AI for managers and team leaders

Key information

During the training, participants will find out, among other things:

• How generative AI works and how to choose a tool for managerial work
• How to build effective prompts with the KREDO method
• How to analyse operational data and prepare it for a decision
• How to describe a process, find repeatable activities in it and plan automation
• How to support task planning, meetings and communication with the team
• How to roll out AI responsibly in the department, taking GDPR and the AI Act into account

The training can be delivered using the AI tool of your choice: Microsoft Copilot, Gemini or Claude, depending on which solution the company uses or plans to use. The content stays the same; only the interface and configuration details differ.

Objective

The objective of the training is to familiarise participants with the capabilities of generative AI in the context of process management and team work. The training covers the basics of how AI tools work, effective prompting with the KREDO method, analysis of operational data, describing and improving processes, and the ethical and legal issues connected with using AI in an organisation. The emphasis is on working with a chosen AI tool on examples close to a manager’s everyday tasks, from preparing a decision, through planning and reporting, to assessing which activities in the department are worth entrusting to the tool.

Programme

Module 1: The basics of generative AI in a manager’s work

• Sharing participants’ experience
• Key concepts related to how AI works (prompt, token, hallucination, context)
• How to act in the face of false content created by AI
• Comparison of the key AI tools (Microsoft Copilot, Gemini, Claude) and choosing a tool for managerial work
• The role of AI in managing an organisation: where it genuinely shortens work and where it remains a promise
• Privacy and data security in AI tools

Module 2: Prompt engineering, the KREDO method

• Anatomy of an effective prompt, the KREDO model
• Techniques to start with: asking AI questions, generating variants, correcting answers
• Building prompts for managerial scenarios: a meeting summary, feedback, a status report
• Fast models versus advanced reasoning models: when to use which
• Working in a single thread instead of starting from scratch

Participants will learn to choose the tool and model to suit the purpose, instead of using one solution for everything.

Module 3: Data analysis and preparing decisions

• Analysing summaries and reports from spreadsheet files
• Drawing conclusions from operational data: trends, deviations, bottlenecks
• Comparison tables and simple visualisations as a basis for decisions
• Scenario and risk analysis: variants of how a situation may develop instead of a numerical forecast
• The limits of trust in numbers provided by AI and the duty to verify them against the source

Module 4: Processes: describing, improving, automating

• Describing and organising an existing process with the help of AI
• Identifying repeatable activities and candidates for automation
• Designing process improvements and assessing their feasibility
• What AI assistants are and how they take over the team’s repeatable tasks
• Configuring an assistant or global instructions for a standing process in the department
• An overview of workflow automation tools and the situations in which they make sense

Module 5: Leading the team and measuring work

• Planning tasks, priorities and schedules
• Preparing meetings, agendas and notes of what was agreed
• Drafting communication to the team and to superiors
• Measuring process effectiveness: which indicators can be collected and how AI helps describe them

Module 6: Rolling out AI in the organisation: risk, ethics, good practice

• What can be passed to public AI and what must stay inside the company
• Personal data, GDPR and trade secrets in a manager’s work
• The AI Act: the four risk levels in a nutshell
• A manager’s responsibility for results generated by AI

Trainer

Franciszek Kołpanowicz: entrepreneur and certified AI trainer who helps leaders and teams become more effective through intelligent technologies. He has been published in Rzeczpospolita, among other places. He has more than 2,000 hours of work with generative AI behind him and shares his knowledge at public events, including the “Manager in the Age of AI” training organised by Rzeczpospolita, as well as at the UKEN and PASE conferences.

His background in philosophy (Jagiellonian University) and his experience in IT quality control allow him to combine analytical thinking with asking the right questions. His own practical journey with AI showed him how this technology can become a real lever for growth.

Drawing on hands-on experience, he shows leaders and their teams how to use AI not only to work more efficiently but also to think more clearly and make faster business decisions. His AI training has, among other results, cut the time needed for routine analysis of multi-page legal documentation by 80%.

In his training sessions he pays particular attention to the participants themselves, drawing on their experience and needs as the work progresses. As a result, his sessions are not repetitive routine but an enriching and individual experience.

His mission is to make artificial intelligence a practical tool for development: business, intellectual and cultural.

Prerequisites

The training does not require any prior experience with AI tools. Basic computer and browser skills are necessary, as is access to the chosen AI tool, agreed with the client before the training.

Organisational requirements on the client’s side

• Before the training, every participant has an account for the chosen AI tool (Microsoft Copilot, Gemini or Claude, depending on what is agreed) that has been set up and tested
• Login checked in advance on the device the participant will work on
• One workstation per person: a laptop for each participant (their own or provided by the organiser), not shared
• Stable Wi-Fi in the room, sufficient for all participants working at the same time
• A projector or large screen for the trainer’s presentation
• A room suitable for workshop-style work (tables, space for notes)
• A flipchart or whiteboard with markers

Methodological note: the training works with one jointly chosen AI tool, so that within one day participants have time to genuinely master it in the context of their own work, rather than just seeing a few demonstrations. The choice of the specific tool and the detailed scope will be confirmed during the needs survey before the training.

