AI for Managers – AI Management Lab: modern AI tools in managing the organization and processes

Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

Smarter use of AI tools - You will learn how to choose between ChatGPT, Copilot, Gemini, Claude and Perplexity, so you can match the right tool to each management task and avoid inefficient, scattered work.

Faster preparation of materials - With AI, you will create notes, reports, summaries, presentations and messages much faster, while keeping your communication consistent and improving the quality of materials for teams and leaders.

Effective prompting - You will master prompts with a clear role, goal, context and response format, so you can get more relevant outputs from AI and refine them more easily for real management needs.

Stronger team management - You will use AI to plan team work, define roles, prepare feedback, support onboarding and build development plans, making it easier to organize work and communicate clearly with employees.

Better decision support - You will learn how to use AI to compare options, assess risks, build scenarios and interpret KPIs, helping you prepare data-based recommendations and make decisions more efficiently.

Ideas for process improvement - You will identify processes worth enhancing with AI and build a list of practical use cases in sales, HR, marketing, finance and operations, with a focus on measurable business value.

Safe and responsible AI use - You will learn how to spot risks related to confidential data, model errors and overreliance on AI outputs, so you can use these tools safely and responsibly in your management work.

AI rollout plan for your team - You will leave the training with a simple AI implementation plan for your team or department, including goals, metrics, pilot areas and change communication, ready to put into action.

Training programme

1. Introduction to artificial intelligence in business

what artificial intelligence and generative AI are,
how tools such as ChatGPT, Copilot, Gemini, Claude or Perplexity work,
differences between a chatbot, an AI assistant, an AI agent and automation,
the most important AI trends in business and management,
examples of the use of AI in the work of managers and teams.

2. AI as support for the manager in daily work

preparing notes, summaries, reports and presentations,
creating internal and external communication with the help of AI,
analysis of documents, emails, offers, data and business information,
support in planning meetings, tasks and priorities,
faster preparation of recommendations, decisions and courses of action.

3. Prompting and effective work with AI tools

principles of creating effective commands for AI,
how to ask questions to obtain specific and useful answers,
structure of a good prompt: role, goal, context, data, response format,
techniques for refining and verifying AI responses,
creating your own prompt templates for a manager.

4. AI in team management

AI support in team work planning,
creating role descriptions, scopes of responsibilities and goals,
preparing feedback, conversation summaries and development plans,
AI in onboarding new employees,
support in the analysis of competencies, training needs and team development,
risks related to the use of AI in the area of HR and people management.

5. AI in decision-making and data analysis

how to use AI to analyze business information,
comparing decision variants with the help of AI,
identification of risks, opportunities and possible consequences of decisions,
creating simple SWOT analyses, scenarios and recommendations,
AI as support in the interpretation of data, reports and KPI indicators.

6. AI in business process optimization

identification of processes that can be improved with the help of AI,
automation of repetitive administrative and analytical tasks,
examples of the use of AI in sales, customer service, finance, HR, marketing and operations,
process mapping and indicating places where AI can bring the greatest value,
creating a list of potential AI implementations in the organization.

7. Security, ethics and responsible use of AI

what data should not be entered into AI tools,
confidentiality, data protection and information security,
AI hallucinations, errors and the risk of overreliance on tools,
verification of responses generated by AI,
principles of responsible use of AI in a manager's work,
the role of the manager in building a conscious culture of AI use.

8. AI implementation strategy in a team or organization

how to prepare the team to work with AI,
defining the goals and effectiveness measures of AI implementation,
how to choose pilot areas for implementation,
building a simple AI implementation plan in the department,
implementation barriers: employee resistance, lack of competencies, tool chaos,
how to communicate changes related to AI in the organization.

9. Practical workshop: AI in a manager's work

creating prompts for everyday managerial tasks,
analysis of a sample business problem using AI,
preparation of an action plan for a team or project,
developing ideas for automating selected processes,
creating an individual list of AI applications in the participants' work.

What are the prerequisites for participating in the training?

Management basics - You should have experience organizing your own work or a team’s work, so you can easily relate the training examples to decisions, communication and everyday responsibilities.

Confidence with a computer - You should be comfortable using a computer, browser, email and office documents, because during the training you will work with AI tools and digital materials.

Knowledge of company processes - You should know the core processes, tasks or challenges in your department, so you can build meaningful AI use cases during the workshop that fit your actual work.

Openness to testing tools - You should be ready to test new tools and ways of working on your own, because the training is based on exercises, iteration and practical verification of AI solutions.