Day 1 – Foundations and practical use of AI
Generative AI fundamentals and working with tools
- Capabilities and limitations of generative AI in practice
- AI mindset: where AI delivers the greatest value
- Overview of tools (ChatGPT, Claude, Gemini, specialised applications)
- Differences between tools and their appropriate use cases
- Prompting basics and best practices
Practical use of AI in everyday work (block 1)
- Writing and editing emails (replies, follow-ups, personalisation)
- Creating texts and internal outputs (summaries, drafts, background
materials)
- Writing meeting notes (from transcripts and notes)
- Structuring information and working with unclear assignments
Practical use of AI in everyday work (block 2)
- Working with documents (summarising, extracting, comparing)
- Analysing large texts and finding key information
- Creating checklists, procedures and internal standards
- Introduction to data analysis and simple visualisation
Day 2 – Systematisation, workflows and implementation
Systematising work and creating workflows
- How to set up your own AI working system
- Creating and organising a prompt library (templates)
- Combining multiple tools in a single workflow
- Chaining steps (e.g. transcription › summary › output)
- Speeding up repetitive tasks
Advanced use and efficiency
- Iterating and improving outputs (prompt refinement)
- Working with context and inputs (documents, data)
- Transferring between tools (copy/paste workflow, integrations)
- Practical scenarios from participants' real work
Safety, quality and implementation
- Working with sensitive data and security principles
- Verifying outputs and quality control
- Risks (hallucinations, bias) and how to manage them
- When not to use AI
Building the AI Playbook and action plan
- Creating your own prompt library (8–10 templates)
- Defining key use cases for your own work
- Designing concrete workflows
- Action plan (what to deploy immediately / what to test / what to develop
further)
Hands-on practice
- Practical exercises on real work tasks (emails, documents, analyses)
- Simulating everyday work with AI tools
- Creating your own prompts and improving them iteratively
- Designing simple workflows for repetitive tasks
- Building a personal AI Playbook (8–10 concrete procedures)
Wrap-up
- Recap of key principles and procedures
- Discussion of participants' specific scenarios
- Q&A
- Recommended tools and resources for further
development