To be confirmed before the training

Licences and access:

• Which AI tool does the company use or plan to use (Microsoft Copilot, Gemini, Claude)? The choice is made before the training, based on the needs survey.
• Does every participant have their OWN access, or do participants share one account? With a shared account the exercises do not work.
• If Microsoft Copilot: do participants have an active Microsoft 365 subscription (Business or Enterprise)? Full integration in Word, Excel and PowerPoint additionally requires Microsoft 365 Copilot.
• If Gemini: are participants working on free accounts or on a paid plan? The programme works on the free version; a paid plan raises the limits. Working with company email and Drive requires access to be enabled separately by the organisation’s administrator.

Participants’ technical readiness (CRITICAL):

• Every participant must arrive with a logged-in account on their own laptop: we do NOT set up accounts in the training room
• Test before the training: every participant opens the tool and verifies that they can ask a question and receive an answer
• If any participant does not have access: advance notice, and we will prepare an alternative path

Infrastructure:

• Stable Wi-Fi tested under load (all participants working simultaneously in the browser and in applications)

Key information

During the training, participants will find out, among other things:

• How generative AI works and how to choose a tool for managerial work
• How to build effective prompts with the KREDO method
• How to analyse operational data and prepare it for a decision
• How to describe a process, find repeatable activities in it and plan automation
• How to support task planning, meetings and communication with the team
• How to design AI agents using the KREDOS method and configure their knowledge base
• How to work in Gemini Notebook with sources uploaded to the tool
• How to use the advanced functions of the chosen AI tool
• How to support your work with Fireflies and Gamma AI
• How to roll out AI responsibly in the department, taking GDPR and the AI Act into account

The training can be delivered using the AI tool of the client’s choice: Microsoft Copilot, Gemini or Claude, depending on which solution the company uses or plans to use. The scope of content remains the same; what differs are the details of the interface, the configuration and the set of advanced functions covered on Day 2.

Objective

Educational objective: The service “Using AI in Process Management, AI for Managers (2 days)” leads to the acquisition of competences and prepares participants to use generative AI tools independently in managing a team’s work and the running of processes: to prepare material for a decision on the basis of operational data, to describe a process and indicate the activities suitable for automation, to plan work, run meetings and communicate with the team, and also to design an AI agent that takes over a repeatable team task and to work with sources uploaded to the tool, in compliance with the data protection rules in force in the organisation.

The service ends with the acquisition of competences. The educational objective is elaborated below in three dimensions: the main objective, the thematic scope and the result.

Main objective: Raising the qualifications of senior staff in using generative AI to manage a team’s work and the running of processes, and preparing the manager for the role of the person introducing AI tools in their department. The training prepares participants to assess independently which activities are worth entrusting to an AI tool and which remain with the human, to design an AI agent for a repeatable team task, and to lead this change in a way that complies with the data protection requirements in force in the organisation.

Thematic scope: Day 1 covers the basics of how generative AI tools work and the concepts needed for informed work with a model, prompting with the KREDO method in managerial scenarios, analysis of operational data and preparation of material for a decision, describing and improving processes including identifying repeatable activities, and support in task planning, preparing meetings and communicating with the team. Day 2 covers AI agents and the KREDOS method, working in Gemini Notebook with sources uploaded to the tool, tools that support meeting notes and the preparation of presentations and proposals, the advanced functions of the chosen AI tool, and, to conclude, legal and ethical issues: personal data protection, GDPR, trade secrets, the risk levels under the AI Act and the manager’s responsibility for results generated by AI.

Result: After completing the training, the participant builds prompts using the KREDO method instead of formulating queries ad hoc, prepares with the help of AI summaries, comparison tables and scenario variants as material for a decision, describes a process in their department and identifies the activities in it suitable for automation, and prepares meeting agendas, notes of what was agreed and communication to the team and superiors more quickly. Instead of building a prompt from scratch for every repeatable task, they configure an AI agent with its own knowledge base, use deep research and task scheduling in the chosen tool, and select tools for meeting notes and for preparing presentations. For each of these tasks, they verify the model’s answer against the source and recognise which data must not be passed to a public tool.

