Training course
digicode: AITRAN
AI Transformation Manager
Course facts
- Viewing and understanding the opportunities and challenges of AI transformation from different perspectives
- Making strategically important decisions (e.g. regarding hosting infrastructure, legal responsibility or new business models)
- Operational implementation of your own project (e.g. development of new products and services, adaptation of processes or introduction of tools)
In five practice-oriented modules, you will learn how to effectively drive the AI transformation in your company.
Together with experts and like-minded people, you will develop the foundations for effective AI projects and workflows that will make your company future-proof.
You will identify specific AI use cases for your organization and learn how to develop a sustainable AI strategy and effective guidelines for your team. You will deepen your knowledge of legal requirements and key aspects of data management. The course is rounded off with tried-and-tested change management principles that will enable you to anchor AI initiatives in your company in the long term.
Your plus: Personal support and coaching
During the course, you will benefit from a unique combination of personal learning support from an AI transformation expert (two 1:1 coaching sessions) and a specialized chatbot. With this support, you can put your own AI project directly into practice.
The training course consists of the following modules:
1 Onboarding
- Strategy vs. use case: How do you proceed?
- Tasks and processes: What is suitable for AI?
- Tool setup: How do you assess needs?
- Piloting: How do you measure success?
- Scaling: How does the transformation succeed?
3 AI strategy and guidelines for generative AI
- Business models: Understanding the opportunities and risks of AI in different industries
- AI use cases and tools for businesses: Focus on HR, marketing and customer care, as well as ChatGPT, Gemini and Microsoft Copilot
- AI governance: Learning how to deal with legal and ethical challenges
- AI guidelines: Developing policy and guidance documents to match use cases and tools
- Success measurement: Applying criteria to optimise and evolve the AI strategy
- Introduction & definitions of key terms
- Overview of applicable law and related concepts
- AI Act
- Unfair Competition Act
- Data protection laws (i.e. GDPR and Swiss Data Protection Act)
- Copyright and intellectual property
- Use cases
- Use of Chat GPT, Copilot, Gemini, Mistral, etc.
- Implementing your own chatbot
- Delegating decision-making to AI
- Use of AI in your company
- AI & products/services
- AI & HR
- AI & sales
- AI & finance and operations
- AI & marketing
5 AI and Data Management
- Data as a management topic: Why data is not a tool or Excel issue, but rather the basis for control, ownership, and better decisions
- The role of data for AI: Why data quality, timeliness, and access rights are the bottleneck (foundation models do not know your business)
- Data types & data landscape: Important data types (e.g., numerical, text, documents, product, user, HR, policy data) and typical system landscapes, including single source of truth
- AI integration & automation: Integration patterns (assistant, router, automator) and building blocks such as custom GPTs and automation tools (e.g., Make, Copilot Studio, n8n)
- Use cases, roadmap & governance: AI use case canvas for structured description and prioritization, roles & responsibilities, guidelines/compliance, and success measurement with process, business, and data KPIs
6 Artificial Intelligence and Change Intelligence
- AI & Organization: How is artificial intelligence changing collaboration, roles, and structures?
- Technical vs. organizational perspective: What challenges arise alongside the technology?
- Change management in the context of AI: Why does AI transformation require new strategies and approaches?
- Change & dynamics: How can we deal with the speed and depth of AI-driven change?
- Culture & identity: What impact does AI have on corporate culture and self-image?
- Change processes: What distinguishes AI-driven transformation from traditional change processes?
- Change strategies: Taking technological and organizational complexity into account simultaneously
- Reflecting on AI cases: Analyzing and classifying your own AI case with suitable tools
- Planning the next steps: Specifying technical and non-technical measures for the AI project
- Structuring the change process: Identifying side issues and systematically integrating them into planning
7 Offboarding
8 Final Presentation & Discussion
Consists of the following modules
- Onboarding
- AI Business Use Cases
- AI strategy and guidelines for generative AI
- AI & Compliance
- AI and Data Management
- Artificial Intelligence and Change Intelligence
- Offboarding
- Final Presentation & Discussion
This course combines three innovative learning formats: An AI-based chatbot for teaching the basics, in-depth thematic sessions on site and/or online and personal advice from experts in 1:1 coaching. Within this framework, you will take the first steps with your own project to advance the AI transformation in your company.
This course is designed for managers and decision-makers who want to transform their organization through targeted AI implementation.
It is particularly suitable for people who have already gained initial experience with AI tools or have taken part in one or two AI day courses – and now want to take the next step: To actively help shape a well-founded, strategically sensible introduction of AI in the company.
This course is aimed at people in the following roles, among others:
- Project managers, product managers and product owners
- Business analysts and data engineers
- Team leaders (Head of IT, Head of HR, Head of Marketing, etc.)
- Career changers and those returning to tech and digital
- Consultants and internal change agents
The course has no formal prerequisites.
- Initial practical experience with ChatGPT and/or similar AI tools and basic knowledge of artificial intelligence are recommended.
- Willingness to set up free accounts for various tools yourself during the course.
At the end of the course, participants present their findings in a 15-minute presentation, followed by a 15-minute discussion. This interactive type of examination is a valuable opportunity to consolidate what has been learned and exchange ideas with others – and successful completion leads to Digicomp certification as an «AI Transformation Manager».
Please bring your own laptop.
You can use it to save what you have been shown and learned directly in your environment and use it immediately for your daily work in the company. If you do not have a laptop, we can provide you with a computer. Please contact info@digicomp.ch after registering for the course.