Practical Introduction to AI in Business

This training teaches how to use AI in everyday work—from content generation and analysis to process automation. Participants will learn prompt engineering, create their own AI assistants, and practice data analysis, reporting, and implementing AI solutions with attention to security and legal compliance.

Who is this training for?

• Managers and business leaders who want to understand how to use AI to streamline processes and support decision-making
• Specialists and office employees who want to learn practical use of AI tools (e.g., ChatGPT, automation tools, content creation)
• HR, marketing, sales, and analytics professionals, as the program strongly emphasizes content generation, data analysis, prospecting, and automation
• People responsible for implementing new technologies in the company—the training also covers legal and organizational aspects (GDPR, AI Act, change management)

Training Benefits

• Gain comprehensive knowledge of AI possibilities in business
• Learn to use AI tools in your daily work
• Find out how to implement AI safely, legally, and responsibly in your organization

Module 1: Panorama of the AI Revolution – What You Need to Know About Artificial Intelligence (3h)

• Introduction to artificial intelligence: what AI is and why it is crucial for modern organizations
• Overview of global AI trends: how AI is changing industries, the labor market, and management
• What can AI do today? The most interesting, most useful, and best AI tools
• What can AI do today? The most interesting, most useful, and best AI tools
• AI tools and models for creating multimedia (DALL·E, Midjourney, Sora, Runway, ElevenLabs, Udio)
• The AI solutions ecosystem for business—tool aggregators and specialist tools
• No-code process automation platforms (Make, Zapier)—capabilities overview

Module 2: Fundamentals of AI Technology – From Theory to Practical Application (1h)

• An accessible introduction to AI technologies—machine learning, neural networks, and large language models (LLMs)
• How do LLMs work? Natural Language Processing (NLP) and next-token prediction
• The importance of NLP in modern service economies
• Comparing ChatGPT and other large language models (Claude, Google Gemini, MS Copilot, DeepSeek, Grok)—capabilities, differences, use cases
• Main AI limitations (hallucinations, bias, incomplete knowledge) and ways to address them

Module 3: Practical Workshop – First Steps with ChatGPT (4h)

• Overview of the ChatGPT interface and core features
• Privacy protection when working with ChatGPT—data controls and memory settings
• Creating effective prompts—instructions, context, persona, emotional layer
• Generating and editing business content with AI
• Creating marketing materials
• Market research, competitive analysis, prospecting
• Automating sales proposal preparation
• Reporting, data analysis, and data visualization
• Strategic planning, brainstorming, and supporting creative processes

Module 4: Effective AI Collaboration – Techniques and Best Practices in Prompt Engineering (3h)

• Introduction to prompt engineering: how to craft effective instructions for AI-powered tools
• Core prompt engineering techniques—one-shot, few-shot, chain of thought, tree of thought, decomposition, reflective prompts, meta-prompts
• Advanced procedural prompts for complex tasks
• Advanced ChatGPT tools—reasoning models, DeepResearch, Canvas
• Managing large context windows, planning conversation flows
• Working with your own files, creating a contextual knowledge base
• Reporting, analysis, and data visualization with AI

Module 5: Practical Workshop – Building Your Own AI Assistant (2.5h)

• Defining problems to solve with AI assistants, based on the organizational context
• Participants work on creating a prototype of a personal AI assistant for selected on-the-job use cases
• Presentation and evaluation of the solutions developed

Module 6: AI Safety – How to Use Artificial Intelligence Responsibly and Legally (1.5h)

• How does artificial intelligence use our data?
• Privacy policies of AI system providers
• Complying with GDPR requirements in the context of working with AI
• The AI Act—key provisions and requirements of the EU AI regulation
• Intellectual property law in the context of AI-generated content—current regulations and potential risks

Module 7: Practical Aspects of Implementing AI in Organizations (1h)

• Change management in the AI era—key elements of implementing AI solutions in an organization
• Building an AI culture—identifying harmful attitudes and fostering the right mindset toward AI
• Group discussion: planning AI tool adoption in the organization
• Training summary, QA session