Learning outcomes and verification criteria

After completing the service, the participant:

Programme

Day 1: Foundations, data and processes in a manager’s work

Module 1: The basics of generative AI in a manager’s work

• Sharing participants’ experience
• Key concepts related to how AI works (prompt, token, hallucination, context)
• How to act in the face of false content created by AI
• Comparison of the key AI tools (Microsoft Copilot, Gemini, Claude) and choosing a tool for managerial work
• The role of AI in managing an organisation: where it genuinely shortens work and where it remains a promise
• Privacy and data security in AI tools

Module 2: Prompt engineering, the KREDO method

• Anatomy of an effective prompt, the KREDO model
• Techniques to start with: asking AI questions, generating variants, correcting answers
• Building prompts for managerial scenarios: a meeting summary, feedback, a status report
• Fast models versus advanced reasoning models: when to use which
• Working in a single thread instead of starting from scratch

Module 3: Data analysis and preparing decisions

• Analysing summaries and reports from spreadsheet files
• Drawing conclusions from operational data: trends, deviations, bottlenecks
• Comparison tables and simple visualisations as a basis for decisions
• Scenario and risk analysis: variants of how a situation may develop instead of a numerical forecast
• The limits of trust in numbers provided by AI and the duty to verify them against the source

Module 4: Processes: describing, improving, automating

• Describing and organising an existing process with the help of AI
• Identifying repeatable activities and candidates for automation
• Designing process improvements and assessing their feasibility
• What AI assistants are and how they take over the team’s repeatable tasks
• Configuring an assistant or global instructions for a standing process in the department
• An overview of workflow automation tools and the situations in which they make sense

Module 5: Leading the team and measuring work

• Planning tasks, priorities and schedules
• Preparing meetings, agendas and notes of what was agreed
• Drafting communication to the team and to superiors
• Measuring process effectiveness: which indicators can be collected and how AI helps describe them

Day 2: AI agents, the toolkit and rollout in the department

Module 6: AI agents in a manager’s work

• What AI agents are and how they differ from a single prompt
• Agent versus AI assistant: scope of action and limitations compared with an ordinary conversation with a model
• The components of an agent: the system instruction, the knowledge base, the user’s command
• The KREDOS method: designing an agent together with standards, that is, the limits of its action
• An agent that tidies up work after a meeting: a note, a task list, correspondence
• An agent that prepares a status report and documents on the basis of a brief
• Configuring the knowledge base: the team’s documents and procedures in the agent
• When an agent does not work and how to recognise a task better left to a human

Module 7: Gemini Notebook, working with sources uploaded to the tool

• What Gemini Notebook is and when it works better than an ordinary conversation with a model
• Adding sources: documents, spreadsheets, presentations, web pages, audio and video recordings
• Asking questions about uploaded materials, with references to specific passages in the sources
• Summarising extensive project and process documentation for the purposes of a decision
• Audio podcasts based on uploaded materials, that is, a two-voice discussion of a document
• Other formats generated from sources: notes, mind maps, flashcards and quizzes
• The team’s internal knowledge base and preparing for a meeting on the basis of uploaded materials

Module 8: Additional AI tools in a manager’s work

• Fireflies: automatic notes from online meetings
• Configuring Fireflies connected to the calendar, so that the bot joins scheduled meetings automatically
• Comparing the free and paid Fireflies plans in terms of archive length, integrations and transcription limits
• Searching the meeting archive for agreements and guidelines
• Gamma AI: creating presentations and styled proposals from a description
• Materials for a meeting and a meeting with the board, prepared from an outline
• Criteria for choosing an additional tool: cost, data security, implementation effort

Module 9: Advanced functions of the chosen AI tool

The scope of this module is adapted to the choice of model made before the training, because advanced functions differ between providers and change from quarter to quarter. Some capabilities are common to all solutions: deep research with analysis of multiple sources (deep research), including verification of citations before the results are used, and task scheduling, that is, recurring queries and the monitoring of chosen topics carried out without the user’s involvement.

The remaining functions are covered in the variant appropriate to the chosen tool. In Gemini this is Canvas mode, that is, interactive work with a document, changing its length, style and tone, and creating web pages and interactive materials. In ChatGPT: websites created from a description in natural language, a browser agent performing tasks in a browser window, skills, projects that organise conversations and files around a single topic, and plugins. In Claude: projects, skills and connectors linking the model to company systems.

The choice of variant is made before the training, together with the decision on the main tool, on the basis of a needs survey. The scope is then confirmed with the client in writing.

Module 10: Rolling out AI in the organisation: risk, ethics, good practice

• What can be passed to public AI and what must stay inside the company
• Personal data, GDPR and trade secrets in a manager’s work
• The AI Act: the four risk levels in a nutshell
• A manager’s responsibility for results generated by AI

Trainer

Franciszek Kołpanowicz: entrepreneur and certified AI trainer who helps leaders and teams become more effective through intelligent technologies. He has been published in Rzeczpospolita, among other places. He has more than 2,300 hours of work with generative AI and more than 2,000 hours of work with training groups behind him, and he shares his knowledge at public events, including the “Manager in the Age of AI” training organised by Rzeczpospolita, as well as at the UKEN and PASE conferences.

His background in philosophy (Jagiellonian University) and his experience in IT quality control allow him to combine analytical thinking with asking the right questions. His own practical journey with AI showed him how this technology can become a real lever for growth.

