Artificial Intelligence for Managers
and Administrative Professionals
Teaching blocks
15. 9. | 17. 9. | 22. 9. | 24. 9. | 29. 9. | ||||||
| Module 1 (16-20h) | Module 2 (16-20h) | Module 3 (16-20h) | Module 4 (16-20h) | Module 5 (16-20h) | ||||||
2. 11. | 4. 11. | 9. 11. | 11. 11. | TBD | ||||||
| Modul 1 (13-17h) | Modul 2 (13-17h) | Modul 3 (13-17h) | Modul 4 (13-17h) | |||||||

About the course
The program also includes a module dedicated to legal aspects, risks, and regulations (including the AI Act), which is sponsored by the Legitas law firm.
The program includes hands-on demonstrations, case studies, and interactive workshops that allow you to immediately apply what you learn. The course is suitable even for participants without technical backgrounds and emphasizes the legal and ethical aspects of AI. After completing the course, you will be equipped to use artificial intelligence effectively in your daily practice and gain a competitive advantage.
Legitas - Legal aspects and risks

Course Content and Schedule
This module explains key AI concepts such as machine learning, NLP, and LLMs, along with their practical applications in business. It focuses on understanding how AI helps improve efficiency and reduce costs in everyday processes.
- Key Terms: AI, machine learning, NLP, large language models (LLMs).
- History and Trends: A brief timeline and the current significance of AI.
- Business Value: Automation, time savings, improved efficiency.
- Difference Between a Chat Model and an AI Assistant, including application examples.
In this module, we focus on real-world examples of how AI is used — such as email automation, report generation, or chatbot implementation. We will demonstrate how companies leverage AI to gain a competitive advantage.
- Automation of Routine Tasks: emails, forms, reports.
- Chatbots and Voice Assistants: internal support and customer communication.
- Decision Support: data processing, trend prediction.
- Examples of companies that have already implemented AI and the results they achieved.
1.3 Discussion and Interaction (40 min)
- Q&A on the theoretical foundations.
- Brainstorming: potential uses of AI in participants’ own processes.
- Sharing ideas among participants.
- Recap of key concepts and preparation for the next module.
- Discussion of expectations for the practical demonstrations in the next part of the course.
2.1 Introduction to Language Models (60 min)
- What is a language model and why is it so useful for text creation and processing?
- Examples of tools: ChatGPT, Bing Chat, Bard (basic description of how they work, how they differ).
- Prompt engineering in a nutshell: why it is important how we ask a question or prompt AI.
2.2 Practical work with language models (90 min)
- How to formulate a query for AI so that the output is as accurate as possible: tone, style, context.
- Examples:
- Generating business emails or texts for marketing purposes.
- Summarizing long documents or reports.
- Creating short presentations or outlines for training.
- Tips and tricks: how to recognize when AI is "making things up" and when it is better to use verified sources.
2.3 Ethical and legal aspects (60 min)
Data protection and basic principles (GDPR at a basic level).
- Potential risks: bias, misinformation, security of shared data.
- Internal company rules: when and how to consult with IT and management about AI deployment.
- Specific examples of successful and easily understandable deployment of language models.
- Open discussion on possible obstacles and participants' real-life experiences.
3.1 Identifying Opportunities (60 min)
This module helps participants identify areas where AI can deliver the greatest value and introduces simple methods for analyzing processes and evaluating their automation potential.
- How to identify processes suitable for automation.
- Evaluating costs and benefits (ROI).
- Practical tools for analyzing process efficiency.
3.2 Pilot Projects and Implementation (90 min)
In this module, participants learn how to structure AI pilot projects—from initial testing to full-scale deployment.
- Process: From Proof of Concept to full-scale deployment.
- Collaboration between a reasoning model and a “standard” model: practical demonstrations.
- Evaluating the success of a pilot project and iterating based on feedback.
A practical module focused on introducing AI into the workplace and communicating its benefits to employees.
- Explaining the benefits to colleagues.
- Internal guidelines for working with AI.
- Communication strategies for smooth AI adoption.
A module dedicated to sharing best practices and discussing real-world examples.
- Sharing best practices.
- Recommendations of tools and partners.
- Discussion of participants’ real-world examples.
- Participants will propose a specific scenario for deploying AI in their company.
- They will define goals, metrics, necessary resources, and implementation procedures.
- Proposal for integrating a language model with an internal database (RAG) or internal AI assistant.
- A short test to check your understanding of key concepts (prompt engineering, ethics, integration).
- Practical task: design a prompt or simple solution with an AI model.
- Recap of the main points of the course.
- Recommendations for advanced resources, tools, communities, and literature.
Legal standards and regulations, the AI Act, a legal perspective on cybersecurity, contractual protection of customers, and related legal practice
- Why AI cannot be used without a legal context
- Typical legal and security issues in the use of AI
- Overview of relevant legal areas (criminal and civil law, AI Act, GDPR, etc.)
- Examples of situations where improper use of AI led to legal or reputational risks
- Practical impacts of regulation on specific AI systems (LLMs, automation, chat/voice bots)
- Personal data protection (GDPR)
- European AI Act regulation
- Copyright law
- Terms of use and contractual relationships
- How to assess whether an AI tool (ChatGPT, Claude, DeepSeek, etc.) is appropriate and secure
- Risk assessment criteria: security, GDPR compliance, data handling
- Examples of risk assessments for commonly used AI tools
5.4 Proper Use of AI Tools
- Handling personal and sensitive data
- Contractual terms and conditions
- Copyright considerations
5.5 Internal Process Setup
- How to ensure legal and secure use of AI within a company or organization
- AI literacy and employee training
- Internal rules and AI guidelines
- Inventory and audit of used AI tools
5.6 Discussion and Q&A
- Sharing experiences
- Addressing specific practical questions
- Recommendations for further development and resources on legal aspects of AI
Technical Requirements
At least a high school education
Bring the device you normally use for work, and don’t forget your charger.
Access to AI Tools
Make sure to create accounts for tools such as ChatGPT (the OpenAI Playground). It is necessary to have access to at least one AI tool.
Who is this course for?
Teaching methods
- Interactive lectures with demonstrations (ChatGPT, Bing Chat, OpenAI Playground).
- Practical workshops: Creating prompts, simulating work with data.
- Discussions and case studies.
- Final project and test.
What You Will Gain from the Course
Who Will You Learn From?
RNDr. Jakub Haláček
He later changed direction and joined Unicorn Systems as a business analyst and consultant. He currently holds the position of Director of the Unicorn AI Research Center, where he focuses on research in the field of artificial intelligence.
Lucie Malá, LL.M.
Mgr. Petra Stupková
Testimonials
Company Director
HARTMANN-RICO a.s.
General Manager
Marketing Zone
Manager for Education and Social Affairs
AutoSAP