit trail).

• A high level overview of  EU AI Act’s key elements (scope, risk classes, obligations) and the most relevant GDPR touchpoints for AI.

• Knowledge of how to perform a quick baseline of current practice and identify priority gaps.

• An understanding of risk and controls at a pragmatic level (model and data risks, necessary practices for evaluation and monitoring).

• A realistic implementation roadmap with owners, milestones, and success criteria.

• A view of “what it looks like in real life.”
  

The course is aimed at:

• Compliance, Risk, Legal, Governance, IT, and DPO profiles who do not work with AI daily but need to make AI governance concrete.

• Private-sector companies across industries.

Prerequisites

• No specific AI prerequisites.

• Advantageous: basic knowledge of corporate governance and regulation.
  

Course Lecturers

Björn Preuss, VP Product & AI Governance Advisory, 2021.AI

Björn supports medium-sized and large companies with their AI ambition—from strategy and governance to development, operations, and scaling.  He is an Assistant Professor for Risk management and Finance at CBS and a trusted advisor on the subject. Holding a Ph.D. in quantitative economics, he combines a theoretical and practical view on AI risk management.  In this practical course he aims to turn his advice into clear control points —without slowing AI innovation. His teaching is research grounded, with examples from practice to give you a clear guidance on what to do next to be ready for the future.

Charlotte Bagger Tranbjerg, CEO & Founder, Lex Futura

Charlotte is one of the Nordics’ most experienced advisors in tech and data compliance. With a PhD in Law (2006), many years as advisor and partner at Bech-Bruun, and recognition as Women in Data 2022, she combines deep legal expertise with strong technology understanding. She makes complex rules usable across the organisation and links business, risk management, and law into actionable, compliant solutions. Her teaching is clear, down-to-earth, and action-oriented.

Dates and venue

• Date & venue: 9.00 - 17:00 CEST

• Duration: 8 hours in-person, followed by online follow-up & Q&A approx. 14 days after the course

• Price: 5.900 DKK excl VAT

• Catering: Included

• Cancellation/no-show: [TBD by DNV]

• Participant requirements: (e.g., laptop; optional access to internal policies for reflection; NDA if relevant) [TBD by DNV]

• Certificate/CPD: [TBD by DNV]
  

Disclaimer: This course is for educational purposes and does not constitute legal advice. Content may be updated in line with new or amended regulations and guidance.