Drawing on hands-on experience, he shows leaders and their teams how to use AI not only to work more efficiently but also to think more clearly and make faster business decisions. His AI training has, among other results, cut the time needed for routine analysis of multi-page legal documentation by 80%.

In his training sessions he pays particular attention to the participants themselves, drawing on their experience and needs as the work progresses. As a result, his sessions are not repetitive routine but an enriching and individual experience.

His mission is to make artificial intelligence a practical tool for development: business, intellectual and cultural.

Prerequisites

The training does not require previous experience with AI tools. Basic skills in using a computer and a browser are necessary, as is access to the chosen AI tool, agreed with the client before the training. Module 7 is run in Gemini Notebook, which works on a free Google account regardless of the main tool chosen for the training. Module 8 covers free Fireflies and Gamma AI accounts.

Organisational requirements on the client’s side

• Before the training, every participant has an account for the chosen AI tool (Microsoft Copilot, Gemini or Claude, depending on what is agreed) that has been set up and tested
• Login checked in advance on the device the participant will work on
• One workstation per person: a laptop for each participant (their own or provided by the organiser), not shared
• Stable Wi-Fi in the room, sufficient for all participants working at the same time
• A projector or large screen for the trainer’s presentation
• A room suitable for workshop-style work (tables, space for notes)
• A flipchart or whiteboard with markers

Methodological note: the training works with one jointly chosen main tool across both days, so that participants have time to genuinely master using it in the context of their own work, rather than merely see a few demonstrations. The additional tools from Day 2 are covered as a supplement and do not replace the main tool. The choice of the specific tool and the detailed scope will be finalised during the needs survey before the training.

To be confirmed before the training

Licences and access:

• Which AI tool does the company use or plan to use (Microsoft Copilot, Gemini, Claude)? The choice is made before the training, based on the needs survey.
• Does every participant have their OWN access, or do participants share one account? With a shared account the exercises do not work.
• If Microsoft Copilot: do participants have an active Microsoft 365 subscription (Business or Enterprise)? Full integration in Word, Excel and PowerPoint additionally requires Microsoft 365 Copilot.
• If Gemini: are participants working on free accounts or on a paid plan? The programme works on the free version; a paid plan raises the limits. Working with company email and Drive requires access to be enabled separately by the organisation’s administrator.

Participants’ technical readiness (CRITICAL):

• Every participant must arrive with a logged-in account on their own laptop: we do NOT set up accounts in the training room
• Test before the training: every participant opens the tool and verifies that they can ask a question and receive an answer
• If any participant does not have access: advance notice, and we will discuss an alternative way of working

Infrastructure:

• Stable Wi-Fi tested under load (all participants working simultaneously in the browser and in applications)

Learning outcome · Verification criteria · Validation method

Explains what a prompt and a hallucination are Indicates how to tell that AI has made up an answer Indicates which AI tool to choose for their task Indicates what data must not be entered into public AI Lists the four risk levels under the AI Act · Defines the terms: prompt, context, hallucination Recognises false content generated by AI and states how to verify it Compares the available AI tools and justifies the choice of one of them for a managerial task · Theory test

Creates prompts using the KREDO method for managerial scenarios (Module 2) · Creates a prompt containing all five elements of the KREDO method Chooses a fast model or a model with advanced reasoning to suit the type of task Corrects the model’s answer by working in a single thread instead of starting over · Observation

Prepares material for a decision on the basis of operational data (Module 3) · Analyses a summary and identifies trends, deviations and bottlenecks in it Creates a comparison table serving as the basis for a decision Verifies the numbers given by AI against the source and assesses the limits of trust in them · Observation

Describes a process and plans its improvement (Module 4) · Describes and organises the course of an existing process with the help of AI Identifies repeatable activities in the process and indicates candidates for automation Configures an assistant or global instructions for a standing task in the department · Observation

Applies AI in leading the team and measuring work (Module 5) · Plans tasks, priorities and the team’s work schedule using AI Creates a meeting agenda and a note of what was agreed Drafts communication to the team and to superiors in a given tone · Observation

Designs an AI agent for a repeatable team task (Module 6) · Defines the components of an agent: the system instruction, the knowledge base and the user’s command Creates an agent using the KREDOS method, together with standards setting the limits of its action Assesses which task suits an agent and which should be left to a human · Observation

Works in Gemini Notebook on sources uploaded to the tool (Module 7) · Adds sources and asks questions about them with reference to specific passages Creates a summary of extensive documentation for the purposes of a decision Generates material from the sources in a chosen format: a note, a mind map or a podcast · Observation

Selects additional AI tools for managerial tasks (Module 8) · Configures automatic meeting notes and searches their archive Creates a presentation or proposal on the basis of an outline Assesses a tool in terms of cost, data security and implementation effort · Observation

Uses the advanced functions of the chosen AI tool (Module 9) · Runs deep research and verifies the citations in the generated report Configures a task schedule monitoring a given topic Discusses the advanced functions available in the tool chosen for the training · Observation

