An AI policy alone does not constitute governance. It is crucial that organisations know which AI systems are being used, who decides on their deployment, which risks are accepted, and how procurement, operation, monitoring and escalation are embedded within the organisation. The training course provides a practical governance model for organisations wishing to scale AI in a controlled manner.
An AI policy on its own does not constitute governance. What is crucial is that organisations know which AI systems are being used, who decides on their deployment, which risks are accepted, and how procurement, operation, monitoring and escalation are embedded within the organisation. This training course provides a practical governance model for organisations wishing to scale AI in a controlled manner.
Objectives and benefits
· Understand the key building blocks of effective AI governance and apply them to your own organisation.
· Clearly define roles, responsibilities and approval processes for AI.
· Establish a risk-based AI inventory and tiered control mechanisms.
· Integrate governance into existing processes such as procurement, IT approval, project management, data protection, security and incident management.
Content / Agenda
· What AI governance must achieve: steering rather than a list of prohibitions; distinguishing it from pure AI policy or AI ethics.
· Governance model: AI inventory, use-case classification, risk levels, approval thresholds and documented decisions.
· Roles and responsibilities: Business Owner/AI Owner, IT, Security, Data Protection, Legal/Compliance and management escalation.
· Lifecycle governance: procurement, testing/pilot, go-live, change/model updates, monitoring, incidents and exit.
· Third-party and reseller governance: manufacturer information, contractual assurances, customer transparency, delineation of responsibilities and the passing on of regulatory requirements within the supply chain.
· Practical workshop: Setting up a lean governance process and discussing typical approval decisions.
Target audience
Senior management and executives; those responsible for AI, digitalisation and innovation; legal, data protection, compliance and risk; IT and security management; procurement and vendor management; product and project managers. In the reseller sector, this is also particularly relevant for those who select manufacturer solutions, bundle their own services or share responsibility for governance and compliance requirements vis-à-vis end customers.
Practical relevance
The focus is not on abstract regulation, but on concrete control: who is authorised to approve what? What information must manufacturers provide? When is an in-depth review required? How can shadow AI and uncoordinated AI provenance paths be prevented? Participants will receive a transferable governance framework and discuss specific role-based and approval scenarios.
Concept and format
A 4-hour face-to-face session including a short break, as case studies and discussion constitute a significant part of the course’s value. A hybrid delivery is technically possible, but should only be chosen if suitable room technology and clear facilitation are in place, so that online participants are equally involved in discussions and exercises.
Organisation and price
Duration: 4 hours, including a short break
Date: 3 & 10 December 2026
Format: Face-to-face
Participants: Max. 15
Prerequisites: No specialist legal or technical knowledge required; some prior experience with AI is an advantage
Materials: Set of slides, certificate of attendance
Recommended price: CHF 290 per person, excluding VAT
Registration: ALSO Training – AI Governance: From AI Policy to an Effective Governance Architecture