The Governing AI Use in the Enterprise training course helps organizations structure their approach to artificial intelligence in a pragmatic, coherent and responsible way. It covers how to frame AI usage, clarify responsibilities, limit misuse, protect information and turn AI into a controlled performance lever rather than a source of risk or improvisation.
An essential training course to move from scattered usage to structured governance
During this training course, participants discover how to define governance suited to their organization, set simple rules, identify use cases to authorize, to regulate or to prohibit, distribute roles across business units, management, HR, IT, legal or compliance, and support teams through gradual adoption. The training emphasizes the challenges of confidentiality, quality, security, accountability and adoption management.
Module 1: Why Govern AI in the Enterprise
Module 2: Key Risks Related to AI Use
Module 3: Defining a Governance Framework
Module 4: Distributing Roles and Responsibilities
Module 5: Supporting AI Adoption
Module 6: Building a Governance Roadmap
The growing adoption of artificial intelligence in organizations creates an urgent need for governance. Without a structured framework, the use of AI can generate legal, ethical and operational risks that outweigh the expected benefits. AI governance aims to maximize value while controlling risks.
Companies that implement effective AI governance protect themselves against potential misuse and position themselves favorably in the face of increasing regulations in this area.
AI governance rests on several pillars. Strategy defines the organization’s vision and objectives regarding AI. Policies frame authorized usage and prohibited practices. Processes organize the concrete implementation of rules. Oversight ensures compliance with commitments and continuous improvement.
The human dimension is essential. Appointing responsible individuals, training employees and establishing information reporting channels are indispensable components of a living and effective governance framework.
The regulatory landscape is evolving rapidly. The European AI Act imposes differentiated obligations based on the risk level of AI systems. Switzerland, although not an EU member, is impacted by this regulation through its trade relationships and multinational companies. The Federal Act on Data Protection adds specific requirements for the processing of personal data by AI.
Anticipating these regulatory developments allows Swiss companies to prepare with confidence and turn compliance into a competitive advantage.
AI risks in business are numerous. The confidentiality of data transmitted to tools, the reliability of results, algorithmic bias, intellectual property of generated content and dependency on providers are all risks to map and manage. A risk-based approach allows you to prioritize actions and allocate resources proportionally.
Control mechanisms include regular audits, reliability testing, ethical reviews and escalation processes. These controls must be adapted to the risk level of each AI use case.
AI governance must be proportionate and pragmatic. An overly rigid framework hinders innovation, while an absence of framework exposes the organization to unacceptable risks. The recommended approach is to start with the most critical use cases and gradually extend the governance scope.
ITTA supports executives and managers from French-speaking Switzerland in implementing their AI governance with training delivered in Geneva and Lausanne, combining theoretical framework and practical tools that are directly applicable.
Switzerland, with its tradition of regulatory rigor and its position at the crossroads of Europe, is particularly concerned by AI governance challenges. Swiss companies operating internationally must anticipate the requirements of the European AI Act while respecting the national legal framework. Implementing adapted AI governance is both a compliance obligation and a competitive advantage.
The Swiss economic fabric, composed of multinationals, innovative SMEs and public institutions, presents varied needs in terms of AI governance. The training courses delivered by ITTA in Geneva and Lausanne are designed to meet this diversity of contexts, providing tools and methodologies adaptable to each type of organization and industry sector.
Who should lead AI governance in the company?
AI governance involves the executive team, legal, IT, HR and business units. Appointing an AI officer or a dedicated committee helps coordinate the various stakeholders and maintain a coherent vision.
Does the European AI Act apply to Swiss companies?
Swiss companies that offer services in the EU or that use AI systems developed in the EU may be affected. The training details the implications for the Swiss context and recommended preparatory measures.
How can I assess AI-related risks in my organization?
Risk assessment begins with an inventory of AI uses, a classification by risk level and an impact analysis. The training provides a structured methodology and practical tools for this assessment.
Does AI governance slow down innovation?
Well-designed governance accelerates innovation by clarifying the rules and reducing uncertainty. Employees are more likely to innovate when they know what is allowed and what is not.
Should certain AI uses be prohibited in the company?
Some uses may require restrictions or prohibitions, particularly those involving sensitive data, automated decisions with human impact or non-compliance risks. Governance defines these limits explicitly and with justification.
Monday to Friday
8:30 AM to 6:00 PM
Tel. 058 307 73 00
ITTA
Route des jeunes 35
1227 Carouge, Suisse
Monday to Friday, from 8:30 am to 06:00 pm.