Key information

During the training, participants will find out, among other things:

• How generative AI works and how the available tools differ
• How to build effective prompts with the KREDO method
• How to draft communication to the team, meeting notes and reports, and work with extensive documentation
• How to use Gemini in Gmail, Docs, Sheets and Google Drive
• How to work in NotebookLM with uploaded documents, with references to sources
• How to use Deep Research for in-depth analysis of market and industry information
• How to work with Canvas and create web pages, podcasts and infographics in Gemini
• How to design your own AI assistants with the KREDOS method
• How to support your work with Fireflies and Gamma AI
• How to look after the security of the team’s data when using AI

The training is based on working with Gemini in the Google Workspace environment and includes a comparison with other tools available on the market (ChatGPT, Copilot). The workshop scenarios are chosen to match the tasks participants perform in their managerial role.

Objective

The objective of the training is to familiarise participants with the capabilities of Gemini in the context of a manager’s everyday work, to a wider extent than a single training day allows. The programme leads from the basics of how generative models work and prompting with the KREDO method, through work with documents, documentation and team communication and applications in Google Workspace and NotebookLM, to advanced functions and designing AI assistants using the KREDOS method. The emphasis is on practical applications in the tasks participants perform, from preparing a decision to reporting, and on safe work with company data.

Programme

Day 1: Foundations and a manager’s everyday work

Module 1: The basics of generative AI in a manager’s work

• Sharing participants’ experience: how they use AI today and what they find most difficult
• Key concepts related to how AI works: prompt, context, context window, hallucination
• How to act in the face of false content created by AI: verifying responses and sources
• Comparing AI tools: Gemini, ChatGPT, Copilot
• Privacy and data security in AI tools

Module 2: Prompt engineering: the KREDO method

• The anatomy of an effective prompt: the KREDO model
• “Best starter prompts” techniques: questions to the AI, generating options, correcting responses
• Building KREDO prompts for typical managerial scenarios: a meeting summary, feedback, a status report
• Correcting AI responses: working in one thread instead of starting over
• Fast vs advanced models: when to use which

Module 3: Creating and drafting documents and communication

• Drafting letters, notes and communication to the team in a given tone
• Editing existing documents: shortening, simplifying the language, changing the style
• Recurring documents and forms prepared from a template
• Meeting summaries and status reports based on working materials
• Checking a document for consistency and completeness before sending

Module 4: Working with documentation: searching, classification, archiving

• Loading contracts, terms and conditions, reports and procedures as sources for analysis
• Asking questions about a document and extracting provisions relevant to a decision
• Summarising lengthy documents for a note or a decision
• Comparing document versions and detecting differences
• Describing documents for later search and archiving

Module 5: Gemini in Google Workspace

• Gemini in Gmail: searching correspondence, summarising threads and preparing replies
• Gemini in Google Docs: drafting and organising content
• Gemini in Google Sheets: summaries and analysis of operational data
• Gemini in Google Drive: searching for and summarising materials
• Gemini in Calendar and Google Meet: organising the team’s work and meetings
• Configuring Gemini’s access to Google Workspace resources

Module 6: NotebookLM: working with sources uploaded to the tool

• What NotebookLM is and when it works better than an ordinary chat
• Adding sources: documents, spreadsheets, presentations, web pages, audio and video recordings
• Asking questions about uploaded materials, with references to specific passages in the sources
• Generating content from sources: audio summaries, notes, mind maps, quizzes
• Use cases: the team’s knowledge base, analysis of documentation, preparing for a meeting on the basis of uploaded materials

Day 2: Advanced functions, assistants and the manager’s toolkit

Module 7: Advanced Gemini features

• Deep Research: in-depth search and analysis of industry, market and competitor information
• Canvas: interactive work on a document, changing the length, style and tone of a text
• Creating web pages and interactive materials
• Generating audio podcasts and infographics from your own content
• Working with files: analysing documents, reports, spreadsheets and presentations
• Scheduled tasks in Gemini: automatic monitoring of selected websites and topics
• Global instructions: standing guidelines saved once and taken into account by Gemini in every subsequent conversation, without repeating them in prompts

Module 8: AI assistants in Gemini

• What assistants (Gems) are and how they differ from a single prompt
• AI assistant vs AI agent: scope of operation and limitations
• The components of an assistant: system instruction, knowledge base, user command
• The KREDOS method: designing an assistant together with standards, that is, the boundaries of its operation
• Designing an assistant tailored to a manager’s everyday tasks
• An assistant that tidies up work after a meeting: a note, a task list, correspondence
• An assistant that prepares documents and presentations from a brief
• Configuring the knowledge base: team documents and procedures in the assistant

Module 9: Additional AI tools

• Fireflies: automatic notes from online meetings
• Gamma AI: creating presentations and styled proposals
• 11labs: voice cloning and creating an avatar

Module 10: Information security and good practice

• What can be passed to public AI and what must stay inside the company
• Personal data, GDPR and trade secrets in a manager’s work
• Anonymising content before passing it to an AI tool
• Account privacy settings and control over conversation history
• Good practice for working with AI in a team

Module 11: Summary and Q&A session

• A methodology for working with AI on company data: testing and refining prompts
• Training summary
• Recommended apps
• Q&A session

Trainer

Franciszek Kołpanowicz: entrepreneur and certified AI trainer who helps leaders and teams become more effective through intelligent technologies. He has been published in Rzeczpospolita, among other places. He has more than 2,000 hours of work with generative AI behind him and shares his knowledge at public events, including the “Manager in the Age of AI” training organised by Rzeczpospolita, as well as at the UKEN and PASE conferences.

His background in philosophy (Jagiellonian University) and his experience in IT quality control allow him to combine analytical thinking with asking the right questions. His own practical journey with AI showed him how this technology can become a real lever for growth.

Drawing on hands-on experience, he shows leaders and their teams how to use AI not only to work more efficiently but also to think more clearly and make faster business decisions. His AI training has, among other results, cut the time needed for routine analysis of multi-page legal documentation by 80%.

In his training sessions he pays particular attention to the participants themselves, drawing on their experience and needs as the work progresses. As a result, his sessions are not repetitive routine but an enriching and individual experience.

His mission is to make artificial intelligence a practical tool for development: business, intellectual and cultural.

Prerequisites

The training does not require any previous experience with AI tools. On the participants’ side, the following must be provided:

• A computer workstation for each participant: one laptop per person, not shared
• A Google account with access to Gemini for each participant.
• An account in the organisation’s Google Workspace domain: the fifth module involves working on the participant’s own email, documents, spreadsheets and Drive resources
• Login to gemini.google.com checked in advance on the device the participant will work on

Organisational requirements on the client’s side

• Stable Wi-Fi in the room, sufficient for all participants working at the same time
• A projector or large screen for the trainer’s presentation
• A room suitable for workshop-style work (tables, space for notes)
• A flipchart or whiteboard with markers

To be confirmed before the training

Licences and access:

• Does every participant have their OWN work account, or do they share one?
• Which Google Workspace plan does the organisation have?
• Gemini access to Google Workspace applications (Gmail, Drive, Docs, Sheets) switched on: a setting on the organisation’s administrator side

Participants’ technical readiness (CRITICAL):

• Every participant must arrive with a Google Workspace account already signed in on their own laptop: we do NOT set up accounts in the training room
• Please run a test before the training: each participant opens gemini.google.com on their work account and checks that they can ask a question and receive an answer
• If any participant does not have access to Gemini: please let us know in advance and we will discuss an alternative route

Infrastructure:

• Stable Wi-Fi

Key information

Language: English

Objective

The objective of the training is to familiarise participants with the practical use of Microsoft Copilot and AI tools in the context of a Team Leader’s everyday challenges: from analysing team data, through preparing reports and communication, to the conscious and responsible use of AI in managerial work. The training emphasises building real prompting skills and critical evaluation of AI results, set within leadership scenarios.

Learning outcomes

• The ability to build effective prompts using the KREDO method, adapted to a leader’s tasks
• Practical knowledge of how to use Copilot in Excel, Word, PowerPoint, Outlook and Teams
• An understanding of the framework for responsible use of AI (the 4D method: Delegation, Description, Discernment, Diligence)
• Knowledge of data security and the AI Act rules relevant to managerial work
• A ready working document created during the workshop, useful in everyday work

Programme

Module 1: The basics of generative AI and responsible use of AI

• Exchange of participants’ experiences: how Team Leaders use AI today
• Key concepts: prompt, context, context window, hallucination
• Comparing AI tools: Microsoft Copilot vs ChatGPT vs Gemini: when to use which
• The 4D method (Delegation, Description, Discernment, Diligence): a framework for the responsible use of AI in a leadership role
• Data security: Copilot M365 (company) vs public tools: what can be passed to AI and what cannot
• The AI Act: the 4 risk levels in a nutshell
• Moderated discussion: the Team Leader’s responsibility for results generated by AI

Module 2: Prompt engineering: the KREDO method

• The anatomy of an effective prompt: the KREDO model
• Live demonstration: leadership scenarios (a team meeting summary, feedback for an employee, a status report for a superior)
• Techniques for correcting AI responses and generating options to choose from
• Fast models vs advanced reasoning models: when to use which
• The “one conversation = one thread” principle
• Practical exercises: participants build KREDO prompts on scenarios prepared by the trainer

Module 3: Microsoft Copilot in a Team Leader’s work

• Analysing team data in Excel: reporting results, creating formulas from a prompt, identifying trends
• Creating working documents in Word: procedures, summaries, project briefs
• Preparing status presentations in PowerPoint
• Managing communication in Outlook: thread summaries, prioritisation, draft replies
• Meeting notes in Teams: extracting tasks and decisions
• Workshop: each participant creates one working document that is useful in their daily work

Organisational requirements on the client’s side

• Each participant works on their own laptop, signed in to a work Microsoft 365 account
• Stable Wi-Fi in the room, sufficient for 12 people working at the same time
• A projector or large screen for the trainer’s presentation
• A room suitable for workshop-style work (tables, space for notes)
• A flipchart or whiteboard with markers

TO BE CONFIRMED BEFORE THE TRAINING

Licences and access:

• Does every participant have a Microsoft 365 Copilot licence (Copilot Pro)? A Microsoft 365 account alone is NOT the same as Copilot Pro. Without this licence, Copilot does not work in the Office applications (Word, Excel, PowerPoint, Outlook). The programme is prepared for both cases, but the scope of the practical exercises will differ.
• Does every participant have their OWN licence, or do they share one account? (With a shared account the exercises will not work)
• Which version of Microsoft Outlook do participants use? (classic vs new Outlook) The Copilot interface differs between versions.
• Is the Copilot add-in visible in the Office applications for every participant? (Please verify before the training)

Participants’ technical readiness (CRITICAL):

• Every participant must arrive with an M365 account already signed in on their own laptop: we do NOT set up accounts in the training room
• Please run a test before the training: each participant opens copilot.microsoft.com and checks that they can ask a question and receive an answer
• If any participant does not have access to Copilot: please let us know in advance and we will prepare an alternative route

Infrastructure:

• Stable Wi-Fi tested under load (12 people working at the same time in the browser and Office applications)

The training works with one main tool (Microsoft Copilot), so that participants have time to genuinely master using it in the context of their own work, rather than merely see a few demonstrations.

Trainer

Franciszek Kołpanowicz: entrepreneur and certified AI trainer. He has been published in Rzeczpospolita, among other places. He has more than 2,000 hours of work with generative AI behind him and has shared his knowledge at public events, including the “Manager in the Age of AI” training organised by Rzeczpospolita and the UKEN and PASE conferences. His background in philosophy (Jagiellonian University) and his experience in IT quality control allow him to combine analytical thinking with asking the right questions. In his training sessions he pays particular attention to the participants themselves, drawing on their experience and needs as the work progresses.

Key information

Language: English

Objective

The objective of the training is to familiarise participants with the practical use of Microsoft Copilot and AI tools in the context of a Team Leader’s everyday challenges. Day 1 builds the foundation: prompting with the KREDO method, applications of Copilot in M365 apps, and the responsible use of AI. Day 2 takes participants to the level of creating their own AI Agents and automating repeatable leadership processes, without coding.

Learning outcomes

• The ability to build effective prompts using the KREDO method, adapted to a leader’s tasks
• Practical knowledge of how to use Copilot in Excel, Word, PowerPoint, Outlook and Teams
• An understanding of the framework for responsible use of AI (the 4D method: Delegation, Description, Discernment, Diligence)
• The ability to design and configure your own AI agent in Microsoft Copilot
• A ready, working AI Agent that prepares working documents on the basis of meeting transcripts and correspondence
• Knowledge of the differences between AI models and an informed choice of tool for the task

Differences between the 1-day and 2-day options

The 1-day option gives participants solid foundations: effective prompting, practical uses of Copilot in M365 and a framework for responsible use of AI.

The 2-day option goes further. Each participant leaves the training with a ready, working AI Agent that automates their repeatable leadership processes (for example, turning a meeting transcript into a brief, a checklist and a status report). In addition, participants learn about the differences between AI models and learn to choose a tool consciously for a specific task.

The key difference: after day 1 participants know how to use AI. After day 2 they have a deployed solution that saves them time in their daily work straight away.

Programme

DAY 1

Module 1: The basics of generative AI and responsible use of AI

• Exchange of participants’ experiences: how Team Leaders use AI today
• Key concepts: prompt, context, context window, hallucination
• Comparing AI tools: Microsoft Copilot vs ChatGPT vs Gemini: when to use which
• The 4D method (Delegation, Description, Discernment, Diligence): a framework for the responsible use of AI in a leadership role
• Data security: Copilot M365 (company) vs public tools: what can be passed to AI and what cannot
• The AI Act: the 4 risk levels in a nutshell
• Moderated discussion: the Team Leader’s responsibility for results generated by AI

Module 2: Prompt engineering: the KREDO method

• The anatomy of an effective prompt: the KREDO model
• Live demonstration: leadership scenarios (a team meeting summary, feedback for an employee, a status report for a superior)
• Techniques for correcting AI responses and generating options to choose from
• Fast models vs advanced reasoning models: when to use which
• The “one conversation = one thread” principle
• Practical exercises: participants build KREDO prompts on scenarios prepared by the trainer

Module 3: Microsoft Copilot in a Team Leader’s work

• Analysing team data in Excel: reporting results, creating formulas from a prompt, identifying trends
• Creating working documents in Word: procedures, summaries, project briefs
• Preparing status presentations in PowerPoint
• Managing communication in Outlook: thread summaries, prioritisation, draft replies
• Meeting notes in Teams: extracting tasks and decisions
• Workshop: each participant creates one working document that is useful in their daily work

DAY 2

Module 4: Creating a personal AI agent in Microsoft Copilot

• Prompt vs agent: how they differ and when it is worth creating an agent
• Designing the Agent’s role to fit a Team Leader’s tasks (for example, a team data analyst, a reporting assistant, a meeting organiser)
• Examples of applications: preparing recurring reports, meeting summaries, creating project plans, organising the team’s knowledge
• Creating a personalised agent in Microsoft Copilot using the KREDOS model
• Exercise: each participant designs and tests their own AI agent

Module 5: Automating a leader’s work with AI

• A Copilot agent for working with Excel files: automated analysis and reporting
• A Copilot agent for working with Word documents: generating procedures and briefs
• The Copilot Agent in work with PowerPoint presentations: creating status slides
• A Copilot agent for working with Outlook email: prioritisation and draft replies
• Workshop: designing a real leadership process using AI: from a meeting transcript to a ready set of documents (a project brief, an action checklist, a status report, a note of decisions)

Module 6: AI models in practice

• AI models available on the market: strengths and limitations
• AI at home vs AI in a corporation: differences in capabilities
• Uses of multimodal models: creating graphics
• AI toolkit: a review of the best tools for creating presentations and transcribing meetings
• Automating work: the possibilities of Zapier and n8n
• Exercise: comparing the responses of different tools to the same task

Participants will learn to choose a tool to fit the goal, instead of using one model for everything. They will improve the efficiency and quality of their work.

Organisational requirements on the client’s side

• Each participant works on their own laptop, signed in to a work Microsoft 365 account
• Stable Wi-Fi in the room, sufficient for 12 people working at the same time
• A projector or large screen for the trainer’s presentation
• A room suitable for workshop-style work (tables, space for notes)
• A flipchart or whiteboard with markers

TO BE CONFIRMED BEFORE THE TRAINING

Licences and access:

• Does every participant have a Microsoft 365 Copilot licence (Copilot Pro)? A Microsoft 365 account alone is NOT the same as Copilot Pro. Without this licence, Copilot does not work in the Office applications (Word, Excel, PowerPoint, Outlook). The programme is prepared for both cases, but the scope of the practical exercises will differ.
• Does every participant have their OWN licence, or do they share one account? (With a shared account the exercises will not work)
• Which version of Microsoft Outlook do participants use? (classic vs new Outlook) The Copilot interface differs between versions.
• Is the Copilot add-in visible in the Office applications for every participant? (Please verify before the training)

Participants’ technical readiness (CRITICAL):

• Every participant must arrive with an M365 account already signed in on their own laptop: we do NOT set up accounts in the training room
• Please run a test before the training: each participant opens copilot.microsoft.com and checks that they can ask a question and receive an answer
• If any participant does not have access to Copilot: please let us know in advance and we will prepare an alternative route

Infrastructure:

• Stable Wi-Fi tested under load (12 people working at the same time in the browser and Office applications)

Online verification of access to AI agents in Microsoft Copilot (critical for the 2-day option):

Before the training it is necessary to check with participants (or with one representative participant, if identical permissions are assumed across the group):

• Are the Microsoft agents Researcher and Analyst visible and working?
• Can company knowledge from SharePoint or Office documents (company sources) be connected to an agent?
• Can a participant create their own agent, and does that agent answer questions?
• Do all participants have the same level of permissions?

Each of these elements is controlled by a separate switch in the Microsoft 365 admin centre: in practice a user may see an agent in the list but lack the permissions to talk to it. For this reason, confirming that the agents merely appear in the UI is not enough.

Verification can be carried out in three ways: (1) confirmation from the client’s IT administrator, (2) a short online session with the trainer before the training (a separately priced service), (3) commissioning a full technical verification.

Without confirmation of these points, the agent-building workshop on the second day may turn out to be impossible to deliver in full: in that case the workshop part will be replaced by a presentation.

The training works with one main tool (Microsoft Copilot), so that participants have time to genuinely master using it in the context of their own work, rather than merely see a few demonstrations.

Trainer

Franciszek Kołpanowicz: entrepreneur and certified AI trainer. He has been published in Rzeczpospolita, among other places. He has more than 2,000 hours of work with generative AI behind him and has shared his knowledge at public events, including the “Manager in the Age of AI” training organised by Rzeczpospolita and the UKEN and PASE conferences. His background in philosophy (Jagiellonian University) and his experience in IT quality control allow him to combine analytical thinking with asking the right questions. In his training sessions he pays particular attention to the participants themselves, drawing on their experience and needs as the work progresses.